BI Trend Monitor 2020 - BARC Research Study The world's largest survey of BI trends - Controller Institut Insights

BI Trend Monitor 2020
    The world's largest survey of BI trends

           BARC Research Study
BI Trend Monitor 2020                                 Sponsors

©2019 BARC – Business Application Research Center   BI Trend Monitor 2020   3
Authors                                                  BI Trend Monitor 2020

                      Larissa Baier            Timm Grosser
                      Senior Analyst           Senior Analyst

                      Dr. Carsten Bange        Lars Iffert
                      Founder & CEO            Analyst

                      Annika Baumhecker        Nikolai Janoschek
                      Research Analyst         Analyst

                      Jacqueline Bloemen       Patrick Keller
                      Senior Analyst           Senior Analyst

                      Dr. Sebastian Derwisch   Ann-Katrin Neeb
                      Analyst                  Research Analyst

                      Dr. Christian Fuchs      Robert Tischler
                      Senior Analyst           Senior Analyst

4   BI Trend Monitor 2020                      ©2019 BARC – Business Application Research Center
BI Trend Monitor 2020                                                  Table of Contents

                                                          34 | Advanced Analytics/Machine Learning/AI
     6      | Foreword
                                                          36 | Big Data Analytics

     8      | Management Summary                          38 | Integrated Platforms for BI and PM

                                                          40 |3 Embedded BI and Analytics
     11     | Survey Results                              42 |3 Data Storytelling

                                                          44 |3 Mobile BI
           12 | BI Trends Overview
                                                          46 |3 Analytics Teams/Data Labs
           14 | BI Trends Development
                                                          48 |3 Using External/Open Data

     16 | The Trends in Detail                            50 |3 Cloud BI for Data & Analytics

           16 | Master Data/Data Quality Management       52 |3 Data Catalogs

           18 | Data Discovery/Visualization              54 |3 Process Mining

           20 | Establishing a Data-Driven Culture

           22 | Data Governance
                                                      56 | Recommendations
           24 | Self-Service BI
                                                      59 | Sample & Methodology
           26 | Data Preparation by Business Users

           28 | Data Warehouse Modernization          60 | BARC Company Profile
           30 | Agile BI Development
                                                      62   |   Sponsor Profiles
           32 | Real-Time Analytics

©2019 BARC – Business Application Research Center                                BI Trend Monitor 2020   5
BI Trend Monitor 2020                                                                                                 Foreword

       ompanies are in the midst of many            due to a lack of data quality or analytical   important in addressing these challeng-
       profound changes: The amount                 skills. In addition, there has been an in-    es by a broad group of BI and analytics
       of data available and the speed of           creased focus on data protection since        professionals. Their responses provide a
producing new data has been increasing              the GDPR came into effect in 2018. Amid       comprehensive picture of regional, com-
rapidly for years, and business models as           a huge flood of information, companies        pany and industry specific differences
well as process improvements increasing-            will have to find ways to handle data in      and offer up-to-the-minute insights into
ly rely on data and analytics. Against this         a way that not only complies with legal       developments in the BI market. Our long-
backdrop, a key challenge is emerging:              requirements, but also helps to improve       term comparisons also show how trends
the efficient and, at the same time, inno-          processes and make day-to-day business        have developed, making it possible to
vative use of data is only possible when            easier.                                       separate hype from stable trends.

capabilities for - and the operationaliza-               his year we asked 2,865 users, con-
tion of - both analytics and data manage-                sultants and vendors for their views     Dr. Carsten Bange
ment are ensured. Many companies are                     on the most important BI trends. The
already reaching their limits with a ‘the                                                         Würzburg, Germany, November 2019
                                                    BARC BI Trend Monitor 2020 illustrates
more data the better‘ approach and can-             which trends are currently regarded as
not fully leverage the benefits they expect

©2019 BARC – Business Application Research Center                                                                     BI Trend Monitor 2020   7
Management Summary
     BI Trend Monitor 2020

   The market for BI and data management is                  For this study we took a unique approach to                  dustry specific differences and providing com-
   constantly changing. As an industry analyst,              identifying trends: we asked over 2,800 users,               prehensive insights on the BI market. We have
   we frequently highlight and predict important             consultants and vendors for their views on the               condensed the main findings of this study into
   topics that have an impact on the agendas of              most important BI trends, delivering an up-to-               six hot spots in order to contextualize the most
   organizations and the people within them.                 date perspective on regional, company and in-                striking differences and continuous trends.

  Result           Top trending topics                        Result              Best-in-class                           Result          Vendors vs. users
  area 1                                                      area 2              companies
                                                                                   Best-in-Class compa-                   area 3
                    Trending topics                                                nies
   Data quality and master data management                    Best-in-class companies* attach greater im-                 In general, vendors, consultants and users
   has been ranked as the most important trend                portance to all BI trends than organizations                have quite a similar view of the importance of
   three years in a row now. The stability of this            that see themselves as laggards*. However,                  BI trends. However, perceptions differ when it
   trend shows the relevance of having good                   their perception of some trends is fairly sim-              comes to real-time analytics and data prepa-
  Data discovery/visualization, data quality/
   quality data to be significantly higher than oth-          ilar (e.g., data warehouse modernization and                ration for business users, which are seen as
   er trenddata
             topicsmanagement       and self-service
                    with a much broader      presence         self-service BI).                                           considerably more important by users and
   in thecurrently   the reflects
          media. It also   topics the
                                    BI fact
                                            that many         Conversely, best-in-class companies and lag-                vendors than by consultants. However, users
  identify   as theplace
                       most high emphasistrends
                               important      on their
                                                    in        gards do not agree on the importance of es-                 and vendors do not agree when it comes to
   master data and data quality management                    tablishing a data-driven culture. Laggards                  the relevance of the cloud for data and analyt-
  their work. At the other end of the spec-
   because they have not reached their goals                  place much less emphasis on this trend. It                  ics. Like last year, this is a trend that vendors
  trum,   data
   yet. This    labs/science,
             trend               cloud
                    is a long-term       BI and
                                     mission  thatdata
                                                   will                                                                   attach great importance to whereas users
                                                              could be argued that laggards might not be
  as   a product
   remain          have been
            very important       voted
                               and       as thetoleast
                                   also refers     the        aware of the benefits or might not have access              seem less enthusiastic. The opposite effect
   equally  stable significance  of data governance,
  important of the nineteen trends covered                    to adequate resources in order to begin the                 can be observed in relation to data warehouse
   which is ranked in fourth position again this              data-driven transformation of their company.                modernization, which is a trend that users are
  in this report.
   year.                                                      However, best-in-class companies’ emphasis                  more likely to rate as important. This is also
   While data discovery and data visualization                on a data-driven culture is especially high.                true of establishing a data-driven culture. As a
   remain as the second most important trend,                 Compared to the average of 6.7/10, best-in-                 very organizational topic, it is understandable
   self-service BI - which was ranked third last              class companies rated this trend at 7.8/10.                 that this should be closer to the hearts of us-
   year – has dropped to fifth place. Establishing a                                                                      ers than software providers.
   data-driven culture has overtaken self-service
   BI, making it the third most important trend.
                                                          * Best-in-class companies comprise the top 10 percent in
   All top trends represent the key message that          terms of achievement of specific BI-related business ben-
   managing and leveraging data in organizations          efits (e.g. “Faster reporting, analysis or planning” and “In-
   needs to combine organizational and techno-            creased competitive advantage”) in this survey. Laggards
                                                          represent the lowest 10 percent.
   logical elements.

©2019 BARC – Business Application Research Center                                                                                              BI Trend Monitor 2020          9
                                                                                                                 BI Trend Monitor 2020

      Result         Industry comparison           Result          Global differences                   Result         Europe
      area 4                                       area 5                                               area 6

     There are some trends that are consid-       Observing BI trends from a geographical              The importance of BI trends is perceived
     ered important consistently across all in-   perspective shows a greater tendency in              quite differently across European coun-
     dustries. This especially applies to data    South America to assess trends as im-                tries. Eastern Europe in particular places
     governance and establishing a data-driv-     portant. In comparison, most trends are              greater importance on most BI trends
     en culture. Nevertheless, the manufactur-    generally rated as less important in Eu-             than the other European regions. Con-
     ing sector rates most BI trends as rather    rope. North America and Asia Pacific have            versely, the German-speaking region (Ger-
     less important than other industries while   a rather mixed view on BI trends. This is            many, Austria and Switzerland; collective-
     the telecommunications industry attaches     especially interesting regarding Asia Pacif-         ly known as DACH) and France put much
     greater importance to most trends.           ic, which in recent years attached greater           less importance on most trends. The only
     Most industries present a mixed view.        importance to all trends and seems now               exceptions in the DACH region are big
     For example, the public sector attaches      to have become more conservative in its              data analytics and self-service BI: both
     great importance to data governance but      view. Following the massive development              trends are rated as relatively important
     deems cloud for data and analytics to be     in this region over the last couple of years,        compared to the rating of other European
     almost irrelevant.                           some trends that were put into practice              regions. The trend that is valued the most
                                                  might already have failed to generate                in the DACH region is master data/data
     These industry-specific differences indi-
                                                  practical value, hence becoming less in-             quality management.
     cate which trends are prioritized, either
                                                  teresting. Alternatively, some trends have           Overall, the European perception reflects
     because they facilitate day-to-day busi-
                                                  worked so well that they are now prior-              the overall assessment of the top trends
     ness in these sectors or because they add
                                                  itized.                                              with master data/data quality manage-
     value over and beyond that. This might
     also explain the finding that the two rel-   Other than for Asia Pacific, the rather con-         ment, data discovery/visualization, data
     atively new topics – process mining and      servative view is typical for Europe and             governance and establishing a data-driven
     data catalogs – are considered unimpor-      can be further examined by looking more              culture as the most important BI trends.
     tant by all industries.                      closely at the regions within Europe (see
                                                  Hot Spot 6).

