The intelligent retailer's world of insight(1)

The Intelligent Retailer’s World of Insight

Benchmark Report 2011

Brian Kilcourse and Paula Rosenblum, Managing Partners

November 2011

Sponsored by:

Supporting Sponsors:

i

Executive Summary

In an era of continued global economic uncertainty, rapid response to market conditions is

increasingly important. Once disparate departments within the retail enterprise now need to

respond as a single organism. An important tool to enable this responsiveness is an Enterprise-

wide BI strategy. The need has grown and more retailers are moving in the direction of putting

one in place. The value of this enterprise-wide strategy is to ensure that each department is

operating from the same set of data, delivered at the same time. Delivery mechanisms can and

will likely differ depending on the physical location of the data consumer, but the data itself is

consistent across channels, geographies, departments and roles.

Business Challenges

In the five years that RSR has been conducting benchmarks on the subject of BI, retailers have

consistently expressed a need to move more quickly. The need for speed remains the most

frequently cited business challenge driving new BI and Analytics initiatives. But the challenge is

different for Retail Winners compared to all other retailers. While average and laggard performers

aren’t getting the information quickly enough, most Retail Winners are getting the information

quickly, but are unable to react to what it reveals. Additionally, more real-time information on

relevant and personalized cross-sells, up-sells and hot promotions, along with actionable

information about customer complaints, should be deliverable - but the industry, for the most part,

is lagging.

Opportunities

Most retailers share the same desire to retain customers longer, and as a result have shifted the

focus of their BI efforts to the stores. Winners additionally focus on improving their ability to react

more quickly to supply chain disruptions outside the “four walls” of the business. Non-winners put

more faith in opportunities that are inside “the four walls” of the business, after the receipt of

goods.

Organizational Inhibitors

For most retailers, siloed information contained in existing “legacy” transactional systems is by far

their biggest operational impediment to delivering new generation BI capabilities. But retailers

also complain more that it’s hard to quantify the technology ROI for new BI capabilities. To

overcome this inhibitor, many are turning to pilot projects to prove the value of new BI and

Analytics capabilities.

Technology Enablers

Retailers understand that without a robust technology infrastructure, transforming mountains of

transaction and customer data into useable metrics is almost impossible. While the “plumbing” for

BI is being put into place, retailers are excited at the prospect of bringing consumer-grade

usability into the enterprise. But today’s reality is different: while desktop scorecards and

dashboards have clearly become more ubiquitous, a surprising percentage of C-level executives,

store managers and other retail executives are still predominantly getting their analytics through

“Flash” reports.

BOOTstrap Recommendations

RSR’s recommendations to retailers regarding next-generation BI and Analytics are as follows:

ii

1. Get an enterprise-wide BI strategy in place. Such a strategy will have these critical

components: executive commitment; an infrastructural plan for creating, retrieving, updating,

and deleting “big data”; a wireless plan for the stores; a roadmap that insures a step-wise

approach to implementation, and modern “delivery vehicles” for actionable information.

2. Prioritize those who most need real-time information, and information that is most valuable.

Temper the enthusiasm created by consumer-oriented smart mobile technologies with

appreciation for the underlying complexities.

iii

Table of Contents

Executive Summary ........................................................................................................................... i Research Overview ......................................................................................................................... 1

Why Did We Undertake This Research? ..................................................................................... 1 Traditional Approaches and Conventional Wisdom Now Fall Short ............................................ 2 Guidelines Used for Describing BI in this Report......................................................................... 3 RSR’s Methodology and “What’s a ‘Retail Winner’ Anyway?” ..................................................... 4

Defining Winners and Why They Win, and Why Laggards Fail ............................................... 4 Survey Respondent Characteristics ............................................................................................ 4

Business Challenges ....................................................................................................................... 6 Can’t Get Information Fast Enough or Can’t Act on What They See .......................................... 6 Delivery Mechanisms Lag ............................................................................................................ 7 The Data Delivered Remains Somewhat Pedestrian .................................................................. 8 Despite the Challenges, Opportunities Abound ........................................................................... 9

Opportunities ................................................................................................................................. 10 Pushing Reaction Time To The Front Of The Process .............................................................. 10 Getting Smart In The Store ........................................................................................................ 11 What About New Demand Signals From Social Media? ........................................................... 12

Organizational Inhibitors ................................................................................................................ 14 Siloed Systems Supporting Siloed Business Units .................................................................... 14 Status Quo ................................................................................................................................. 15 Pilot Projects Gain Favor ........................................................................................................... 16

Technology Enablers ..................................................................................................................... 18 There’s a Lot of Plumbing Under those Dashboards ................................................................. 18 Beyond the Excitement and Promise, What’s the Reality Today? ............................................ 19

BOOTstrap Recommendations ..................................................................................................... 21 1. Get an Enterprise-wide BI Strategy in Place ......................................................................... 21 2. Prioritize those Who Need Real-time Information Most ......................................................... 21 3. Temper Enthusiasm with Appreciation for Complexity of the Task ....................................... 21

Appendix A: RSR’s Research Methodology .................................................................................... a Appendix B: About Our Sponsors.................................................................................................... b Appendix C: About RSR Research .................................................................................................. d

iv

Figures

Figure 1: Not Your Father’s Uses for Business Intelligence ............................................................ 1

Figure 2: Enterprise-wide BI: 80% are doing SOMETHING…. ....................................................... 3

Figure 3: Either We Can’t Get the Data or We Can’t Do Anything about It ..................................... 6

Figure 4: Smaller Retailers Challenged to Recognize Best Customers .......................................... 7

Figure 5: Delivery Vehicles Lag for Everyone but Consumers ........................................................ 8

Figure 6: Pedestrian Data Yields Sub-optimal Results ................................................................... 9

Figure 7: Nimble On The Buy Side? .............................................................................................. 10

Figure 8: Getting Back To The Store ............................................................................................. 12

Figure 9: Not Getting All The Signals - Yet ................................................................................... 13

Figure 10: Legacy .......................................................................................................................... 14

Figure 11: Frog In a Kettle? ........................................................................................................... 15

Figure 12: “Try It, You’ll Like It!” .................................................................................................... 16

Figure 13: Infrastructures Matter ................................................................................................... 18

Figure 14: Delivery Mechanisms all Sound Really Appealing… ................................................... 19

Figure 15: …but Reality Lags Behind ............................................................................................ 20

1

Research Overview

Why Did We Undertake This Research?

