Advanced Demand Forecasting - NEAL ANALYTICS CASE STUDY
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For retail and many other industries, demand
forecasting has been an important and frequently
utilized solution due to its ability to capture and
combine historical trends with key factors to estimate
future demand. However, while forecasts are usually
Advanced Demand accurate when driven at a macro level, accuracy falls
off rapidly as one drills down into specific segments.
Forecasting
Unfortunately, more actionable forecasts usually occur
at a micro level. The ability to drill down to a more
granular level and explain the nuanced demand in
NEAL ANALYTICS CASE STUDY individual markets is key for district and store
managers to understand where their business is
By Clarissa Koszarek and David McClellan succeeding and failing. Essentially, granular demand
forecasts have the potential to be the most impactful,
but are often the most challenging to model and are
ripe for techniques like Machine Learning to solve.
H&R Block saw this as an opportunity to resolve
longstanding gaps & gain a deeper understanding of
what drives their business when it approached Neal
Analytics with two goals: construct an advanced
analytics solution to better forecast the total number
of tax returns in the 2018 tax season, and gain a
deeper understanding of the contributing factors
driving that demand. On the surface, this appears to
be a simple demand forecasting problem, but when
you consider that H&R Block has the most seasonal
demand in the S&P 500, or that traditional customer
factors are not realistic predictors, this posed a unique
and interesting challenge. Neal Analytics was eager to
support where H&R Block had yet to succeed with
other consulting firms or using internal teams.
Advanced Demand Forecasting
Creating a Competitive Advantage in a Unique Market
Leveraging Industry Expertise solid forecasts and insights on a
Given the limited timeline week-by-week basis for the 2018
leading up to the 2018 tax tax season, Neal Analytics hit the
season and the need to develop ground running, developing
a sophisticated machine learning forecast models to predict the
solution quickly, Neal Analytics total number of tax returns to be
targeted specific forecasting and filed in their offices. These
business goals to quickly build models adjusted dynamically on
an enterprise grade solution for a weekly basis based on actual
“This solution fills a critical critical milestones, leading to use returns filed the previous week,
need for our business in in the 2018 tax season. By using and Neal Analytics’ predictions
that it provides my team Neal Analytics’ forecasting tools for total returns were within 2%
and I with the data and leveraging H&R Block’s of the final number at the start
industry expertise, Neal Analytics of the season. Providing H&R
needed to go to the CEO
provided H&R Block with Block with high accuracy so early
with insights that result in on in the 2018 Tax Season gave
action, positively affecting accurate forecasts earlier in the
tax season, as well as an in- their operations team more
our clients and our bottom clarity and foresight on how best
depth look at the key drivers of
line.” their complex business, thus to plan office execution through
enabling tactical adjustments to the season, pivoting strategies
Ed Dobbles maximize performance in each on the fly as needed to capture
Vice President, Analytics company district. maximum business. This solution
and Pricing, H&R Block armed H&R Block with new
capabilities that would assist this
Predicting an Evolving Market established leader in staving off
The tax preparation industry is threats from their competition.
an established, yet due to
culture shifts and technology
Office Level Forecasting
innovation, constantly evolving
ecosystem in which H&R Block As a whole, H&R Block operates
has been a major player for over 12,000 offices that are broken up
60 years. With the growth of into a multitude of districts
online preparation software, as consisting of both franchise and
well as continued competition corporate locations. Previously,
from traditional competitors, return forecasts and strategic
H&R Block tasked Neal Analytics management were only run at a
to provide them with key companywide level, with no
insights to increase annual concrete picture of what was
return counts and market share. driving variance in performance
As an additional challenge in the from one location to the next.
industry, over 95% of their Neal Analytics aimed to resolve
business is condensed to about this gap by training thousands of
3 months, compounding the individual machine learning
need for immediate intervention models and utilizing the
when things are off pace and consensus predictions across
requiring precise and immediate various sensitivities for each
execution to reach seasonal market, providing reliable local
targets. With the goal of arming forecasts and identifying the key
H&R Block’s leadership with drivers of increased returns.
Advanced Demand Forecasting
Creating a Competitive Advantage in a Unique Market
Using the analysis of the key drivers tailored to each to solve this problem with tools
drivers of higher return counts, manager’s small group of stores. such as Tableau and open source
we were able to isolate the One example of this relates to code, they ultimately failed to
effects of price on demand and labor hours, by far the greatest significantly advance H&R Block’s
compare the effects of discounts expense in any services company. analytics capabilities, leading to
to better understand trade-offs. By utilizing their internal labor interest in what the Neal
By analyzing these effects at both data, Neal Analytics was able to Analytics team could provide in
the whole company and district isolate the effects of adding or thought leadership. H&R Block
levels, H&R Block was able to removing hours from a given needed concrete ROI from a true
better understand in which district to see its effects on business solution to prove the
markets certain pricing and production. Ultimately, the value from the cloud and data
discount strategies were the success of the solution has science. With this engagement,
most effective. As a result, Neal ensured the final output will be Neal Analytics delivered that ROI
Analytics not only provided integrated into H&R Block’s and the competitive advantage of
accurate weekly forecasts for strategic planning for many tax Azure Machine Learning in only a
district managers, but also seasons to come. Although H&R few months’ timeline.