10     BI Trend Monitor 2020                                                                      ©2019 BARC – Business Application Research Center
Survey Results
BI Trends Overview
Data quality/master data management, data discovery/visualiza-
                                                                                                                        BI Trends Overview
tion and data-driven culture are the top trends.

Importance of BI trends from “not important at all“ (0) to
“very important“ (10)
                                                                                    7.3 Master data/DQ mgmt
                                                                              6.9             Data discovery
                                                                                                                       We asked users, consultants and software
                                                                              6.9         Data-driven culture          vendors of BI and data management tech-
                                                                                                                       nology to give their personal rating of the
                                                                             6.8            Data governance            importance of twenty trending topics that
                                                                        6.5                     Self-service BI        we presented to them. While the two most
                                                                                                                       important trends remained the same as
                                                                       6.3     Data prep. by business users            last year with master data and data quality
                                                                                                                       management in first position and data dis-
                                                                 5.9         Data Warehouse modernization
                                                                                                                       covery in second, third spot is now occu-
                                                            5.8                         Agile BI development           pied by establishing a data-driven culture.
                                                                                                                       This trend, which was newly introduced
                                                           5.6                             Real-time analytics         last year and went straight into fifth place
                                                          5.5           Adv. analytics/Machine learning/AI             in the rankings, is seen as even more im-
                                                                                                                       portant this year. Self-service BI, on the
                                                          5.5                               Big data analytics         other hand, went down to fifth place this
                                                                                                                       year whereas data governance remains in
                                                    5.2                Integrated platforms for BI and PM              fourth.
                                                    5.1                                         Embedded BI            All in all, these five top trends represent
                                                                                                                       the foundation for organizations to man-
                                                5.1                                          Data storytelling         age their own data and make use of it.
                                                5.1                                                 Mobile BI          Furthermore, it demonstrates that organi-
                                                                                                                       zations are aware of the relevance of high
                                               5.0                                  Analytics Teams/Data labs          quality data and its effective use. These
                                                                                                                       trends stand for underlying structures
                                               4.9                                   Using external/open data
                                                                                                                       being changed: Organizations want to go
                                              4.9                             Cloud BI for data and analytics          beyond the collection of as much data as
                                                                                                                       possible and actively use data to improve
                                        4.2                                                     Data catalogs          their business decisions. This is also sup-
                                       4.1                                                    Process mining           ported by data warehouse modernization,
                                                                                                                       which is once again in seventh place this
 0   Not important at all                                                                        Very important   10

n = 2865

©2019 BARC – Business Application Research Center                                                                                        BI Trend Monitor 2020        13
BI Trends Development
The biggest surge in interest is seen with data-driven culture.                                BI Trends Development

Development of rankings of BI trends
  2016       2017       2018         2019       2020
    1.         1.          1.         1.            1.    Master Data/DQ management
    2.         2.         2.          2.            2.    Data discovery                         Some trends have slightly increased in
                                                                                                 importance since last year (e.g., real-time
    3.         3.         3.          3.            3.    Data-driven culture                    analytics and integrated platforms for BI
    4.         4.          4.         4.            4.    Data governance                        and PM). However, they all climbed just
    5.         5.         5.          5.            5.    Self-service BI                        one rank with the exception of establish-
                                                                                                 ing a data-driven culture, which jumped
    6.         6.         6.          6.            6.    Data prep. by business users           two places. Therefore, no huge shift can
    7.         7.          7.         7.            7.    Data Warehouse modernization           be observed in terms of upward trends.
    8.         8.          8.         8.            8.    Agile BI development                   The opposite is the case for downward
                                                                                                 trends: Mobile BI fell from twelfth to fif-
    9.         9.          9.         9.            9.    Real-time analytics                    teenth place this year, continuing its
   10.         10.        10.        10.            10.   Adv. analytics/Machine learning/AI     downward trend that started in 2017. It
   11.         11.        11.         11.           11.   Big data analytics                     seems as if the mobile application of BI
                                                                                                 functions is not seen as important any-
   12.         12.        12.        12.            12.   Integrated platforms for BI and PM     more, either because it is available now
   13.         13.        13.        13.            13.   Embedded BI                            or because requirements have shifted.
   14.         14.        14.        14.            14.   Data storytelling                      Advanced analytics/machine learning/AI
                                                                                                 is ranked one place lower than last year
   15.         15.        15.        15.            15.   Mobile BI                              (down from 9 to 10). More important than
   16.         16.        16.        16.            16.   Analytics teams/Data labs              the difference of one rank however is the
   17.         17.        17.         17.           17.   Using external/open data               tendency behind this slight downward
                                                                                                 trend: In 2018, many hopes were based
   18.         18.        18.        18.            18.   Cloud BI for data and analytics
                                                                                                 on new tools using machine learning and
   19.         19.        19.        19.            19.   Data catalogs                          artificial intelligence so this topic might
   20.         20.        20.        20.            20.   Processing mining                      have been expected to rise. However,
                                                                                                 even if we refer to it as a stagnation in
               21.                                                                               perceived importance rather than a “real”
                                                               Trend not included in             downward trend, this result is surprising.
                                                               BI Trend Monitor 2020

n = 2794/2772/2770/2679/2865

©2019 BARC – Business Application Research Center                                                                  BI Trend Monitor 2020       15
Master Data/Data Quality
Master Data Management is a major trend in the transport and                                                        Master Data/Data
manufacturing sectors, but less important in Southern Europe.                                                    Quality Management

                                                                                               Rank of trend
                                                                                               in this region/
                                                                    Average                     industry etc.
                          Business user                                                               1
       Company/                   IT user                                   7.2                       1
       User type             Consultant                                7.0                            1           The importance of data quality and mas-
                                 Vendor                                6.8                            1           ter data management can be explained
                   More than 2500 empl.                                      7.5                      1           very simply: people can only make the
       Company         100 - 2500 empl.                                     7.3                       1
                                                                                                                  right decisions based on correct data. De-
       size                                                                                                       cision-making processes and operational
                    Less than 100 empl.                               6.7                             3           actions depend on reliable data. Through
                              Transport                                          7.7                  1           their aggregation mechanisms, BI reports
                         Manufacturing                                           7.7                  1           and analyses can help to reveal data
                                                                                 7.7                              quality issues.
                       Retail/Wholesale                                                               1
                                                                              7.6                                 The goal of master data management is
                                   Telco                                                              1
                                                                                                                  to bring together and exchange master
       Industry                  Utilities                                   7.3                      1           data such as customer, supplier or prod-
                     Public sector/Educ.                                7.0                           3           uct master data across multiple systems.
                                Services                                7.0                           1           Aside from a “master” ERP system, many
                                                                       6.9                                        companies also work with other CRM or
                       Financial Services                                                             4
                                                                                                                  SCM systems, use web services, or need
                                       IT                              6.8                            3           to merge systems following corporate
       Best-in-            Best-in-Class                                      7.5                     4           mergers, or to co-operate as partners ef-
       class                   Laggards                                6.9                            1           fectively.
                         Asia and Pacific                                    7.3                       3           There are proven concepts for increasing
                                                                            7.3                                   data quality and implementing master
       Global                    Europe                                                               1
                                                                                                                  data management. One example is the
       regions           North America                                  7.1                           4           Data Quality Cycle, which many software
                         South America                                 6.9                            5           vendors have implemented in their tools.
                       Northern Europe                                       7.5                      1           In today’s digital age, in which data is in-
                               BeNeLux                                       7.5                      1           creasingly emerging as a factor of pro-
                                                                                                                  duction, there is a growing need to use
                                  France                                                              2           and produce high quality data to make
       European                   DACH                                       7.4                      1
       regions                                                                                                    new services and products possible. The
                            UK & Ireland                                    7.3                       3           critical success factors for sustainable
                         Eastern Europe                                    7.1                        4           high data quality are defined roles and
                                                                                                                  responsibilities, quality assurance pro-
                       Southern Europe                                                                6           cesses and the continuous monitoring of
                                                                                                                  the quality of a company’s data.
                                        0                                                       10
     n = 2616                                Not important at all                  Very important

