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Winning the Analytics Arms Race
Retailers are not yet up to speed with advanced analytics,
but they are racing to catch up fast
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Winning the Analytics Arms Race
Retailers are not yet up to speed with advanced analytics,
but they are racing to catch up fast
While a few high-performing retailers have made analytics
central to their business models, the overwhelming truth is
that most have not. This inadequate state of affairs has been
arrived at after retailers have invested in a variety of BI tools
over the years and now possess databases that scream out for
attention and double in size every 18 months.
Too often CIOs have taken the view that a retailer’s data
resources are a challenge that needs to be beaten into submission instead of an opportunity to drive new business. As a
result, retail databases are typically under used and underappreciated.
Where is your organization on an analytics maturity model?
Do you have multiple analytics tools in different stages of advancement? Do your executives have the ability to conjecture
future outcomes using predictive analytics or do they just receive standard hindsight views? What inhibitors are holding
back your organization from deploying advanced analytics?
We wanted to find out the answers to these questions and
take a deeper dive into current and future trends in advanced
analytics in retail. In the end, the overwhelming conclusion
found in this study is that while retailers may not be up-tospeed today with their analytical capabilities, they are racing
What’s Next for Retail Analytics?
As a follow-on to our survey, RIS News engaged Peter Charness, President of Manthan Systems, U.S., to get his views, and that of his
company, on the future of retail analytics:
Q: Is knowing the future the Next Big Thing in Retail BI?
A: Many retailers are still struggling with knowing what happened
yesterday, and to know that by item, by store, by customer, even
by tweet, is still a challenge. Even more critical to future success is
having the ability to take action on that information, and to provide
this capability broadly, from executives to store associates and out
to suppliers.
Q. Wasn’t that the goal of traditional Retail Data Warehouse
projects?
A: Yes, but such efforts require complex and costly ongoing IT development projects. The business teams need specialized skills to utilize
these tools, and let’s face it, complex IT projects don’t always deliver
as planned. Add to these challenges expensive user based software
licenses and the fact that most BI tools underwhelm as they are focused on “informing,” not on action. This is why retailers need more.
Q: How do retailers solve this problem?
A: BI solutions are now available as packages, eliminating the
need for risky, costly IT projects. These packaged retail analytic applications are comprehensive and provide innovative new ideas and
methods to Retailers. Enterprise licensing models and better thoughtthrough user interfaces make it practical to extend BI to every store
associate and, if desired, with collaboration to every supplier. Finally,
newer BI solutions go far beyond providing just analytical guidance,
they provide the capability to simulate best outcomes, and through
workflow, implement the desired actions.
Manthan Systems
800-746-9370 x108
www.manthansystems.com
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s po n s o re d by
F I G U R E 1 to catch up as quickly as they can.
Status and Maturity of Advanced
Analytical Capabilities
In an effort to dig deeply into the current
state of advanced analytics in retail we broke
out our benchmarking question into three
categories – performance analytics (analyzing
data used for merchandising, operations and
store KPIs), customer and marketing analytics, and predictive analytics.
Of these three categories, the most advanced is performance analytics, where 17.1%
say they have up-to-date technology in place.
This raises the question: Is 17.1% a large slice
of the pie? No, not really. But it isn’t too far
off the mark. When doing studies like this,
mature areas of technology, such as POS or
merchandising or workforce management,
would typically register a number between
20% and 30%. (Keep in mind no technology
is ever up to date for long before evolutionary
upgrades are introduced, so it is rare in studies if more than 30% of retailers say they are
up to date with any particular technology.)
However, while the up-to-date percentage
is on the low side, the number of retailers who
are updating now is high at 48.8%. Add another 17.1% who say they will begin updating
by the end of 2012 and a picture of massive
investment in this technology emerges.
An even more dramatic picture emerges
for customer and marketing analytics. In
this category there is a lower level of up-todate technology in place (12.5%) and a much
higher level of updating activity currently being done (62.5%).
This latter number is unusually high by any
standard and, as noted earlier, it helps make
the case that retail investment intentions in
the area of analytics is at a very high level. Is
it an all-time high? This is difficult to say because we do not have multi-year comparisons
available that slice and dice data in exactly
this way, but it is hard to imagine investment
interest ever being much higher.
One last point to make about the level
of focus on customer and marketing analytics: Jeff Roster, a Gartner research analyst,
recently noted that by 2015 the technology budgets for retail marketing departments
To help support analysis of PERFORMANCE data, what is the
staus of your organization’s advanced analytical solutions?