dissected the key performance Block had previously attempted
Data Simulated
Transforming Data to Insights efficiency, arming operations with Within this tax season, H&R Block
Structuring returns data for the the tools to reel in employee was able to apply the analysis
machine learning models also hours and cut operational spend. from the Power BI dashboards to
enabled a variety of BI Following this success, there is identify the top and bottom
dashboards. This context helped now an initiative to place Power performing districts and
HRB gain insight into which BI analysis dashboards in the categorize key factors leading to
regions are most efficient and hands of sales leads, analysts, their performance. These insights
productive, as well as provide managers and executives will become the main points of
clarity on how or where adding companywide. This exposure to change in the 2019 tax season,
employee hours has the ML derived BI has generated but in the hands of district
strongest impact on demand. To momentum and innovation in a managers, also enabled tactical
top it off, this analysis highlighted company with a promising interventions and investments in
the districts with the lowest enthusiasm for analytics and a the operations that most
desire to outrun its competitors. impacted their business.Advanced Demand Forecasting
Creating a Competitive Advantage in a Unique Environment
As an example, H&R Block President of Analytics and The combination of Neal
discovered that in a few Pricing at H&R Block, has Analytics and the Microsoft
districts, one of the most attested to the impact of the Cloud came through for H&R
important factors in the loss of solution saying “This solution Block, just in time for the tax
tax returns filed in stores is the fills a critical need for our season, allowing H&R Block to
retention of clients for more business in that it provides my forecast earlier and more
than 3 years. By highlighting team and I with the data importantly, actionably interpret
this factor, H&R Block is able to needed to go to the CEO with it, while setting up a long-term
pinpoint marketing investment insights that result in action, analytics platform in Azure with
and implement additional positively affecting our clients many additional use cases on
changes contributing to client and our bottom line. Further, the roadmap. We look forward
satisfaction and thus improved we can deploy these Power BI to their continued success and
retention. Another example of a dashboards to our store consider this an outstanding
key feature factoring into the managers so they can see in customer outcome where exotic
loss of tax returns is the real time how their stores are data science and AI were able to
number of hours their tax forecasted to perform, but generate real business value in a
preparers work in a week. Upon most importantly, how to rapid deployment methodology.
further analysis, H&R Block improve it.”
discovered that they may have Future Development
been ramping down the By addressing the demand With the 2018 Tax Season
number of hours assigned to a forecasting and sales driver officially ended, H&R Block now
tax preparer too quickly, thus analysis problems in unison, has the capabilities to review
decreasing the number of H&R Block is now able to drive their operation and execution of
returns filed per hour and real time improvement to the this year’s tax season, viewing
increasing the wait times and management and operations of performance through a few new
client dissatisfaction. A district their corporate offices. Armed lenses. By adjusting their overall
manager can now optimize with this information from strategy before the 2019 tax
their store’s operations so that dynamic and clear reporting, season, H&R Block intends to
they are investing in the right their analysts and managers will capture additional market share
activities to maximize customer better be able to handle next with better offerings, improve
outcomes and increase annual year’s operational changes and operations by focusing on what
returns. identify what changes are matters most to the customers
needed by implementing the in each market, and adjust
proactively to the predicted
On-Demand Store Analysis best practices of top offices
and intervening with their events and market environment
Beyond an accurate number to in the upcoming weeks.
report to shareholders and Wall bottom performers.
Street, the primary value of the
solution is derived from the
ability to generate week-by-
week analysis of performance.
This enabled a pivot to better
execution throughout the
season instead of waiting until
after the season is completed
and making changes for the
next. This ability has had a
ripple effect of value to the
business. Ed Dobbles, the Vice
Data SimulatedAdvanced Demand Forecasting
Creating a Competitive Advantage in a Unique Environment
Overview Customer Profile
Customer: H&R Block H&R Block operates both in-office and online tax
Website: www.hrblock.com preparation by tax professionals in 12,000 offices
Country or Region: United Sates across the United Sates. In 1955, H&R Block was
Industry: Tax Preparation founded in Kansas City, Missouri and has since then,
Employee Size: 87,500 developed a long-standing tradition of excellence in
Partner Name: Neal Analytics the tax preparation industry. As a leader in
Website: www.NealAnalytics.com technology in it’s industry, H&R Block assisted the
IRS in testing the now-booming e-filling method
back in 1986, and in 2017 surpassed it’s competitors
by introducing advanced intelligence and machine
learning. The company’s shares trade on the NYSE
under the ticker symbol “HRB.”You can also read