©2019 BARC – Business Application Research Center                                                                                   BI Trend Monitor 2020        17
Data Discovery/Visualization
Best-in-class companies value data discovery much more than                                                                 Data Discovery/
laggards do.                                                                                                                  Visualization

                                                                                                   Rank of trend
                                                                                                   in this region/
                                                                    Average                         industry etc.
                                  IT user                                  7.0                            3
       Company/              Consultant                                    6.9                            2
       User type          Business user                                    6.9                            2          Data discovery is the business user driven
                                 Vendor                              6.4                                  4          process of discovering patterns and outli-
                   More than 2500 empl.                                     7.0                           4          ers in data. At least three functional areas
       Company         100 - 2500 empl.                                    6.9                            2          are required to efficiently and effectively
       size                                                                                                          identify patterns and outliers in an iter-
                    Less than 100 empl.                                    6.9                            1
                                   Telco                                         7.5                      2          ative approach. Business users must be
                                                                                 7.4                                 well equipped with data preparation fea-
                                       IT                                                                 1
                                                                            7.1                                      tures to connect to a wide range of sourc-
                     Public sector/Educ.                                                                  2
                                                                                                                     es, clean, enrich and shape data to pub-
                       Retail/Wholesale                                     7.1                           3
                                                                                                                     lish data sets for analytics. These data sets
       Industry                 Services                                   7.0                            3          are explored by visual analysis or sifted by
                       Financial Services                                  7.0                            2          guided advanced analytics to reliably iden-
                                 Utilities                                 6.9                            2          tify relevant patterns.
                         Manufacturing                                 6.6                                2          Data discovery is currently evolving along
                              Transport                               6.6                                 5          two axes to increase efficiency and quali-
                           Best-in-Class                                               8.0                1          ty. Improving user guidance and automa-
       class                   Laggards                              6.3                                  4          tion is at the top of the agenda for most
                         South America                                             7.8                    1          vendors. Machine learning is increasingly
                         North America                                           7.4                      2          leveraged to guide business analysts and
       regions           Asia and Pacific                                    7.1                           4          automate tasks through all steps from
                                 Europe                                6.7                                2
                                                                                                                     preparation to visualization. New concepts
                                                                                       7.9                           for organization and search such as data
                         Eastern Europe                                                                   1
                                                                                                                     catalogs and NLQ aim to offer addition-
                                  France                                                                  1
                                                                                                                     al support for power users. Additionally,
                       Northern Europe                                      7.1                           2
                                                                                                                     data discovery functions are increasingly
       European             UK & Ireland                                    7.1                           4
       regions                                                                                                       being built into analytics and BI platforms
                       Southern Europe                                     7.0                            3          so findings can be connected and harmo-
                               BeNeLux                                     6.8                            4          nized throughout the enterprise.
                                  DACH                              6.3                                   3

     n = 2629                           0                                                           10
                                             Not important at all                      Very important

©2019 BARC – Business Application Research Center                                                                                       BI Trend Monitor 2020        19
Data-Driven Culture
Data-driven culture is most relevant within best-in-class compa-
                                                                                                                      Data-Driven Culture
nies and in the UK & Ireland, and least relevant in the DACH region.

                                                                                                    Rank of trend
                                                                                                    in this region/
                                                                    Average                          industry etc.
                             Consultant                                                                    3
       Company/                   IT user                                   6.9                            4
       User type          Business user                                    6.8                             3          One of the biggest shifts in today’s busi-
                                 Vendor                              6.2                                   6          ness world is the transformation from
                   More than 2500 empl.                                         7.1                        3          isolated and project-oriented data usage
       Company      Less than 100 empl.                                    6.8                             2          to a completely data-driven enterprise.
                       100 - 2500 empl.                                    6.7                             4          ‘Data-driven’ in this context means that all
                                                                                 7.3                                  decisions and processes within a business
                       Retail/Wholesale                                                                    2
                                                                                                                      are based on data. This concerns simple
                                   Telco                                                                   3
                                                                                                                      key figures like revenue or profit, but also
                       Financial Services                                       7.1                        1          results from advanced analytics models.
                                Services                                    7.0                            2          Moreover, both quantitative and qualita-
       Industry                        IT                                   7.0                            2          tive data can be used to support the de-
                     Public sector/Educ.                                    6.9                            4          cision-making process. While companies
                              Transport                                   6.6                              4          have always been interested in their num-
                                                                          6.6                                         bers, the extent of data use is exercised
                                 Utilities                                                                 5
                                                                                                                      at a higher level within a data-driven cul-
                         Manufacturing                                    6.5                              5          ture. The main aim is to replace managers’
       Best-in-            Best-in-Class                                               7.8                 2          gut feelings with data-derived facts and
       class                   Laggards                              6.2                                   6          to empower all employees to actively use
                         North America                                                7.7                  1          data to enhance their daily work. The goal
                         South America                                                7.7                  2          is to fully utilize a company’s potential by
       regions                                                                    7.4                                 making decisions more successful, initia-
                         Asia and Pacific                                                                   1
                                                                                                                      tives more effective and competitive ad-
                                 Europe                               6.4                                  4          vantages more striking.
                            UK & Ireland                                               7.8                 1
                                                                                                                      However, a data-driven culture should not
                         Eastern Europe                                           7.5                      3          be interpreted as blindly following num-
                       Southern Europe                                           7.3                       1          bers. Key focus areas should be to en-
       European                BeNeLux                                          7.0                        2          hance data interpretation skills and critical
                       Northern Europe                                      7.0                            3          thinking. This enables businesses not only
                                  France                             6.2                                   7          to base their decisions on reliable data,
                                                                    5.9                                               but also to know when it is better not to
                                  DACH                                                                     5
                                                                                                                      do so.
                                        0                                                            10
      n = 2619
                                             Not important at all                       Very important

©2019 BARC – Business Application Research Center                                                                                        BI Trend Monitor 2020        21
Data Governance
Very important in UK & Ireland. Less important in the DACH re-
                                                                                                                            Data Governance
gion and within small companies.

                                                                                                     Rank of trend
                                                                                                     in this region/
                                                                    Average                           industry etc.
                                  IT user                                                                   2
       Company/           Business user                                     6.6                             4
       User type                 Vendor                                 6.6                                 3
                             Consultant                                 6.5                                 4
                                                                                                                       Unlike BI governance, which centers on
                                                                                  7.2                                  preparing and presenting data for busi-
                   More than 2500 empl.                                                                     2
       Company                                                                                                         ness management systems, data govern-
                       100 - 2500 empl.                                     6.8                             3
       size                                                                                                            ance focuses on the data in all systems
                    Less than 100 empl.                                6.3                                  6          that are dealing with data. Because busi-
                     Public sector/Educ.                                          7.3                       1          ness and technical responsibilities are
                              Transport                                           7.3                       2          traditionally covered on a per system lev-
                                   Telco                                      7.1                           4          el, this overarching view of data needs to
                                                                             7.0                                       be specifically addressed, preferably by
                       Financial Services                                                                   3
                                                                                                                       a central body within the organization.
       Industry                 Services                                     6.9                            4          This ensures broader thinking in terms of
                                       IT                                   6.7                             4          knowledge, organization and technology.
                       Retail/Wholesale                                     6.7                             4          Data governance is needed as the steer-
                                 Utilities                                  6.7                             4          ing mechanism for data strategy. A proper
                         Manufacturing                                  6.6                                 3          data strategy orchestrates how business
       Best-in-            Best-in-Class                                            7.6                     3          strategy is translated into data and ana-
       class                   Laggards                                     6.7                             2          lytics. Data strategy manages the exploita-
                                                                                   7.4                                 tion of data across all business processes
                         Asia and Pacific                                                                    2
                                                                                                                       to promote business efficiency and inno-
       Global            North America                                            7.3                       3          vation. Data governance is required to im-
       regions           South America                                      6.7                             9          plement a data strategy, including policies
                                 Europe                                 6.6                                 3          and frameworks to manage, monitor and
                            UK & Ireland                                            7.7                     2          protect data capital while taking people,
                       Southern Europe                                            7.2                       2          processes and technologies into account.
                                  France                                      7.0                           3
                                                                                                                       Establishing data governance is a long-
       European                                                              7.0
                                                                                                                       term endeavor. Most of all, it requires a
                       Northern Europe                                                                      4
       regions                                                                                                         clear, conscious management decision on
                               BeNeLux                                       6.8                            3          how to work with and use data.
                         Eastern Europe                                     6.7                             6
                                  DACH                                6.1                                   4

                                        0                                                             10
      n = 2628                               Not important at all                        Very important

©2019 BARC – Business Application Research Center                                                                                        BI Trend Monitor 2020       23
Self-Service BI
Self-service BI is especially popular in Eastern Europe, but less
                                                                                                                                      Self-Service BI
popular in Northern Europe and BeNeLux.