Business Intelligence and its resultant analytics have come a long way in retail over the past five

years. These changes are enabled by faster hardware and informed by new data and user

interfaces emerging from the consumerization of IT. New, simpler to use tools and techniques are

being used by retailers track and monitor performance.

Specifically we find BI-generated reports, dashboards and alerts:

• moving out of the glass house into the hands of decision-makers

• shifting from long lag-time look backs to near-real-time feedback loops

• becoming more granular and detailed

• shifting focus from solely within the enterprise to 360 degree views – from source to

consumption

This is evident in retailers’ assessment of BI value (Figure 1):

Figure 1: Not Your Father’s Uses for Business Intel l igence

Source: RSR Research, November 2011

While retail over-performers (the group RSR calls “Retail Winners”) have a slightly different focus

than the aggregate, the overall response pool calls out the importance of getting information

faster and places a greater focus on evaluating the entire value chain, from source to

consumption.

29%

36%

36%

38%

39%

42%

42%

57%

62%

40%

41%

54%

45%

36%

29%

40%

30%

32%

31%

23%

11%

16%

25%

29%

19%

12%

5%

Enable a “360 degree” view of our business (customers, suppliers & partners, internal operations)

Maximize the value of our investments in inventory

Help plan product assortment, allocation, pricing andpromotions

Help optimize supply chain performance

Match internal process performance metrics tocustomer satisfaction metrics to assess the value of…

A tool to manage “exceptions” as they are happening, not after-the-fact

A tool to support more timely responsiveness todemand changes

Understand customer behaviors in order to executeour business strategy and build loyalty

Track key performance data to control our internalprocesses and compare actual performance against plan

Value of BI to Support Business Processes

Very Relevant Somewhat Relevant Little to No Relevance

2

Retail Winners tend to be more outwardly focused than their peers:

• 40% of Retail Winners find 360 degree views of the business to be very relevant vs. 15%

of all other respondents

• 69% of Retail Winners believe understanding customer behaviors to help build business

strategy is very important vs. 35% of all other respondents

• Almost half (47%) of Retail Winners believe in is very important to match their internal

performance metrics with customer satisfaction metrics to evaluate their business vs.

only one quarter (25%) of all other respondents

Clearly in an era of continued global economic uncertainty, rapid response and outwardly facing

metrics are increasingly important.

Traditional Approaches and Conventional Wisdom Now Fall Short

Retailers and economists have long used metrics like consumer confidence and the fluctuating

price of oil and other commodities as a predictor of demand. They have also used their own

products’ past performance as prelude to the future. But the Great Recession and the uncertain

economic years that followed have shown these forecasts to be unreliable for retailers at all levels

of performance1.

Similarly, conventional wisdom long held that all reductions in payroll-to-sales ratios in stores

were good reductions. However, as the web and other selling channels have become more

convenient, the lack of helpful staff in stores has become more obviously inconvenient for

shoppers who have found their voice in Social Media, and found alternatives through mobility.

RSR’s research has shown payroll-to-sales ratios are finally stabilizing2, but tools are clearly

needed to insure that in-store payroll is acting as productively and as frequently in customer-

facing roles as possible.

In the face of so much uncertainty, and with the need to respond as a single organism rather than

as a set of disparate departments, the recognition of the value of an Enterprise-wide BI strategy

has grown and more retailers are moving in the direction of putting one in place (Figure 2).

1 Twenty-first Century Merchandising Takes Hold: Benchmark Report 2011, RSR Research, August 2011 2 The 21

st Century Store: The Search for Relevance, Benchmark Report, RSR Research,

June 2011

3

Figure 2: Enterprise-wide BI : 80% are doing SOMETHING….


The value of an enterprise-wide strategy is that it insures each department is operating from the

same set of data, delivered at the same time. Delivery mechanisms can and will likely differ

depending on the physical location of the data consumer, but the data itself is consistent across

channels, geographies, departments and roles.

Guidelines Used for Describing BI in this Report

We’ve found differences in terms used by retailers and vendors when describing BI and analytics.

To set a level playing field, we make the following distinctions:

• Many people consider the terms Business Intelligence (BI) and Analytics to be

interchangeable. For our purposes in this report, we will take this route. BI churns data

and produces outputs. Those outputs are “analytics.” For our purposes, they both fall

under the topic “BI.” “Advanced” analytics offer the ability to optimize pricing, model

customer behavior, segment customers, forecast demand and more. As part of an

enterprise BI strategy, these advanced analytics should be reviewed distinctly from

reporting and are beyond the scope of this document.

• Our definition of “real-time BI” means “as real-time as it needs to be”. As we’ll see later,

in many instances, retailers are receiving information faster than they can actually use it.

In our view real-time BI delivers actionable information into the hands of decision-makers.

With these nuances explained, we’ll move on to the details of the report.