Plan to update
in 2013
Will begin by
end of 2012
7.3% 9.8%
17.1%
No Plans
17.1%
Up-to-date
tech in place
48.8%
Updating now
F I G U R E 2 To help support analysis of CUSTOMER and MARKETING data,
what is the status of your organization’s advanced analytical solutions?
2.5%
Plan to update
in 2013
Will begin by
end of 2012
7.5%
15%
12.5%
No Plans
Up-to-date
tech in place
62.5%
Updating now
will equal or surpass the budgets for the IT
department. While we didn’t ask who is in
charge of the budget for this question, there
is no doubt that the marketing department is
the beneficiary of it, which makes this a confirming point to the overall trend that RIS has
been calling the “rise of the chief marketing
officer (CMO)” in retail.
Of the three advanced analytics categories highlighted here, predictive analytics is
the most advanced, the least familiar, and
the hardest to reach for retailers who do not
have the skills and qualified staff in-house to
ensure the technology can actually live up to
expectations. (Figure 3.)
As a result, the percentage of retailers who
say they have up-to-date tech in place is just
10.5%, and the figure for those who are up-
dating now is just 34.2%, both of which are
the lowest numbers of the three categories
benchmarked in this study. This trend is also
borne out by the high number of retailers who
say they have no adoption plans – 21.1%
The big takeaway here is that retailers who
have already taken steps to move down the
road to deploying predictive analytics have
a clear advantage over retailers who haven’t,
which is currently a big majority of the
marketplace.
Retailers who have up-to-date predictive
analytics tools in place are able to do affinity analysis that tells them which products
drive purchases of other products and what
is the optimal pricing for both. Then this tool
enables retailers to conjecture what happens
when you link the product that triggers the
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initial transaction to a different trigger product through a promotional campaign that
ultimately multiplies purchasing of a host of
products.
Multi-variant predictive analysis on this
scale is not possible without having advanced
predictive tools in place, and those retailers
that possess them will have a multi-year advantage over those who do not to increase
sales and profits before competitors catch up.
So, we now see that retailers are furthest
down the road in deploying performance analytics solutions. Most are focused on getting
up to speed with customer and marketing
tools, and are least advanced with predictive
analytics capabilities. The question this raises
is: How does this all add up to a position on
an advanced analytics maturity ladder?
To get an answer to this question we asked
retailers to assess their overall analytical capabilities according to three steps on a maturity ladder: Step 1. Basic analytical capabilities with fixed delivery methods for standard
reports; Step 2. Descriptive analytical capabilities using historical data where users have
the ability to investigate patterns; and Step 3.
Predictive analytical capabilities that enable
retailers to conjecture future outcomes.
The good news from a survey standpoint
is that the percentage of retailers who selected Step 3. Predictive (10.3%) is virtually the
same number as those who said they have upto-date predictive analytics in place (10.5%)
in the previous question. This is a nice confirming point that gives us confidence in the
rest of the study.
However, the dominant answer to the maturity question is that most retailers are located on the Step 2. Descriptive rung (51.3%).
As previously noted, descriptive is a term used
in analytics to differentiate between those
who use historical data (year over year, month
over month, and so forth) and those who conjecture outcomes (predictive).
Nearly two fifths of retailers believe they
are on the lowest rung of the maturity ladder, Step 1. Basic (38.5%). This indicates a
large number of retailers have a great deal of
work to do to upgrade their analytics capabili-
s po n s o re d by
F I G U R E 3 To help support a shift to insights driven by predictive analytics,
what is the status of your organization’s analytical solutions?
No Plans
Plan to update
in 2013
21.1%
10.5%
Up-to-date
tech in place
34.2%
18.4%
Updating
now
15.8%
Will begin by
end of 2012
F I G U R E 4 Where does your organization stand on this analytics maturity ladder?
10.3%
Step 2 Descriptive:
Users have ability
to investigate
patterns
51.3%
ties beyond the basic level and much more to
do before they can be truly equipped with advanced capabilities.
This also confirms the takeaway that retailers who are already on Step 3 of the maturity
ladder have a multi-year head start to fine tune
their capabilities and reap the benefits before
less advanced retailers catch up.
Who Needs Analytics?
In previous questions we discovered that performance analytics (the capability of analyzing data used for merchandising, operations
and store KPIs) was the most advanced analytical tool set in the retail enterprise. So, it
makes sense to assume that the merchandis-
38.5%
Step 3 Predictive:
Ability to conjecture
a future outcome
Step 1 Basic:
Fixed delivery of reports
ing department or store operations department would be most in need of advanced analytics to do their jobs effectively. Wouldn’t it?