                                                                                                         Rank of trend
                                                                                                         in this region/
                                                                     Average                              industry etc.
                                  IT user                                   6.6                                 5
       Company/              Consultant                                     6.5                                 5
       User type          Business user                                    6.4                                  6
                                                                           6.3                                             Self-service BI has been on the wish lists of
                                 Vendor                                                                         5
                                                                                                                           many organizations for years and remains
                   More than 2500 empl.                                          6.9                            5          a high priority according to our survey
       Company         100 - 2500 empl.                                    6.3                                  5
       size                                                                                                                findings. This continuously high demand
                    Less than 100 empl.                                    6.3                                  5          underlines the importance of equipping
                       Financial Services                                        6.9                            5          modern analytical landscapes according-
                                 Utilities                                      6.8                             3          ly. But a shift has taken place. Companies
                                                                                6.7                                        today no longer solely focus on providing
                              Transport                                                                         3
                                                                                                                           self-service capabilities to users to serve
                                   Telco                                                                        5
                                                                                                                           their departmental requirements, they
       Industry        Retail/Wholesale                                      6.6                                5          want to democratize data access while
                     Public sector/Educ.                                    6.6                                 6          ensuring consistent and high-quality data
                                       IT                                   6.6                                 5          and results.
                         Manufacturing                                      6.5                                 4          Self-service BI promises quicker and more
                                Services                                   6.3                                  6          efficiently prepared dashboards and re-
       Best-in-            Best-in-Class                                          7.1                           6          ports by empowering the business users
       class                                                                6.5                                            involved to gain insights from data and
                               Laggards                                                                         3
                                                                                                                           make better informed decisions. The
                         South America                                                                          3
                                                                                                                           number of implementations that allow
       Global            Asia and Pacific                                         6.9                            5          business users to build their own con-
       regions           North America                                      6.6                                 7          tent is increasing. Not all business users
                                 Europe                                    6.4                                  5          actively take part in creating analytics and
                         Eastern Europe                                                 7.6                     2          BI content. Companies understand that
                       Southern Europe                                          6.7                             4          self-service BI complements serviced or
                                                                            6.4                                            ‘silver-service’ BI, which is used for criti-
                                  DACH                                                                          2
       European                                                                                                            cal enterprise-wide content, but does not
                                  France                                  6.2                                   6
       regions                                                                                                             make it redundant. It is important to find
                            UK & Ireland                                  6.1                                   7          the appropriate balance between service
                               BeNeLux                                5.9                                       5          and self-service for all users and use cas-
                       Northern Europe                              5.5                                         8          es.

                                        0                                                                 10
     n=2624                                  Not important at all                            Very important

©2019 BARC – Business Application Research Center                                                                                             BI Trend Monitor 2020        25
Data Preparation by
Business Users
South American companies place the most value on data prepa-                                                              Data Preparation by
ration, DACH and the BeNeLux countries much less so.                                                                           Business Users

                                                                                                        Rank of trend
                                                                                                        in this region/
                                                                    Average                              industry etc.
                                 Vendor                                                                        2
       Company/           Business user                                     6.5                                5
       User type                  IT user                                  6.3                                 6
                                                                                                                          Data preparation describes the process of
                             Consultant                              5.8                                       7          cleaning, structuring and enriching data
                    Less than 100 empl.                                     6.6                                4          by business users for use in analytics. The
       Company         100 - 2500 empl.                                    6.3                                 6          goal of data preparation is to build valua-
                   More than 2500 empl.                                   6.2                                  7          ble assets from raw data to help answer
                     Public sector/Educ.                                        6.7                            5          concrete business questions though ana-
                                                                            6.5                                           lytics.
                                Services                                                                       5
                                                                           6.4                                            Achieving efficient and agile data prepa-
                              Transport                                                                        6
                                                                                                                          ration is of utmost importance in today’s
                                 Utilities                                                                     6
                                                                                                                          volatile economy. It is key to increase the
       Industry        Financial Services                                 6.2                                  7          ability to leverage enterprise and external
                       Retail/Wholesale                                   6.2                                  7          data to inform decisions and to monetize
                         Manufacturing                                    6.1                                  6          data to reduce costs or increase revenues.
                                   Telco                              6.1                                      9          The enduring importance of data prepa-
                                       IT                             6.0                                      7          ration shows that this task is increasingly
                                                                                      7.2                                 shifting from IT to business users.
       Best-in-            Best-in-Class                                                                       5
       class                                                               6.3                                            To ensure high efficiency and quality with-
                               Laggards                                                                        5
                                                                                                                          out sacrificing agility, it is vital to estab-
                         South America                                                                         4
                                                                                                                          lish collaboration between development
                         North America                                            7.0                          5
       Global                                                                                                             resources in IT and the business users
       regions           Asia and Pacific                                    6.6                                6          involved. Easy-to-use and intuitive tools
                                 Europe                               6.0                                      6          with sophisticated user guidance and au-
                         Eastern Europe                                          6.9                           5          tomation powered by machine learning
                                  France                                         6.9                           4          are vital to infuse efficiency and quality
                                                                                6.6                                       into data preparation efforts. Governing
                       Southern Europe                                                                         5
       European                                                                                                           distributed data preparation assets can-
                       Northern Europe                                     6.4                                 5
       regions                                                                                                            not by overvalued. Data catalogs serve as
                            UK & Ireland                                   6.3                                 5          inventories and ensure access to and re-
                               BeNeLux                              5.6                                        7          use of data. Beyond technology, collabo-
                                  DACH                              5.6                                        7          ration must be promoted to benefit from
                                                                                                                          democratized access to data.
                                        0                                                                10
      n = 2634                               Not important at all                           Very important

©2019 BARC – Business Application Research Center                                                                                            BI Trend Monitor 2020         27
Data Warehouse Modernization
Data warehouse modernization is prominent in South America,                                                                  Data Warehouse
but less important for vendors and small companies.                                                                           Modernization

                                                                                                     Rank of trend
                                                                                                     in this region/
                                                                    Average                           industry etc.
                                  IT user                                    6.1                            7
       Company/           Business user                                    5.8                              7
       User type             Consultant                                    5.8                              8
                                                                     5.2                                               Older data warehouse landscapes have
                                 Vendor                                                                    15
                                                                                                                       become too complex to support agile de-
                   More than 2500 empl.                                          6.3                        6          velopment, or too expensive to have their
       Company         100 - 2500 empl.                                    5.9                              7
       size                                                                                                            functionality extended to accommodate
                    Less than 100 empl.                              5.3                                   13          modern analytics requirements. Further-
                       Retail/Wholesale                                          6.3                        6          more, the type of implementation for
                       Financial Services                                        6.2                        6          which many data warehouse landscapes
                                                                             6.1                                       were originally designed and optimized
                              Transport                                                                     7
                                                                                                                       does not cover the way analytics is cur-
                     Public sector/Educ.                                    6.0                             7          rently moving forward in the direction of
       Industry          Manufacturing                                      6.0                             7          exploration and operational processing
                                 Utilities                                  6.0                             7          alongside classical BI requirements.
                                   Telco                                    6.0                            10          Now, organizations are beginning to un-
                                       IT                                  5.8                              8          derstand the new challenges and the
                                Services                               5.6                                  8          potential of alternative methodologies,
                           Best-in-Class                                          6.5                       8          architectural approaches and utilizing
       class                                                                 6.1                                       other technical options such as in-mem-
                               Laggards                                                                     7
                                                                                                                       ory, cloud storage and data warehouse
                         South America                                             6.7                      8          automation tools. IT must be prepared for
       Global            North America                                       6.1                            8          fast-changing analytical requirements, and
       regions           Asia and Pacific                                    5.9                            13          they must also compete against new and
                                 Europe                                    5.8                              7          cheaper implementation options from ex-
                         Eastern Europe                                          6.3                        8          ternal service providers. Collaborative ap-
                                                                                 6.2                                   proaches are needed to cover the increas-
                       Southern Europe                                                                      7
                                                                                                                       ing expectations of the business to pull
                            UK & Ireland                                                                    8
       European                                                                                                        maximum business value from data. It is
                                  France                                   5.8                              8
       regions                                                                                                         now time to assess historically grown data
                                  DACH                                     5.7                              6          warehouses against present demands
                               BeNeLux                                 5.7                                  6          and evaluate how updated hardware and
                       Northern Europe                                 5.6                                  7          technology could make life easier.

      n = 2619                          0                                                             10
                                             Not important at all                        Very important

©2019 BARC – Business Application Research Center                                                                                        BI Trend Monitor 2020       29
Agile BI Development
South America leads the way. This trend is much less important
                                                                                                                          Agile BI Development
in BeNeLux countries and the DACH region.