5%

15%

35%

17%

28%

Very low priority or no plans

We see the value, but it's not at the top of ourpriority list

We're working on putting one in place

We've have one in place for less than twoyears

We've had one in place for longer than twoyears

To What Extent Does Your Company Have Enterprise-wide BI Strategy in Place?

4

RSR’s Methodology and “What’s a ‘Retail Winner’ Anyway?”

RSR uses its own model, called the “BOOT,” to analyze Retail Industry issues. We build this

model with our survey instruments. Appendix A contains a full explanation of the methodology. In

a nutshell, the BOOT consists of four parts:

• Business Challenges – the external challenges a company faces.

• Opportunities – the ways the company perceives it can overcome those challenges

• Organizational Inhibitors – the internal barriers the company faces that may prevent it

from taking advantages of the opportunities it sees

• Technology Enablers – assuming a company can overcome its internal issues, the

technology tools it can use to support taking advantage of the opportunities it identifies

Defining Winners and Why They Win, and Why Laggards Fail

In our surveys, we continue to find differences in the thought processes, actions, and decisions

made by retailers who outperform their competitors and the industry at large – Retail Winners.

The BOOT model helps us better understand the behavioral and technological differences that

drive sustainable sales improvements and successful execution of brand vision.

Our definition of these Retail Winners is straightforward. We judge retailers by year-over-year

comparable store/channel sales improvements. Assuming industry average comparable store/

channel sales growth of two percent (the bar in a post-recession world is relatively low), we

define those with sales above this hurdle as “Winners,” those at this sales growth rate as

“average,” and those below this sales growth rate as “laggards” or “also-rans.” Because there

have been so many strong retail “comebacks” post-recession, we also identified those whose

comparable increases exceeded 10%. It is consistent throughout much of RSR’s research

findings that Winners don’t merely do the same things better, they tend to do different things.

They think differently. They plan differently. They respond differently.

Laggards also tend to think differently. They may have spectacular vision, but often fail on

execution. They may forget the power and breadth of choices today’s customer has. They fail to

re-invent themselves when it becomes obvious their existing business model is no longer

working. They don’t change their business processes in an effective manner, and so they either

eschew technology enablers, or don’t gain expected Return on Investment on those they DO buy.

In good times, they skate by: in tough times these weaknesses come back to haunt them.

Survey Respondent Characteristics

RSR conducted an online survey from July - October 2011 and received answers from 95

qualified retail respondents. Respondent demographics are as follows:

• Job Title:

Senior Management (CEO, CFO, COO) 23%

Vice President 32%

Director/Manager 27%

Internal Consultant 6%

Internal Staff & Other

12%

• 2010 Revenue ($ Equivalent):

Less than $249 Million 32%

$250 - $999 Million 9%

5

$1 - $5 Billion 26%

Over $5 Billion

18%

• Selling Format:

Fast Moving Consumer Goods 38%

General Merchandise and Apparel 46%

Food Service/Hospitality 16%

• Headquarters/Retail Presence:

United States 61% 67%

Canada 7% 26%

Latin America 2% 20%

Europe 11% 27%

United Kingdom 4% 21%

Asia Pacific 11% 31%

Middle East 1% 11% Africa

2% 10%

• Year-Over-Year Comparable Store Sales Growth Rates (assume average growth of 2%):

Worse than Average (Laggards) 16%

Average 19%

Better than Average (Retail Winners) 54%

More than a 10% Improvement 11%

6

Business Challenges

Can’t Get Information Fast Enough or Can’t Act on What They See

In the five years that RSR has been conducting benchmarks on the subject of BI, retailers have

consistently expressed a need to move more quickly. In 2007, this was at least somewhat

influential to more than 90% of survey respondents. This year the need for speed remains the

most frequently cited business challenge (Figure 3).

Figure 3: E ither We Can’t Get the Data or We Can’t Do Anyth ing about It


But we’ve also seen a shift this year. While just more than half of respondents are not getting

information to merchants quickly enough, just under half of respondents get the information, but

can’t act on what they receive. The organization’s ability to respond lags its ability to inform.

This is most evident when looking at Retail Winners vs. the rest of the respondent pool. Sixty

percent of average and laggard performers aren’t getting the information quickly enough, and

59% of Retail Winners are getting the information quickly, but are unable to react.

27%

60%

27%

60%

47%

33%

33%

10%

28%

31%

48%

48%

48%

59%

17%

37%

33%

52%

46%

41%

48%

Logistics managers don’t get information fast enough to minimize the impact of supply chain

problems

Can’t identify our best customers to offer special incentives to them while they are shopping

We struggle to match inventory to demand

Merchants don’t get information fast enough to react to differences between what they thought

would happen vs. what is actually happening

Marketing doesn’t know what customer sentiment is until we can see it in sales

Can’t support customer cross-channel activities very well

We can’t act quickly enough on the information we receive

Top Three Business Challenges that Create Interest in Using Near-real-time BI

All Respondents Winners All Others

7

More significant differences emerge when looking at Retailers across different revenue bands.

The largest retailers, those with annual revenue over $5 billion are caught in BOTH conundrums.

Seventy percent report their merchants don’t get information fast enough (vs. only 38% of

retailers with annual revenue less than $250 million), and 60% report that they can’t act quickly

enough on that information when they do get it. These are the most significant business

challenges they face, by a wide margin.

The smallest retailers, on the other hand, also can’t act on what they do receive (69%), but in

addition they are challenged to identify their best customers (Figure 4).

Figure 4: Smal ler Reta i lers Chal lenged to Recognize Best Customers


This is problematic, given that most small and mid-sized retailers attempt to differentiate through

knowing their customers and the products they prefer. Without a proper BI infrastructure and

tools, they may find themselves losing their most important advantage against their larger

competitors. When Amazon.com knows your customers’ preferences better than you do, a local

retailer is in serious trouble.