However, it turns out that the top department on this list is marketing, which was
chosen by 84.6%. It was a clear winner over
merchandising (79.5%) and store operations
(69.2%), which come in second and third.
This is a confirming point to the takeaway
previously noted about the high level of upgrade activity currently taking place in the
area of customer and marketing analytics. It
also confirms the rise-of-the-CMO trend that
RIS has been tracking through other studies
and reports.
In years past, retailers believed the best
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s po n s o re d by
F I G U R E 5 area for investment in advanced analytical
tools was in service of merchandising and
store operations to help them do their jobs
more effectively. But the emphasis has clearly
shifted to marketing, which is assuming an
ever-increasing role in omni-channel retailing, a trend not likely to end any time soon.
Now that we know which department
most needs advanced analytics we wanted
to find out which specific job functions are
most in need of analytics to do their jobs effectively. Topping the list are high-level analysts (62.9% use advanced tools now), who are
trained to use advanced tools and whose job
depends on them.
In second place on this list are e-commerce executives (58.1% use now), and in
third place are merchandisers (51.4% use
now). These latter two groups of executives
both rely on data and analysis to deliver
strong performance from the online channel
(for e-commerce executives) and from the
product mix (for merchandisers). But where
are the marketers? Isn’t their department the
one that is most in need of advanced analytics? Absolutely.
We see evidence of a focus on the marketing department when we look at the chart
segment that tracks plans for adding analytical support in the immediate future. When
looking at this metric we see that 45.5% of
retailers say marketers are scheduled to get
advanced analytical capabilities by the end of
the year, which is a big number that dovetails
nicely with other datapoints in the study.
Interestingly, marketers will not be the
beneficiary of the most activity to add analytics by the end of the year. That honor goes
to social business executives, where 56.7%
of respondents say they plan to add analytics
support by the end of the year.
When we asked retailers to tell us how
they distribute analytical reports throughout
their organizations we found the top two answers to be nearly ubiquitous: 1. Reports by
request (chosen by 78.9%) and 2. Regularly
scheduled reports (76.3%). These methods
are a standard operating procedure and it is
actually surprising they didn’t score 100%. (In
What departments in your organization are in need of advanced
analytical tools to do their jobs effectively?
Marketing
84.6%
Merchandising
79.5%
Store operations
69.2%
53.8%
Supply chain
Purchasing
46.2%
35.9%
Sales
Vendors/suppliers
30.8%
Financial
28.2%
F I G U R E 6 Who in your organization currently uses advanced analytical
capabilities?
High-level analysts
E-commerce
Merchandisers
Marketers
Supply chain executives
C-suite
Area/district managers
Supply chain partners
Store managers
Social business
22.9% 14.3%
62.9%
25.8% 16.1%
58.1%
8.1%
40.5%
51.4%
45.5%
9.1%
45.5%
21.4%
42.9%
35.7%
15.4%
42.3%
42.3%
34.5%
34.5%
31%
35.7%
21.4%
25.9%
25.9%
48.1%
22.6%
10%
56.7%
33.3%
Use Now
the world of statistical analysis scores of 100%
are rarely found even if it would seem to be
the correct response.)
More advanced methods of report distribution are much less common in retail. For
example, delivering multiple dashboards for
different executives comes in at 39.5% and
flash reports at 34.2%. (Figure 7.)
Although not highly placed today, there is
little doubt that mobile dashboards (18.4%)
and mobile alerts (13.2%) will get much
Plan to support by year’s end
No immediate plans
higher usage as tablets and other mobile devices continue to explode in retail.
Optimization and Inhibitors
As we have seen in previous datapoints a
trend is emerging that shows current use of
advanced analytical tools is aimed at supporting efforts to improve performance
(merchandising, operations and store KPIs)
and that future plans point to investments
in the area of marketing. We see more evi-
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dence of this theme in the chart showing
which data sources retailers have integrated
into their advanced analytical/data warehouse
capabilities. (Figure 8.)
At the top of this chart is POS transactional data (73% said POS data is integrated into
advanced analytical/warehouse capabilities).
POS data is the heart and soul of every retail
organization, so it should come as no surprise
to see it at the top of the list. The Association for Retail Technology Standards (ARTS)
estimates there are more than 30 applications
that link to the POS and many of them use
the data in their standard workflows.