                                                                                                        Rank of trend
                                                                                                        in this region/
                                                                    Average                              industry etc.
                             Consultant                                                                        6
       Company/                  Vendor                                   5.6                                 11
       User type          Business user                                   5.6                                 10
                                                                          5.6                                             The term “agile” has increasingly been adopt-
                                  IT user                                                                      9
                                                                                                                          ed in the context of business intelligence in
                   More than 2500 empl.                                         6.1                            8          recent years. Originally referring to a soft-
       Company      Less than 100 empl.                                   5.6                                  8          ware development methodology, the “agile”
       size                                                                                                               moniker is now often used as a requirement
                       100 - 2500 empl.                                   5.5                                  8
                                                                                 6.3                                      when developing new data models, reports,
                                   Telco                                                                       7
                                                                                                                          dashboards or visualizations within a us-
                                       IT                                   6.0                                6          er-centric system designed for data-driven
                       Financial Services                                   6.0                                8          insights. Arguably, most users requesting
                                Services                                   5.8                                 7          “agile BI” use this term to express their ex-
                                                                           5.7                                            pectation that older, historically grown BI
       Industry               Transport                                                                        9          systems and BI organizations quickly sup-
                       Retail/Wholesale                                   5.7                                 10          port changes to business processes in a bal-
                                 Utilities                                5.6                                 11          ancing act between “self-service” and stand-
                         Manufacturing                                    5.6                                  8          ardized projected development.
                     Public sector/Educ.                                  5.6                                  9          Agile BI requires organizations to adopt
                                                                                                                          an iterative development approach with
       Best-in-            Best-in-Class                                                                       7          close collaboration between business and
       class                   Laggards                                   5.6                                  8          IT. Many companies are not set up organi-
                         South America                                                6.8                      7          zationally for this approach, however, and
                         Asia and Pacific                                          6.5                          8
                                                                                                                          some changes to organizational structures
       Global                                                                                                             may be required. The BI and analytics sys-
       regions           North America                                     5.8                                10          tem architecture must be able to deliver
                                 Europe                                   5.6                                  8          metadata-based changed components and
                       Northern Europe                                           6.3                           6          services as lean increments through stand-
                                                                                6.2                                       ardized continuous delivery pipelines. Ideal-
                                  France                                                                       5
                                                                                                                          ly, the agile BI development approach is also
                            UK & Ireland                                        6.2                            6          supported by agile project management,
       European          Eastern Europe                                   5.6                                 12          which iteratively manages planning, require-
                       Southern Europe                                    5.6                                 12          ments collection and development, but also
                                                                      5.4                                                 automated testing. Just-in-time business
                                  DACH                                                                         8
                                                                                                                          information modeling combined with agile
                               BeNeLux                              4.9                                       11          technology for model-driven generation ac-
                                                                                                                          celerate “time to market”.
                                        0                                                                10
      n = 2621                               Not important at all                           Very important

©2019 BARC – Business Application Research Center                                                                                            BI Trend Monitor 2020        31
Real-Time Analytics
North America and Asia & Pacific value real-time analytics very
                                                                                                                            Real-Time Analytics
highly. Northern Europe and DACH see it as less relevant.

                                                                                                         Rank of trend
                                                                                                         in this region/
                                                                   Average                                industry etc.
                                Vendor                                      5.7                                 9
       Company/          Business user                                         5.7                              8
       User type                 IT user                                   5.7                                  8          Faster reporting and analysis of data,
                            Consultant                              4.9                                        14          not only in terms of query performance
                    Less than 100 empl.                                         6.0                             7          (which is still one of the biggest problems
       Company More than 2500 empl.                                        5.7                                 11          users experience with their BI tools), is a
       size                                                                                                                challenge in many companies. There is an
                       100 - 2500 empl.                                   5.4                                   9
                                                                                                                           increasing need to make data from trans-
                                Utilities                                       5.9                             8          actional systems available immediately to
                    Public sector/Educ.                                        5.9                              8          support faster and fact-based operational
                             Transport                                         5.8                              8          decision-making.
                                  Telco                                        5.8                             12          BI with real-time data refers to the near-im-
       Industry                       IT                                       5.7                              9          mediate processing and provision of in-
                                                                           5.6                                             formation about business operations in
                               Services                                                                         9
                                                                                                                           transactional systems (i.e., streaming). Re-
                        Manufacturing                                      5.5                                  9          al-time analytics is about catching events
                       Retail/Wholesale                                   5.5                                  11          or other new data immediately after their
                      Financial Services                                 5.2                                   12          occurrence and processing them for dis-
                          Best-in-Class                                          6.1                           12          play (e.g., in an operational dashboard) or
       class                                                             5.4                                               analysis. Constantly increasing amounts
                              Laggards                                                                          9
                                                                                                                           of data, high-performance computing
                         North America                                                 6.6                      6          time and pattern recognition of events
       Global           Asia and Pacific                                                6.6                      7          (complex event processing) are just some
       regions           South America                                           6.1                           13          of the challenges companies now face
                                Europe                               5.0                                       11          when focusing on BI with real-time data.
                        Eastern Europe                                          5.9                            10          Like visual BI and predictive analytics, BI
                                                                               5.8                                         with real-time data can complement an
                           UK & Ireland                                                                         9
                                                                                                                           organization’s existing BI strategy to gain
                      Southern Europe                                     5.4                                  13          new insights into data with additional,
       European               BeNeLux                                     5.4                                   8          valuable findings. An organization’s deci-
                                 France                                  5.3                                    9          sion-making culture, available skills and
                                 DACH                              4.7                                         15          the identification and promotion of appro-
                                                                   4.6                                                     priate use cases are key aspects to consid-
                      Northern Europe                                                                          15
                                                                                                                           er when exploring a real-time analytics
                                       0                                                                  10               project.
      n = 2635
                                            Not important at all                             Very important

©2019 BARC – Business Application Research Center                                                                                             BI Trend Monitor 2020        33
Advanced Analytics/
Machine Learning/AI
Advanced Analytics is very popular in Eastern Europe. Its                                                                  Advanced Analytics/
relevance is much lower in France and BeNeLux.                                                                             Machine Learning/AI

                                                                                                         Rank of trend
                                                                                                         in this region/
                                                                    Average                               industry etc.
                                 Vendor                                                                         7
       Company/           Business user                                    5.5                                 12
       User type                  IT user                                 5.4                                  10
                                                                                                                           Advanced analytics and machine learning are
                             Consultant                                   5.3                                   9          important trends among BI decision-makers
                   More than 2500 empl.                                         5.9                             9          for 2020. Advanced analytics goes beyond
       Company      Less than 100 empl.                                   5.4                                  11          mathematical calculations such as sums and
       size                                                                                                                averages. It uses mathematical and statistical
                       100 - 2500 empl.                                   5.3                                  10
                                                                                                                           formulas and algorithms in order to generate
                                   Telco                                         6.1                            8          new information, identify patterns and de-
                       Retail/Wholesale                                         5.8                             9          pendencies, and calculate forecasts.
                       Financial Services                                   5.7                                 9          The number of possible use cases in this
                                 Utilities                                  5.7                                10          area is immense, and ranges from conduct-
                                                                           5.6                                             ing forecasts on income, prices, sales, re-
       Industry                        IT                                                                      11
                                                                                                                           quirements or customer value to preventing
                     Public sector/Educ.                                   5.5                                 10          contract cancellations, forecasting machine
                                Services                                   5.5                                 10          downtime, monitoring and evaluating social
                         Manufacturing                                5.2                                      13          media, and predictive policing.
                              Transport                               5.1                                      15          The expansion of advanced analytics and ma-
                                                                                      6.4                                  chine learning also means changes for line of
       Best-in-            Best-in-Class                                                                        9
                                                                                                                           business and IT decision-makers and man-
       class                   Laggards                                   5.3                                  10          agers. They need to assess which use cases
                         South America                                                6.4                      11          to tackle with advanced analytics, the level of
                         Asia and Pacific                                         6.0                           12          priority advanced analytics should have in the
       regions                                                              5.7                                            company as a whole, which roles are required
                         North America                                                                         12          (and with which capabilities), and which tech-
                                 Europe                                   5.4                                   9          nology fits best taking account of the IT land-
                         Eastern Europe                                                6.6                      7          scape and intended users. With the increas-
                       Southern Europe                                           6.0                            9          ing use and maturity of advanced analytics,
                                                                                                                           many companies have now moved on from
                            UK & Ireland                                                                       11          experimentation into more practical, day-to-
       European                                                            5.4
                       Northern Europe                                                                          9          day use cases. The operationalization of use
                                  DACH                                    5.3                                   9          cases is one of the major challenges here.
                               BeNeLux                              4.8                                        13
                                                                                                                           Besides organizational challenges, consider-
                                                                                                                           ations of bias in algorithmic decision-making
                                  France                            4.7                                        13          and ethical standards for such solutions are
                                                                                                                           gaining in importance.
                                        0                                                                 10
      n = 2630                               Not important at all                            Very important

©2019 BARC – Business Application Research Center                                                                                              BI Trend Monitor 2020         35
Big Data Analytics
Very important in South America. Less important in France and
                                                                                                                                Big Data Analytics
for consultants.