Delivery Mechanisms Lag

When we look at the most typical delivery vehicles used to present BI data to various

constituents, it becomes easier to understand why it’s hard to both get and react to data.

Dashboards are great tools for desk-bound C-level and Line of Business (LOB) executives and

managers, but fall short when delivered to people in the field, like store managers and

employees. And the still ubiquitous “flash sales report” typically involves poring over information,

rather than creating an instant call to action (Figure 5).

46%

60%

17%

30%

Less than $249million

$250 million - $999million

$1 Billion to $5 Billion Over $5 Billion

Identifying Best Customers as a Business Challenge (based on Annual Revenue)

8

Figure 5: Del ivery Vehicles Lag for Everyone but Consumers


Today, customers are the most likely recipients of mobile alerts across all revenue bands.

Obviously this needs to change. Store Managers and employees must be armed with up-to-date

information, and can’t be expected to sit at desks or pore over reports while customers wander

around the store, smart phones in hand.

Happily we are seeing many indications of pre-packaged mobile solutions coming from the

vendor community, and are hearing early use-case results and new pilots underway for in-store

employees. The explosion of tablets as an affordable form-factor is making this shift possible and

we expect to see a significant uptick in adoption over the coming year.

The Data Delivered Remains Somewhat Pedestrian

Just as delivery mechanisms have lagged, so have the data elements being delivered to

constituents. While it’s useful to know best and worst sellers, we also believe tools to identify

best customers as they enter the store or corporate ecommerce site should be part of the BI data

portfolio. As we can see below in Figure 6, however, the data delivered remains uninteresting.

We’d love to see more real-time information on relevant and personalized cross-sells, up-sells

and hot promotions, along with actionable information about customer complaints, but the

industry, for the most part, is lagging. We’ll investigate the reasons for this more in the section on

Organizational Inhibitors, but make note of it here.

46%

27%

19%

40%

45%

47%

50%

54%

43%

22%

21%

15%

21%

11%

17%

17%

6%

6%

5%

12%

4%

2%

6%

6%

2%

4%

4%

3%

9%

35%

0%

6%

4%

4%

2%

2%

24%

30%

27%

36%

32%

26%

26%

33%

45%

Supply Chain Managers

Supply Chain Partners

Customers

Employees

Store Managers

Line Level Managers

Designated Analysts

Line of Business Executives -Vice Presidents & Directors

C-level Executives

Most Typical Delivery Vehicles for BI Constituents

Desktop Scorecard/Dashboard Desktop Alerts Mobile Scorecard/Dashboard Mobile Alerts "Flash" Reports

9

Figure 6: Pedestr ian Data Yields Sub-optimal Results


We see no appreciable difference across revenue bands or performance level. While the industry

aspires to become more customer-friendly, it lags in delivering relevant information to those who

might help make it so.

Despite the Challenges, Opportunities Abound

Given that retailers recognize their challenges, and given the explosion of mobile delivery tools

and techniques, coupled with ever more ubiquitous “big data” hardware, we expect to see

retailers making a great leap over the coming year, In the next section we’ll identify the areas

they are most interested in exploring,

26%

26%

33%

39%

46%

46%

57%

63%

74%

Expected Receipts

Loss Prevention alerts

Customer complaints

Hot Promotions

Expected sales

Financial scorecard

Inventory exceptions (out of stock or overstock)

Performance to plan

Current sales (Best sellers/worst sellers)

Most Typical Near Real-time Information Delivered to Constituents

10

Opportunities

Pushing Reaction Time To The Front Of The Process

Most retailers share the same desire to retain customers longer, but Winners differ from others in

their thought process on achieving that objective (Figure 7).

Figure 7: Nimble On The Buy Side?


40%

29%

27%

60%

40%

47%

53%

57%

73%

73%

80%

36%

67%

80%

22%

35%

35%

35%

35%

38%

42%

50%

52%

54%

65%

67%

70%

73%

Reduced shrink

Reduce or eliminate re-work at stores or DC

Exception alerts point out the need for more training

Adjust space allocated for specific product in responseto sales spikes

Improving supply chain network management

Better match of labor to customer flows “just in time”

Rapid response to changes in consumer demand

Improved IT responsiveness & better systemperformance

Higher average transaction value

Improved merchandise productivity

Increased shopping frequency

Better reaction to supply chain shocks

Better “what if” modeling capabilities for matching demand with assortment, price, and promos at a …

Higher customer retention

Rate the following opportunities you see from real-time BI to help overcome those business challenges

(A Lot Of Opportunity)

Winners Others

11

Retailers want to be able to perform more “what if” analyses with their BI capabilities, but the

scenarios they are interested in analyzing differ. Winners are much more focused than their

lesser performing counterparts on improving their ability to react more quickly to supply chain

disruptions outside the “four walls” of the business. These disruptions can ultimately cause

consumer dissatisfaction. Non-winners put more faith in opportunities for a “better response to

changes in consumer demand”, and the ability to “adjust space allocated to a specific product in

response to sales spikes”. These opportunities are inside “the four walls” of the business, after

receipt of goods from suppliers.

It’s an important distinction. While most non-winners don’t see a lot of opportunity on the supply

chain side of their business, a majority does see opportunities for “increased shopping activity”,

“improved merchandise productivity”, and “higher average transaction value”. While these are

important, they are outcomes. As we have seen in other studies, Retail Winners take an activist

role in framing their future prospects, while laggards tend to position themselves as

victims of circumstance. For over-performing retailers, that means gaining visibility as far into

the supply chain as possible to gain the lead-time they need to alter their plans and exceed

consumer expectations.