The next two data sources are supply chain
(60%) and category management (54.3%),
and they are related. Supply chain is an overarching pillar of retailing and category management is one of the many elements that fall
under its umbrella.
With so much emphasis on marketing in
previous datapoints we might have expected
to see the customer loyalty database appear
higher on the list. It comes in fourth place
when looking at those retailers who say they
have integrated this data source now. However, it comes in first place when sorting options
by “will support by end of year.” In this confirming datapoint it scores 40.5%, well above
any of the other options.
It is always worthwhile to look into inhibitors that are holding back broader adoption
of any technology, and when we framed the
question for this report we decided to eliminate “lack of budget” as one of the options,
because it always comes out on top and tells
us very little about deeper issues. (Figure 9.)
The top four inhibitors on the list tell an
interesting story. They are data integration
(48.6%), adding/hiring new skill sets (45.9%),
training (45.9%) and elevating analytics as a
core priority (40.5%).
Solving the data integration problem is a
big undertaking that only needs to be done
once, but since it takes place below the application layer it is invisible to most executives,
difficult to secure budget, and therefore frequently postponed. For many retailers it is the
s po n s o re d by
F I G U R E 7 How is advanced analytical reporting distributed throughout
your organization?
78.9%
Reports by request
76.3%
Regularly scheduled reports
39.5%
Multiple BI dashboards
34.2%
Flash reports
User-customizable dashboard
23.7%
Mobile dashboard
18.4%
Desktop/laptop dashboard
18.4%
Desktop alerts
Mobile alerts
15.8%
13.2%
F I G U R E 8 Which data sources in your organization have been integrated
into your advanced analytical/data warehouse capabilities?
POS transactions
Supply Chain
Category management
Competitive performance
Suppliers/partners
Customer loyalty
73%
60%
54.3%
31.4% 22.9%
31.3%
31.3%
21.6%
40.5%
Have now
21.6%
5.4%
8.6%
31.4%
14.3%
31.4%
45.7%
37.5%
37.8%
Will support by end of year
No immediate plans
F I G U R E 9 What inhibitors are holding back broader distribution
of advanced analytics in your organization?
Data integration is an issue
Adding/hiring new skill sets
Training
Elevating analytics as a core priority
Data integrity is an issue
Hard ROI
Too difficult to manage/maintain
48.6%
45.9%
45.9%
40.5%
32.4%
27%
16.2%
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elephant in the room. You know it’s there but
don’t want to acknowledge it.
The next three items are all related to the
necessity of embedding the pursuit of analytics into the retailer’s corporate culture. Most
retailers do not currently possess a staff of
high-level analysts (or enough of them) and
therefore need to recruit, hire and train them
to take advantage of truly advanced analytical
tools. This kind of coordinated effort can only
occur when analytics are elevated as a core
priority.
s po n s o re d by
F I G U R E 1 0 What is your organization’s annual revenue?
Less than $100 million
20.5%
33.3%
$2 billion
or higher
$100 million to $500 million
25.6%
$1 billion to $2 billion
12.8%
7.7%
$500 million to $1 billion
Methodology
This study was conducted during the month
of February and only senior executives from
national or large regional retailers were invited to participate. The results do not include
any store-level, field level or regional employees. Only headquarters level staff responses
were included.
FIGURE 11
How did your company’s sales revenue perform in the last
12 months?
32.4%
Conclusion
RIS has been tracking the rise of the retail
CMO for more than a year and the evidence
keeps piling up. Clearly marketing departments drive revenue and advanced analytical
tools help them achieve this goal.
Advanced analytical tools in the hands
of skilled executives have a measurable
impact on revenue, and in a year when
revenue growth is a top priority these tools are
assuming an increasingly vital role in retailer
success.
A retail enterprise that gets maximum value out of its analytics capabilities is one that
has an integrated framework that employs
quantitative methods to derive actionable insights from data, and then uses those insights
to shape business decisions to improve outcomes.
The end game is the creation of a retail
organization where analytics capabilities solve
problems, predict outcomes and deliver results. When the transformation is complete,
analytics will be an engine that helps drive
revenue growth, profitability, customer loyalty
and innovation. RIS
Increased
between
0%-3%
18.9%
Decreased
48.6%
Increased greater
than 3%
FIGURE 12
For 2012, what is the status of your organization’s IT budget?
15.8%
52.6%
Increased
between
0%-5%
Decreased
31.6%
Increased
more than 5%
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