                                                                                                           Rank of trend
                                                                                                           in this region/
                                                                    Average                                 industry etc.
                                 Vendor                                    5.4                                   14
       Company/           Business user                                      5.7                                 9
       User type                  IT user                                  5.4                                   11
                             Consultant                              4.8                                         15          While big data has become an omnipres-
                   More than 2500 empl.                                         5.8                              10          ent term in recent years, and the hype sur-
       Company                                                             5.4                                               rounding it seems to have already peaked,
                    Less than 100 empl.                                                                          12
       size                                                                                                                  the value it can generate is yet to be fully
                       100 - 2500 empl.                                   5.3                                    11
                                                                                                                             explored. Many organizations are still in
                                   Telco                                               6.5                       6           the process of finding ways to make big
                                 Utilities                                      5.8                              9           data usable and profitable. In this con-
                       Financial Services                                   5.6                                  10          text, big data analytics comes into play by
                                       IT                                   5.5                                  13          providing the means to analyze data sets
       Industry          Manufacturing                                     5.5                                   10          from various internal and external sourc-
                                                                           5.4                                               es including sensor/IoT, geolocation and
                     Public sector/Educ.                                                                         11
                                                                                                                             clickstream data. Almost every device or
                                Services                                   5.4                                   11          platform generating data can be used to
                       Retail/Wholesale                                    5.4                                   12          identify patterns and derive added value
                              Transport                                   5.3                                    12          through effectively combined informa-
       Best-in-            Best-in-Class                                              6.3                        10          tion. Big data analytics is used to support
       class                   Laggards                               5.1                                        11          decision-making and process optimiza-
                         South America                                                   6.8                     6
                                                                                                                             tion. Therefore, it is applied at both an op-
                                                                                                                             erational and strategic level. In that sense,
       Global            Asia and Pacific                                                                         14
                                                                                                                             effectiveness in data usage becomes in-
       regions           North America                                       5.7                                 11          creasingly important: The challenge is no
                                 Europe                                   5.3                                    10          longer how to get hold of data, but how
                       Southern Europe                                            6.2                            8           to effectively use the massive amounts of
                         Eastern Europe                                          5.9                             11          data produced every day in order to devel-
                                  DACH                                     5.3                                   10          op new products, reduce costs and make
       European                                                       5.1                                                    better decisions.
       regions         Northern Europe                                                                           11
                            UK & Ireland                              5.0                                        14
                               BeNeLux                               4.8                                         14
                                  France                            4.7                                          14

      n = 2628                          0                                                                   10
                                             Not important at all                              Very important

©2019 BARC – Business Application Research Center                                                                                               BI Trend Monitor 2020        37
Integrated Platforms for BI and
Performance Management (PM)
South America on top of the list for integrated platforms. France                                                       Integrated Platforms
and financial services companies are less sold on the trend.                                                                   for BI and PM

                                                                                                      Rank of trend
                                                                                                      in this region/
                                                                    Average                            industry etc.
                                 Vendor                                                                     10
       Company/           Business user                                     5.5                             11
       User type             Consultant                               5.1                                   10
                                                                     4.9                                                Decision-making in an increasingly com-
                                  IT user                                                                   15
                                                                                                                        plex and volatile world needs transpar-
                   More than 2500 empl.                                   5.3                               13          ent plans and data analyses. Therefore,
       Company      Less than 100 empl.                                   5.3                               14          the seamless integration of performance
                       100 - 2500 empl.                               5.1                                   12          management (particularly planning) and
                                       IT                                  5.5                              14          analytics functionality is beneficial to sup-
                                                                           5.4                                          port decision-making processes optimally.
                                   Telco                                                                    13
                                                                                                                        Best-in-class companies and users know
                                 Utilities                                5.4                               14          that there can be no transparent deci-
                         Manufacturing                                    5.3                               11          sion-making without supporting function-
       Industry      Public sector/Educ.                                  5.3                               13          ality for planning, reporting (e.g., results
                              Transport                                   5.2                               13          reports), analysis (e.g., analyses of planned
                                                                          5.2                                           and actual values) and dashboarding (e.g.,
                       Retail/Wholesale                                                                     14
                                                                                                                        monitoring). Having all these options in
                                Services                              5.1                                   16          one common and integrated platform is a
                       Financial Services                           4.7                                     16          decisive factor for sustained success when
       Best-in-            Best-in-Class                                           6.3                      11          integrating analytics and performance
       class                   Laggards                              4.9                                    12
                                                                                                                        management. Consequently, this integra-
                                                                                                                        tion has been one of the most stable and
                         South America                                                                      10          relevant trends in the market for years.
                         Asia and Pacific                                          6.1                       11
       Global                                                                                                           Integrated platforms for analytics and per-
       regions           North America                                     5.4                              15          formance management are equally rele-
                                 Europe                               5.0                                   12          vant for all user types, company sizes and
                       Southern Europe                                      5.6                             11          industries. Best-in-class companies in par-
                       Northern Europe                                     5.4                              10
                                                                                                                        ticular have invested heavily in integrating
                                                                                                                        analytics and performance management
                         Eastern Europe                                                                     15
                                                                                                                        processes as well as specialist software
       European                BeNeLux                                5.0                                   10
       regions                                                                                                          solutions and the benefits from this effort
                                  DACH                               4.9                                    11          have been empirically proven. Supporting
                            UK & Ireland                             4.9                                    16          analytics and performance management
                                  France                            4.6                                     16
                                                                                                                        on an integrated data platform with an in-
                                                                                                                        tegrated tool is a goal worth investing in.
                                        0                                                              10
      n = 2616                               Not important at all                         Very important

©2019 BARC – Business Application Research Center                                                                                          BI Trend Monitor 2020        39
Embedded BI
Best-in-class companies are much more aware of the value of embed-
                                                                                                                                    Embedded BI
ded BI than laggards. The UK & Ireland are the most reserved.

                                                                                                      Rank of trend
                                                                                                      in this region/
                                                                    Average                            industry etc.
                                 Vendor                                                                      8
       Company/           Business user                                      5.2                            14
       User type                  IT user                                5.0                                14
                                                                                                                        Embedding intelligence in operational ap-
                             Consultant                                                                     12
                                                                                                                        plications is growing steadily in popularity.
                    Less than 100 empl.                                       5.5                            9          From dashboards to prediction and opti-
       Company         100 - 2500 empl.                                  5.1                                13          mization models, users can access com-
                   More than 2500 empl.                                 5.0                                 16          plementary functions directly in their spe-
                                       IT                                      5.6                          10
                                                                                                                        cific operational processes and act on the
                                                                                                                        findings – closing the classic management
                                 Utilities                                                                  12          loop from information to action at an op-
                                Services                                    5.1                             13          erational level. Embedded BI and analytics
                       Retail/Wholesale                                  5.1                                15          enables users to derive information rap-
       Industry          Manufacturing                                   5.1                                14          idly by themselves without having to in-
                                                                        4.9                                             volve the IT department or supervisors. In
                       Financial Services                                                                   13
                                                                                                                        effect, many more people gain access to
                     Public sector/Educ.                                4.9                                 16          information and BI capabilities, making BI
                              Transport                                4.8                                  16          more pervasive or “democratic”. Besides,
                                   Telco                               4.7                                  17          it even allows for automated processes
                           Best-in-Class                                            6.0                     13          where no active user request is needed to
       class                                                           4.8                                              initiate data analysis. However, this oper-
                               Laggards                                                                     14
                                                                                                                        ationalization of BI and analytics implies
                         North America                                         5.6                          13          various challenges. For example, sepa-
       Global            Asia and Pacific                                       5.6                          16          rating the responsibilities of the BI and
       regions           South America                                        5.4                           20          application teams, delimiting operation-
                                 Europe                                4.9                                  14          al BI from classic BI and data warehous-
                                                                         5.1                                            es, or deciding whether to “make or buy”
                       Southern Europe                                                                      16
                                                                                                                        embedded functions. Also, the broad ap-
                         Eastern Europe                                  5.1                                17          proach of automating decisions through
                       Northern Europe                                  5.0                                 12          embedded models and rules brings about
       European                   DACH                                  4.9                                 12          completely new possibilities and challeng-
       regions                                                                                                          es. For example, the change in role of the
                                  France                               4.7                                  12
                                                                       4.7                                              human being from decision-maker to cre-
                               BeNeLux                                                                      16
                                                                                                                        ator and supervisor of decision-making
                            UK & Ireland                              4.6                                   17          models.
                                        0                                                              10
      n = 2616                               Not important at all                         Very important

©2019 BARC – Business Application Research Center                                                                                          BI Trend Monitor 2020        41
Data Storytelling
A big gap exists between best-in-class companies and laggards
                                                                                                                                 Data Storytelling
as well as between Asia & Pacific and Europe.