Another opportunity area also deserves mention: over twice as many non-winners as Winners

see an opportunity to use BI to better control shrink than Winners. This again points to a historical

difference between Winners and others; they have better control of shrink to begin with – thus

there’s less of an opportunity for them as for others.

Finally, while a majority of respondents see an opportunity to use BI for improved system

performance, that choice is oddly out of place with other highly ranked opportunities.

Getting Smart In The Store

In RSR’s June 2011 report entitled The 21st

Century Store: The Search For Relevance3, we

said:

“The evolution and proliferation of consumer-held technologies have brought stores to

their Rubicon. The question retailers face is no longer, “How can we make the in-store

experience as satisfying as the web?” It has become, ‘How can we make our stores more

significant than showrooms for online merchants?’”

Theoretically, that quandary is resolved through the effective use of information, specifically by

informing store-level operational processes with actionable information derived from the

company’s BI and analytics capabilities in something approaching real-time. Consumers have

information at their fingertips nowadays that often exceeds any of the information available to

store management and personnel. If that kind of pressure weren’t enough, there’s also the

challenge of running the store at optimal productivity, having neither too much nor too little

inventory, having the right assortment at the right place and time, and having the right number of

service employees on hand to meet the demands of those hyper-informed consumers. Retailers

are seeking to eliminate the lag time to action, to achieve both the goal of servicing

knowledgeable customers better, and to run a more optimized operation.

3 The 21st Century Store: The Search for Relevance, Benchmark Report, June 2011, © 2011 RSR Research LLC

12

In an apparent response to these concerns, retailers have shifted the focus of their BI efforts to

the stores (Figure 8). Whereas only last year almost ½ of retailers who responded to our study

indicated that all channels would receive equal benefit from realizing the opportunities in BI and

analytics capabilities, this year the best value is perceived to come from improving performance

at the stores, far more than the other selling channels.

Figure 8: Gett ing Back To The Store


This response is heavily weighted to non-winners, who overwhelming chose the store as the #1

benefactor of better BI capabilities (73%). Winners have a far more balanced perspective, but

still also give most weight to the stores (44%).

What About New Demand Signals From Social Media?

In RSR’s report entitled Social Media’s Impact on Customer Engagement 4, responses from

retailers showed us that:

“Top Winners… see Social Media’s potential to create new demand signals. Of course,

messages from various Social Media, whether in the form of Facebook postings, email

messages, blog entries, or Twitter “tweets” are not data – they are sentiments expressed

in plain (or natural) language. Until recently, there were few technical ways of turning that

4 Social Media’s Impact on Customer Engagement, Benchmark Report, May 2011, © 2011 RSR Research LLC

47%

2%

0%

11%

40%

19%

10%

2%

14%

55%

All channels can take equal benefit

Mobile Commerce

Catalog/call centers

Ecommerce

Brick and Mortar stores

What Channel Can Gain the Most Benefit from Near Real Time BI?

2011 2010

13

unstructured text into something that can be transformed into true insights. But that has

changed in the last two years as technology providers have brought natural language

processing capabilities to the market… Top Winners are aware of the opportunity that

such technologies represent, and (more than other retailers) want those capabilities to

turn customer sentiment expressed in Social Media into new demand signals.”

The question for our retailers in this study was how much progress had they made towards being

able to consume and analyze new unstructured data from non-transactional systems such as

social media to optimize their value offerings? The answer is mixed (Figure 9).

Figure 9: Not Gett ing Al l The Signals - Yet


Retailers’ ability to consume un-structured information from Facebook is reflective of that

platform’s overwhelming popularity with consumers. For our retailers, no other source comes

close, even though 45% of respondents say that they can now also use signals from Twitter to

glean business intelligence. But as we’ll see later in this report, it’s not at all clear that retailers

are using such sophisticated tools as natural language processors to convert unstructured into

structured data. It’s far more likely that signals from the social media “cloud” are being translated

into something usable by external sources, such as the social media platforms themselves, in the

form of statistics. While that information is useful, it’s limited by how much the provider can or will

provide.

21%

18%

28%

45%

69%

53%

59%

69%

74%

90%

Presence on commerce portal such asAmazon.com

Location based social networks, eg. FourSquare,shopkick

YouTube

Twitter

Facebook

Value Opportunities from Social Media Networks

Potentially at Least Some Value Actually Achieved at Least Some Value

14

Organizational Inhibitors

Siloed Systems Supporting Siloed Business Units

For most retailers, siloed information contained in existing “legacy” transactional systems is by far

their biggest operational impediment to delivering new generation BI capabilities (Figure 10). In

this regard, Winners fared only slightly better than the total response group (72%).

Figure 10: Legacy


Where Winners did outshine their competition is in the second-ranked operational challenge, that

the “our operational units don’t work well together”. They are learning to work cohesively.

Twenty-five percent fewer Winners than the total response group (36% compared to 48% overall)

rated that a top operational challenge. Presumably, most Winners have addressed the

organizational challenges and varying compensation strategies that prevent line-of-business

organizations working well together.

Another important operational challenge identified by the survey respondents is that “we get

valuable insights from social media networking sites, but can’t use it for decision making”. The

response from Winners and others was consistent. Given the high potential value that retailers

30%

32%

38%

45%

48%

75%

Our IT department doesn’t get information fast enough to react to outages and other

system problems

LP Managers don’t get information fast enough to react to exceptions

We get valuable insights from social networking sites, but can’t use it for decision-

making

Our store managers don’t have the information they need to run their stores

more efficiently

Our operational units don’t work well together

Information is siloed

Identify The Top Three (3) Operational Challenges You Face That Create Interest In Using Near-real-

time BI In Your Company

15

assign to social media (Figure 9), one has to conclude that for some retailers the “signals” to be

derived from social media haven’t affected their merchandising plans yet. Social media is still in

its early days, but it’s important to look at the “other side” of that response – 62% of our

respondents didn’t choose that as a top operational challenge. Given earlier responses about the

value of information derived from social media, it’s a good bet that a plurality of retailers have

managed to eke value out of the feedback they get form consumers, however it is that they get it.

Status Quo

In RSR’s 2010 BI study, when we asked retailers specifically to identify the top three

organizational inhibitors keeping them from taking advantage of real-time BI, retailers confessed

to an inability to get data into a usable format and a lack of funds to “do the deed”.

It is somewhat surprising to see then, in Figure 11, that not much has changed, except that

retailers seem to be more acutely aware of the organizational issues that stand in the way of

delivering improved BI capabilities.

Figure 11: Frog In a Kett le?


Most startling of all is that retailers complain more that it’s hard to quantify the technology ROI for

new BI capabilities (23% more of responding retailers claim this as a “top 3” inhibitor than in

2010).

15%

17%

27%

29%

29%

34%

37%

46%

54%

12%

18%

20%

27%

20%

38%

30%

41%

46%

Poorly defined store-level processes

Entrepreneurial reactive culture makes it difficultto agree on standardized alerts and metrics

We have no idea what to do with the data we getfrom social network and customer feedback sites

Our technology infrastructure is difficult tochange and adapt

We don’t believe we can react quickly enough to the information a real-time BI system might tell us

Different “versions of the truth” – data in different operational systems that can’t easily be …

Hard to quantify technology return on investmentfor new BI capabilities

There are budgetary constraints to creatingintegrated processes and systems

The data we need has to be manually “pulled” from operational systems

Identify The Top Three Organizational Inhibitors Standing In The Way Of Taking Advantage Of The Opportunities

Identified2010 2011

16

Instead, given the challenges and opportunities that retailers have identified, the fact that the

“same old” inhibitors stand in the way of progress seems incomprehensible.

The answer to this paradox might be found in the challenges that retailers have been trying to

address in these times of mobile and hyper-informed consumers. Retailers have a lot on their

plates: channel integration, consumer and employee facing mobile capabilities, the reintegration

of the store into an “omni-channel” world, the rise of the CMO and customer-centric marketing

strategies. All of these are important, and investment in new BI capabilities is apparently taking a

back seat to them all.

Pilot Projects Gain Favor

Given that retailers continue to fret over the ROI for investments in ROI vs. the potential value to

be had from new BI capabilities, our respondents indicate an increased willingness to undertake

pilot projects to prove the value (Figure 12).

Figure 12: “Try It , You’ l l L ike It!”


18%

38%

38%

39%

41%

41%

41%

42%

55%

58%

64%

65%

51%

44%

54%

37%

44%

44%

41%

47%

40%

42%

31%

30%

31%

18%

8%

24%

15%

15%

18%

11%

5%

0%

5%

5%

Improved integration tools

Create an ROI-based business case to gain moreresources for improving BI capabilities

Bringing in outside expertise to drive internal businessprocess change

Hosted solutions (SaaS BI)

Improve our POS systems to start gathering better data

More sophisticated tools to collate the unstructureddata we gather

Wireless devices that can deliver alerts to employees inreal-time

Cheaper, faster technology

Simpler analysis tools

Improve employee training to start entering cleanerdata

Executive Mandate

Pilot programs to prove ROI business case

Rate The Value Of The Following In Overcoming The Organizational Inhibitors You Face To Implementing Capabilities To Deliver Near Real-time Information

A Lot Of Value Some Value Little Or No Value

17

While strong executive-level sponsorship of investments in BI remains a top method for

overcoming inhibitors (as it has in every prior study we’ve undertaken about BI), establishing pilot

projects to prove the ROI has risen to #1 (from #5 in our 2010 study). This rise in importance of

pilot projects is a testament to the urgency that retailers feel to get the ball rolling when it comes

to new investments in BI.

18

Technology Enablers

There’s a Lot of Plumbing Under those Dashboards

When thinking about BI and analytics, we often look from the interface first, and then think about

the underpinnings. In fact, without a robust technology infrastructure, transforming mountains of

transaction and customer data into useable metrics is almost impossible. Our retail respondents

clearly recognize this undeniable truth (Figure 13).

Figure 13: Infrastructures Matter

Source: RSR Research November 2011

While we have some doubt that 63% of respondents are currently gaining real benefits from

Natural Language Processors, we have no doubt that retailers understand the value of getting

their disparate data into a single, usable format through data transformation tools and integration

middleware. We are encouraged to see this universal appreciation of the underpinnings of BI,

especially since at least half our respondents come from the business, rather than technology

side of the retail house.

In that spirit, it’s a bit easier to understand the over-enthusiastic response to perceived value

received from Natural Language Processors. Line-of-business executives are finally trying to

learn the “language” of IT, and while they may not have a thorough understanding of the

differences between data transformation and aggregation tools, and Natural Language

transformation tools, they “get” that the plumbing is necessary to get the results they want.

We see a similar pattern when looking at perceived and actual value of various delivery

mechanisms for BI (Figure 14).