                                                                                                         Rank of trend
                                                                                                         in this region/
                                                                   Average                                industry etc.
                                Vendor                                         5.4                             13
       Company/           Business user                                        5.3                             13
       User type             Consultant                                  4.8                                   16
                                 IT user                             4.7                                       17          Data relies on you to give it a voice, and
                                                                           5.2                                             data storytelling is a way of helping to ex-
                    Less than 100 empl.                                                                        15
       Company More than 2500 empl.                                        5.1
                                                                                                                           plain the meaning of analysis results and
       size                                                                                                                insights gained. Data stories supplement
                       100 - 2500 empl.                                   5.0                                  14          and build on components of visual analy-
                                  Telco                                              5.9                       11          ses, standardized reports and dashboards
                                      IT                                       5.4                             15          such as graphs and tables. They are mod-
                              Transport                                        5.3                             10          ified, annotated and compiled into a nar-
                     Public sector/Educ.                                   5.2                                 14          rative to form the supporting evidence for
                                                                           5.2                                             a well-founded call to action. Stories have
       Industry                Services                                                                        12
                                                                                                                           a greater emotional impact on us than
                       Retail/Wholesale                                   5.1                                  16          bare numbers, so the communication of
                      Financial Services                                 4.8                                   14          insights and messages can no longer sole-
                         Manufacturing                                   4.8                                   16          ly rely on reports. Engaging and inspiring
                                Utilities                            4.6                                       18          stories drive action based on solid data.
       Best-in-            Best-in-Class                                             6.0                       15          Analytics and BI tools are the major gate-
       class                  Laggards                               4.6                                       17          ways to corporate information treasures.
                        Asia and Pacific                                                6.3                      9          Interactively presenting information and
                                                                                     5.9                                   stories in these tools allows for high ef-
       Global            North America                                                                          9
                                                                                                                           ficiency and helps to ensure data quali-
       regions           South America                                          5.6                            18          ty as well as a high level of trust through
                                Europe                               4.6                                       17          end-to-end traceability. This enables in-
                        Eastern Europe                                               5.9                        9          teraction with data, drilling and analyzing
                           UK & Ireland                                        5.4                             12          details without switching tools or making
                               BeNeLux                                    5.0                                   9          manual adjustments. Interactive analytical
       European                                                          4.9                                               storytelling enhances the credibility of sto-
                      Southern Europe                                                                          19
       regions                                                                                                             ries and allows executives to gain further
                      Northern Europe                               4.4                                        17
                                                                                                                           insights that are cumbersome to glean
                                  DACH                             4.4                                         17          from static, predefined analyses.
                                 France                            4.2                                         17

      n = 2609                        0                                                                   10
                                            Not important at all                             Very important

©2019 BARC – Business Application Research Center                                                                                             BI Trend Monitor 2020        43
Mobile BI
South America and retail/wholesale regard mobile BI as very im-
                                                                                                                                             Mobile BI
portant. BeNeLux is some way behind.

                                                                                                       Rank of trend
                                                                                                       in this region/
                                                                  Average                               industry etc.
                               Vendor                                    5.2                                 16
       Company/          Business user                                   5.1                                 15
       User type                IT user                                  5.1                                 12
                                                                    4.8                                                  Mobile BI – driven by the success of mobi-
                            Consultant                                                                       17
                                                                                                                         le devices – was considered by many as a
                   Less than 100 empl.                                   5.2                                 16          big wave in BI and analytics in the begin-
       Company More than 2500 empl.                                  5.1                                     15
       size                                                                                                              ning of 2010s. Many BI vendors developed
                      100 - 2500 empl.                               5.0                                     15          native apps to provide analytics on mobile
                      Retail/Wholesale                                          5.9                           8          devices. However, adoption was very slow
                               Utilities                                  5.4                                13          and there was a degree of disillusion in
                        Manufacturing                                    5.2                                 12          the market. Our survey results show that
                                 Telco                                   5.1                                 15          mobile BI usage has grown by only 20
                                                                     4.9                                                 percent in the last 8 years. Currently not
       Industry                      IT                                                                      18
                                                                    4.9                                                  even a third of the companies surveyed
                              Services                                                                       17
                                                                                                                         use mobile BI.
                    Public sector/Educ.                             4.8                                      17
                                                                   4.8                                                   In our experience, the most successful mo-
                             Transport                                                                       17
                                                                                                                         bile deployments are those in which a mo-
                     Financial Services                            4.7                                       15
                                                                                                                         bile strategy has already been devised and
       Best-in-           Best-in-Class                                         5.9                          16          the needs of mobile workers are carefully
       class                 Laggards                              4.7                                       16          addressed with the BI tool. So, for examp-
                        South America                                                6.2                     12          le, simply copying an existing dashboard
       Global          Asia and Pacific                                         5.8                           15          to a mobile environment does not fulfill
       regions          North America                                    5.2                                 17          the requirements of all different types of
                               Europe                               4.9                                      13          users. There is great potential for mobile
                     Southern Europe                                           5.7                           10
                                                                                                                         BI to support operational processes while
                                                                           5.6                                           simultaneously increasing the penetration
                       Eastern Europe                                                                        13
                                                                                                                         of BI within organizations. Therefore, it
                          UK & Ireland                               5.0                                     15
       European                                                                                                          is not surprising to see the retail, utilities
                     Northern Europe                                4.8                                      13
       regions                                                                                                           and manufacturing industries using data
                                 DACH                               4.8                                      14          on mobile devices more frequently than
                                France                             4.7                                       15          others.
                              BeNeLux                              4.6                                       18

      n = 2622                        0                                                                 10
                                           Not important at all                            Very important

©2019 BARC – Business Application Research Center                                                                                           BI Trend Monitor 2020         45
Analytic Teams/Data Labs
Analytics teams are prominent in South America, but less relevant                                                                  Analytic Teams/
to organizations in the DACH region and the manufacturing sector.                                                                       Data Labs

                                                                                                         Rank of trend
                                                                                                         in this region/
                                                                    Average                               industry etc.
                                  IT user                                  5.1                                 13
       Company/           Business user                                4.9                                     17
       User type                 Vendor                               4.7                                      18          Data science is the generic term for pro-
                             Consultant                               4.7                                      18          cesses that generate knowledge out of data
                   More than 2500 empl.                                      5.5                               12
                                                                                                                           using methods from statistics, machine
       Company                                                                                                             learning and operations research. Data
                       100 - 2500 empl.                               4.8                                      17
       size                                                                                                                labs are separate business units, specifical-
                    Less than 100 empl.                               4.7                                      18          ly designed to conduct data science in an
                       Financial Services                                        5.5                           11          organization. They offer a space for design
                                                                             5.4                                           thinking and experimentation, aside from
                     Public sector/Educ.                                                                       12
                                                                                                                           established processes in the organization.
                              Transport                                     5.3                                11          Data labs require investment in personnel
                                   Telco                                    5.2                                14          as well as new technologies to store, pro-
       Industry                 Services                                   5.1                                 15          cess and analyze data.
                       Retail/Wholesale                                    5.0                                 17          Against that backdrop, it is not surprising
                                                                           5.0                                             that data science and data labs are of in-
                                       IT                                                                      16
                                                                                                                           creasing importance for larger companies.
                                 Utilities                             4.9                                     15          The IT and the financial industries are the
                         Manufacturing                               4.5                                       17          most likely sectors to adopt data science
       Best-in             Best-in-Class                                               6.0                     14          and data labs. The financial industry, in
       class                                                           4.8                                                 particular, has a long track record of using
                               Laggards                                                                        13
                                                                                                                           data analytics methods. However, gener-
                         South America                                             5.9                         14          ally the importance assigned to data labs
       Global            Asia and Pacific                                         5.5                           17          is much lower compared to advanced an-
       regions           North America                                       5.3                               16          alytics and machine learning. Labs require
                                                                      4.7                                                  considerable investment in terms of staff
                                 Europe                                                                        16          and infrastructure and not many compa-
                         Eastern Europe                                      5.4                               14          nies choose to set up data labs to conduct
                       Southern Europe                                       5.4                               14          data science. Integrating data labs and an-
                            UK & Ireland                                   5.1                                 13          alytics teams poses new challenges and
       European                                                            5.1
                                                                                                                           requires revised organizational approach-
                                  France                                                                       10          es to link data labs, IT departments and
                       Northern Europe                                4.7                                      14          business units. Many companies therefore
                               BeNeLux                                4.6                                      17          integrate data scientists into IT or line of
                                  DACH                               4.5                                       16          business. This has many advantages, espe-
                                                                                                                           cially for the operationalization of analytics
                                        0                                                                 10               solutions.
      n = 2613
                                             Not important at all                            Very important

©2019 BARC – Business Application Research Center                                                                                             BI Trend Monitor 2020         47
Using External/Open Data
Especially relevant in best-in-class companies, but not so much in                                                            Using External/
the UK & Ireland and Northern Europe.                                                                                             Open Data

                                                                                                   Rank of trend
                                                                                                   in this region/
                                                                   Average                          industry etc.
                         Business user                                    5.0                            16
                                Vendor                                   5.0                             17
       User type            Consultant                                   4.9                             13
                                 IT user                                 4.8                             16          It is no secret that data is becoming in-
                    Less than 100 empl.                                    5.2                           17          creasingly important to companies. Its val-
       Company More than 2500 empl.                                      4.9                                         ue continues to rise as more ways to ana-
       size                                                                                                          lyze it emerge. The use of external data to
                       100 - 2500 empl.                                  4.8                             16          enrich companies’ own data goes far be-
                       Retail/Wholesale                                    5.3                           13          yond the purchase of address data. Data
                             Transport                                     5.2                           14          has established itself as a product and ex-
                    Public sector/Educ.                                   5.1                            15          tends analyses with targeted insights from
                                      IT                                 4.9                             17          social media, customer, market, meteor-
                               Services                                  4.8                             18
                                                                                                                     ological, geographical and demographic
       Industry                                                                                                      data, and even analytical findings. Compa-
                        Manufacturing                                4.8                                 15
                                                                                                                     nies can purchase these and many other
                      Financial Services                             4.7                                 17          types of data for their own analysis from
                                Utilities                            4.7                                 17          BI generalists, specialist service provid-
                                  Telco                             4.6                                  18          ers and data trade platforms. Open data
                          Best-in-Class                                          5.9                     17          is used to build business models around
       class                  Laggards                              4.5                                  18          targeted analysis.
                         South America                                          5.6                      17          The use of external data spans all com-
                                                                          5.1                                        pany sizes but there are industries that
       Global            North America                                                                   18
                                                                                                                     rely more heavily on it. The transport and
       regions          Asia and Pacific                                                                  18
                                                                                                                     services industries attach the highest im-
                                Europe                                   4.8                             15          portance to external data – economic de-
                      Southern Europe                                      5.3                           15          velopment statistics for medium-term de-
                                 France                                   5.0                            11          velopments, weather data for short-term
                              BeNeLux                                    4.9                             12          developments and spatial data to opti-
       European                  DACH                                    4.8                             13          mize routing are just a few examples of
       regions                                                      4.6                                              the resources used. Manufacturing relies
                        Eastern Europe                                                                   18
                                                                                                                     little on external data and telecommunica-
                      Northern Europe                              4.3                                   18          tions companies actually generate and sell
                           UK & Ireland                            4.3                                   18          data for use by others.

                                       0                                                            10
      n = 2617                              Not important at all                       Very important

©2019 BARC – Business Application Research Center                                                                                      BI Trend Monitor 2020       49
Cloud BI
Most relevant in Asia & Pacific. Less popular in Europe, especially
                                                                                                                                                       Cloud BI
in France.

                                                                                                              Rank of trend
                                                                                                              in this region/
                                                                    Average                                    industry etc.
                                Vendor                                                                              12
                            Consultant                                         5.0                                  11
       User type         Business user                                     4.8                                      18
                                                                                                                                The global trend of running applications in
                                 IT user                                 4.5                                        18          a cloud environment started to branch out
                    Less than 100 empl.                                          5.4                                10          into the analytics domain about ten or twelve
       Company More than 2500 empl.                                        4.8                                      18          years ago. Start-ups were founded to disrupt
       size                                                               4.7                                                   the established vendors with a platform- or
                       100 - 2500 empl.                                                                             18
                                                                                                                                software-as-a-service business model. The
                                      IT                                             5.5                            12          incumbent vendors, who typically generated
                               Services                                         5.1                                 14          their revenues from on-premises implemen-
                                  Telco                                    4.8                                      16          tations, followed suit and now nearly every
                                                                           4.8                                                  analytics, CPM and data management vendor
                                Utilities                                                                           16          offers a cloud-based solution.
                       Retail/Wholesale                                    4.8                                      18
       Industry                                                                                                                 Cloud analytics and data management now
                             Transport                                    4.7                                       18          have very similar functional capabilities to
                      Financial Services                                  4.6                                       18          their corresponding on-premises products.
                    Public sector/Educ.                                  4.5                                        19          Licensing is often based on a rental or pay-
                                                                                                                                per-use model which reduces the one-off
                        Manufacturing                                                                               18          investment. However, the adoption rate for
                          Best-in-Class                                               5.7                           18          cloud analytics and data management de-
       class                  Laggards                                     4.7                                      15          ployments is still rising very slowly. It is not
                        Asia and Pacific                                                     6.2                     10
                                                                                                                                the attractiveness of the platform that deters
                                                                                                                                organizations from moving their analytics
                         South America                                               5.6                            16
       Global                                                                                                                   landscapes into the cloud. Instead, there are
       regions           North America                                               5.5                            14          many contributing factors: legal, security and
                                Europe                                   4.4                                        18          privacy concerns, a shortage of best practice
                                                                                      5.6                                       advice on how to build hybrid or multi-cloud
                           UK & Ireland                                                                             10
                                                                                                                                architectures, a lack of trust in the vendors,
                        Eastern Europe                                           5.3                                16          and the desire to keep company data under
                      Southern Europe                                          5.0                                  17          the control of the IT. However, the overarch-
       European               BeNeLux                                      4.8                                      15          ing issue is that analytics leaders prefer to
       regions                                                           4.5                                                    bring the analytics to the data, and not the
                      Northern Europe                                                                               16
                                                                                                                                other way around. As such, organizations
                                 DACH                               4.1                                             18          with much of their data already in the cloud
                                 France                            3.8                                              18          show a much higher cloud affinity than those
                                                                                                                                with all their data on premises.
      n = 2624                         0                                                                       10
                                            Not important at all                                  Very important

©2019 BARC – Business Application Research Center                                                                                                   BI Trend Monitor 2020          51
Data Catalogs
Data catalogs are most important in the South America and least
                                                                                                                                      Data Catalogs
relevant in Northern Europe and France.

                                                                                                         Rank of trend
                                                                                                         in this region/
                                                                    Average                               industry etc.
                                  IT user                                   4.4                                19
       Company/                  Vendor                                    4.3                                 19
       User type             Consultant                                   4.1                                  19
                          Business user                                4.0                                     20          Data is essential for BI and analytics and
                   More than 2500 empl.                                         4.6                            19          thus also for expanding a company’s abil-
       Company      Less than 100 empl.                                   4.1                                  19          ity to respond to change through digitali-
       size                                                                                                                zation. However, the ability to use data is
                       100 - 2500 empl.                               4.0                                      20
                                                                                 4.8                                       no small matter. Unsufficient data hinders
                     Public sector/Educ.                                                                       18
                                                                                                                           the BI and analytics process and impairs
                              Transport                                         4.7                            19          value creation from data. The desire for a
                                   Telco                                        4.6                            19          central data store can therefore be great,
                       Financial Services                                   4.4                                19          but also very complex to implement.
       Industry                 Services                                   4.3                                 19          Currently, the solution to these challenges
                                       IT                                  4.2                                 19          is seen in the deployment of a data catalog.
                                 Utilities                                4.2                                  20          Data catalogs are designed to register, cat-
                       Retail/Wholesale                                4.0                                     20          alog and link data in order to make it find-
                                                                      3.8                                                  able and usable for “everyone”. This helps
                         Manufacturing                                                                         20
                                                                                                                           to fulfill regulatory as well as business re-
                           Best-in-Class                                              5.1                      19
       Best-in-                                                                                                            quirements. This is possible by describing
       class                   Laggards                                   4.1                                  19          data objects and their relationships with
                         South America                                                 5.4                     19          metadata without having to physically in-
                         North America                                           4.8                           19          tegrate data. The use of a data catalog,
       regions           Asia and Pacific                                         4.8                           19          however, requires a different way of think-
                                 Europe                               3.9                                      19
                                                                                                                           ing and an awareness that data catalogs
                                                                                                                           must be actively maintained. Technology
                         Eastern Europe                                                                        20
                                                                                                                           can assist this process with connectors to
                               BeNeLux                                      4.4                                19          different types of sources, workflows, UIs
                       Southern Europe                                      4.4                                20          and collaboration functions as well as line-
       European             UK & Ireland                                   4.2                                 19          age analysis and cross references.
                                  DACH                               3.8                                       20
                                  France                            3.6                                        19
                       Northern Europe                              3.5                                        19

                                        0                                                                 10
      n = 2400                               Not important at all                            Very important

©2019 BARC – Business Application Research Center                                                                                             BI Trend Monitor 2020        53
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