63%

80%

97%

97%

100%

100%

Natural language processors, to convert unstructured data (e-mails, text, “tweets”, etc.)

into structured data

Integration “middleware” between operational systems

Data transformation & aggregation tools (to help enable normalization of disparate

transactional data formats into “one version of the truth”

Value Opportunities from Infrastructure Tools

Potentially at Least Some Value Actually Received at Least Some Value

19

Figure 14: Del ivery Mechanisms al l Sound Real ly Appeal ing…


The enthusiasm among all respondents is palpable. The iPad and iPhone have provided an

epiphany for many retailers, with notable massive purchases at mega-retailers like Lowes (34,000

iPhones ordered for employees in 2011), and Nordstrom (purchasing iPads for sales associates

to be used for both mobile check-out and clienteling). Perhaps the most interesting data point in

Figure 14 revolves around the value and usage of corporate-wide email. Only here has actual

value lived up to its potential. In fact, the world of email has matured to a point of diminishing

returns. Retailers are far more enthusiastic at the prospect of instant messaging when necessary

through either corporate or employee owned devices than perpetuating the verbose mélange of

emails that every executive pores through on a daily (or hourly) basis.

Our only caveat here is retailers’ propensity to drown themselves with information. A barrage of

instant messages can prove to be as unnerving and counterproductive as a bulging in-box.

Discipline is still needed, or new tools will turn out to be as confusing as their predecessors.

Beyond the Excitement and Promise, What’s the Reality Today?

We have no doubt that plumbing is being put into place, and we also are quite certain that

retailers are excited at the prospect of bringing consumer-grade usability into the enterprise.

After all, there are very few user manuals sent along with new “apps” for mobile phones and

tablets – why do we need training and classes in the use of our enterprise applications? Beyond

the promise, what’s actually in use today? As we can see in Figure 15, actual delivery

mechanisms are quite different than the picture painted above.

47%

54%

34%

76%

70%

73%

75%

70%

87%

71%

71%

92%

94%

98%

Integrated voice/data network at the store level

Instant messaging via the internal network

Employee owned “smart” mobile devices

Corporate-wide Email

Commercial / pre-integrated application suite

Store Manager or Employee “portals”

Company-owned “smart” mobile devices (Phones, iPad, etc.)

Value Opportunities from Different Delivery Mechanisms

Potentially at Least Some Value Actually Received at Least Some Value

20

Figure 15: …but Real i ty Lags Behind


While desktop scorecards and dashboards have clearly become more ubiquitous, a somewhat

stunning percentage of C-level executives, store managers and other retail executives are still

predominantly getting their analytics through “Flash” reports. Of course, in today’s real-time

world, even the name “flash reports” is a bit of a misnomer, left over from a time when they really

just referred to unaudited sales data being given to users.

The only constituent that seems to be getting the results of BI delivered to them on mobile

devices is the consumer. Thirty-five percent of respondents do deliver information to consumers

on mobile devices. We’re not convinced that this information is all analytical in nature, but

certainly it has been scrubbed for relevancy. In fact, some might argue that some of the data

being delivered to consumers, based on computer cookie analysis shifts from relevant to

“creepy”. It’s disconcerting for a consumer who has been browsing for shoes on one site to find

ads for shoes showing up as sidebar ads on their Facebook pages. Yes business intelligence

was used, yes the information was personalized, but it is not necessarily desirable. This delicate

line between relevance and intrusion will be explored extensively over the coming years.

46%

27%

19%

40%

45%

47%

50%

54%

43%

22%

21%

15%

21%

11%

17%

17%

6%

6%

5%

12%

4%

2%

6%

6%

2%

4%

4%

3%

9%

35%

0%

6%

4%

4%

2%

2%

24%

30%

27%

36%

32%

26%

26%

33%

45%

Supply Chain Managers

Supply Chain Partners

Customers

Employees

Store Managers

Line Level Managers

Designated Analysts

Line of Business Executives -Vice Presidents & Directors

C-level Executives

Most Typical Delivery Vehicles for BI Constituents

Desktop Scorecard/Dashboard Desktop Alerts Mobile Scorecard/Dashboard Mobile Alerts "Flash" Reports

21

BOOTstrap Recommendations

We’re really encouraged to see retailers’ enthusiasm for new tools and delivery mechanisms for

BI and analytics – especially given the business-base of most of our respondents. We believe

retailers can leverage that enthusiasm and create new applications to provide digestible

information to the people who need it – on retailing’s front lines. Towards that end, we present

three recommendations.

1. Get an Enterprise-wide BI Strategy in Place

The successful enterprise-wide BI strategy will have several critical components:

• Infrastructure: Hardware is now available to support “Big Data”. Build the integration

bridges from operational systems directly to the data warehouse.

• Executive Involvement: From the responses we’ve received to our BI survey, we

believe Line of Business users are ready and willing to become engaged. They’ll even

talk about infrastructure issues, since they recognize the importance of overcoming them.

• A Roadmap: An enterprise-wide BI strategy should include a step-wise approach to

adding incremental value with BI and its associated outputs. Think about appropriate

hardware platforms, data transformation tools and techniques, and layering in reporting,

alerts, and finally advanced analytics that are retail-specific solutions.

• A Wireless Plan for Stores: Even the best insights will lose value if they’re not

delivered in a timely fashion to the people that need them in the field. The time is NOW

to put a wireless infrastructure in place. Customers can use 3G and 4G to educate

themselves. Retailers will need the wireless infrastructure for store managers and

employees. Letting customers “hop on the bus” will just be a plus.

• Modern Delivery vehicles: The days of desktop dashboards and flash reports are

drawing to an end. “Consumer grade usability” has become the order of the day. No one

gets a user manual with consumer apps. BI can be equally as simple. Plan for simplicity

as an output of back-office complexity.

2. Prioritize those Who Need Real-time Information Most

Scorecards are useful after the fact, but real-time exception alerts are most valuable to those on

the front lines: in call centers, stores and distribution centers. Giving information to those who can

actually do something with it is critical.

3. Temper Enthusiasm with Appreciation for Complexity of the Task

The consumerization of IT has given the non-technical user a real appreciation for the value of

technology tools. However, expectations may sometimes outstrip reality. There are no magic

bullets in successful retailing. Insights delivered in a timely fashion will foster success, but it will

take some time to build those insights. Brand building with words and pictures is relatively easy

compared to the collation and synthesis of mountains of data into actionable information. While

technology development cycles are faster than they used to be, populating apps with high-

powered data will take some time.

We live in very exciting times. The fact that half our respondents can deliver information faster

than their organizations can respond to it is actually a huge leap forward. Business Intelligence

and analytics will support the return to holistic retailing the RSR has been recommending for

several years. Holistic retailing in the 21st century is channel-aware but non-prejudicial (store,

22

mobile, on-line…all are equally important and synergistic), collaborative rather than siloed, and

forward, rather than backward looking, and customer, rather than product-centric.

a

Appendix A: RSR’s Research Methodology

The “BOOT” methodology is designed to reveal and prioritize the following:

• Business Challenges – Retailers of all shapes and sizes face significant external challenges. These issues provide a business context for the subject being discussed and drive decision-making across the enterprise.

• Opportunities – Every challenge brings with it a set of opportunities, or ways to change and overcome that challenge. The ways retailers turn business challenges into opportunities often define the difference between Winners and “also-rans.” Within the BOOT, we can also identify opportunities missed – and describe leading edge models we believe drive success.

• Organizational Inhibitors – Even as enterprises find opportunities to overcome their external challenges, they may find internal organizational inhibitors that keep them from executing on their vision. Opportunities can be found to overcome these inhibitors as well. Winning Retailers understand their organizational inhibitors and find creative, effective ways to overcome them.

• Technology Enablers – If a company can overcome its organizational inhibitors it

can use technology as an enabler to take advantage of the opportunities it identifies.

Retail Winners are most adept at judiciously and effectively using these enablers,

often far earlier than their peers.

A graphical depiction of the BOOT follows:

b

Appendix B: About Our Sponsors

Netezza, an IBM Company, is the global leader in data warehouse and analytic appliances that

dramatically simplify high-performance analytics across an extended enterprise. Netezza’s

technology processes enormous amounts of data at exceptional speed, providing a significant

competitive and operational advantage to retailers worldwide including Catalina Marketing, Guitar

Center, Michaels, Neiman Marcus, Nielsen, Ross Stores and Yum! Brands.

With SAS’s 35 years of advanced analytics and retail domain expertise, retailers choose SAS to

drive better business results. SAS provides winning retailers with solutions for retail merchandise

planning, size optimization, localized assortment optimization, allocation, space planning and

optimization, price optimization, customer insight, social media analytics, campaign management

and advanced forecasting across the enterprise. SAS provide flexible deployment models, and

SAS retail intelligence is ramped up at your pace. Retailers turn and return to SAS because SAS

drives better results.

For further information, visit http://www.sas.com/retail/

c

Supporting Sponsors

By enabling more content, mobility and capabilities than ever before, Intel gives you the

advantage in a rapidly changing world. With advanced silicon, industry standard platforms,

modular infrastructure solutions and ecosystem support, Intel can help you deliver a more

compelling digital lifestyle. Intel, the world leader in silicon innovation, develops technologies,

products and initiatives to continually advance how people work and live. Additional information

about Intel is available at www.intel.com/go/ic.

Manthan Systems produces cutting edge analytic solutions for global retailers. Manthan's breakthrough solutions, under the brand name ARC, transform the way retailers use analytics driven decision making for strategic advantage. The ARC product portfolio spans the entire spectrum of retail decision making with role-based, pre-built applications, and includes products for merchandising analytics, financial analytics, customer centric analytics, supplier portal and analytics. These award winning products provide a significant edge to an organization’s analytical capability and maturity, and are proven to deliver unmatched business benefits in a remarkably short timeframe. Manthan’s experience spans a wide range of retail segments and formats, having transformed decision making for over 50 leading Retailers in 16 countries. For more information visit www.manthansystems.com.

For more than 35 years, RedPrairie’s best-of-breed supply chain, workforce, and all-channel retail

solutions have put commerce in motion for the world’s leading companies. Installed in over

60,000 customer sites across more than 50 countries, RedPrairie solutions adapt to help ensure

visibility and collaboration between manufacturers, distributors, retailers, and consumers.

RedPrairie is prepared to meet its customers’ current and future demands with multiple delivery

options, flexible architecture, and 24/7 technical and customer support. For a world in motion,

RedPrairie is commerce in motionTM

.

To learn more about how RedPrairie solutions can optimize your inventory, improve employee

productivity, or increase sales, visit RedPrairie.com or email [email protected].

d

Appendix C: About RSR Research

Retail Systems Research (“RSR”) is the only research company run by retailers for the retail

industry. RSR provides insight into business and technology challenges facing the extended retail

industry, providing thought leadership and advice on navigating these challenges for specific

companies and the industry at large. We do this by:

• Identifying information that helps retailers and their trading partners to build more

efficient and profitable businesses;

• Identifying industry issues that solutions providers must address to be relevant in the

extended retail industry;

• Providing insight and analysis about a broad spectrum of issues and trends in the

Extended Retail Industry.

Copyright© 2011 by Retail Systems Research LLC • All rights reserved.

No part of the contents of this document may be reproduced or transmitted in any form or by any means without the permission of the publisher. Contact [email protected] for more information.

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