2014 Big Data in Retail
Study
Table of Contents
Goals of the Study ___________________________________________________________ 3
Summary of Results __________________________________________________________ 3
Study Participants ___________________________________________________________ 3
Retailers’ Biggest Obstacles to Success with Analytics _______________________________ 4
Retail Functions with the Most to Gain from Big Data _______________________________ 5
Big Data’s Impact on Retail Processes ____________________________________________ 6
Why Retailers are Holding Out on Big Data _______________________________________ 7
Benefits of Sharing Retail Data with Suppliers _____________________________________ 8
Improving On-Shelf Availability with Big Data _____________________________________ 9
Why Testing is Underutilized in Retail Decision-Making ____________________________ 10
Big Data as a Requirement for Staying Competitive________________________________ 11
The Urgency of Big Data Initiatives _____________________________________________ 12
About the Big Data in Retail Study _____________________________________________ 13
About 1010data ____________________________________________________________ 13
Goals of the Study
The Big Data in Retail Study aims to understand the state of adoption of Big Data in the retail industry, as well as how retailers envision Big Data helping to overcome some of retailers’ top business challenges. Highlights of the study include:
• A deeper view into what prevents retailers from capitalizing on the opportunities of Big Data • Insight into the business processes and functions that stand to benefit most from Big Data
• A look into some of the areas of business need– such as on-shelf availability, supplier collaboration, and testing of new innovations – where Big Data can help deliver business performance
improvements
• Data on how rapidly leading retailers are adopting Big Data solutions, and the time horizon in which retailers are expected to leverage Big data as a competitive advantage
Summary of Results
The 2014 Big Data in Retail Study illustrates that retailers continue to face challenges in delivering the
reporting business users need to enable data-driven decision-making, but are optimistic about the opportunity for Big Data technologies to provide breakthroughs in analysis capabilities across a number of different retail processes. Before moving forward on Big Data initiatives, however, retailers seek a clearer understanding of the potential ROI, especially given the perceived high cost of systems and resources required to implement Big Data solutions. Executives see opportunity for Big Data to assist with perennial retail challenges including supplier collaboration, on-shelf availability, and the testing and rollout of new innovations. Most respondents believe that Big Data is either already delivering a competitive advantage for leading retailers, or will be doing so in the next one to five years.
Study Participants
The Big Data in Retail Study is based on interviews with 201 U.S. executives across a range of retail sub-segments including grocery, drug, specialty, discount, department store, restaurant, hospitality and more. Respondents represent nearly every department across the retail enterprise from businesses of all sizes, including more than 50 respondents from retailers with annual revenues greater than $1B.
Retailers’ Biggest Obstacles to Success with Analytics
Executives were asked about their biggest obstacles to getting the reporting and analytics they need to make better data-driven business decisions. The need for a ‘single version of the truth’ topped the list (41%), followed by the inability to analyze data at a low enough level of detail (38%) and difficulty accessing and integrating enterprise / 3rd-party data users want to analyze (34%). Less cited, but still significant challenges included slow query speeds (16%), incumbent reporting tools that struggle to handle the sophistication of retailers’ analytical questions (15%), and the lack of self-service reporting (13%).
Retailers’ Biggest Obstacles to Analytics Success
Figure 1. Responses to the question “What are retailers’ biggest obstacles to getting the reporting and analytics business users need to make better data-driven business decisions?”
Retail Functions with the Most to Gain from Big Data
Various functional departments across the retail enterprise have the potential to reap benefits from Big Data. When asked which departments stand to gain the most, responses were varied but a few clear winners emerged with merchandising (53%) and marketing (48%) coming out ahead of all others. Store Operations (42%) and E-Commerce (42%) followed closely, with Supply Chain (27%), Finance (23%) and Loss Prevention (21%) also recognized as having potential to benefit from Big Data.
Retail Business Teams that can Best Leverage Big Data
Figure 2. Responses to the question “Which functions in the retail enterprise stand to make the best use of insights from big data discovery?”
Big Data’s Impact on Retail Processes
The study then asked participants to drill into which specific retail processes could be most impacted by Big Data technology. Respondents felt that Big Data could most impact the design of targeted offers and
promotions (50%), followed by forecasting and supply chain modeling (49%), customer-centric merchandising (43%), and loyalty program management (35%). The retailers interviewed also noted that Big Data analytics can deliver benefit in the areas of workforce management (28%), loss prevention processes (16%), and store design (18%). A small portion of respondents (5%) felt that Big Data analytics would not have an impact on retail business processes.
Processes that can Benefit Most from Big Data Technology
Figure 3. Responses to the question “On which of these retail business processes do you think Big Data technology can have the greatest impact?”
Why Retailers are Holding Out on Big Data
While executives see the potential of Big Data to make an impact across a range of retailers’ departmental functions and business processes, they also acknowledge that retailers have a number of reasons for holding back on using Big Data technologies to leverage large and complex data sets. The two most popular reasons for holding back were the need for retailers to better understand how Big Data can help solve their business problems (46%) and that the cost and complexity of implementing Big Data solutions needs to come down (42%). Survey respondents also indicated that the need for Big Data solutions that are intuitive for business users (30%) and retailers’ current struggles with basic business reporting (22%) are significant factors in some retailers’ hesitancy to adopt Big Data solutions. A number of respondents (7%) indicated that they don’t perceive retailers as holding out at all on leveraging Big Data.
Obstacles Preventing Retailers from using Big Data
Benefits of Sharing Retail Data with Suppliers
Next, the study shifted gears, asking executives about some of the specific retail analytical applications enabled by Big Data technology, and how those could benefit retailers. The first area of focus was the sharing of data and analytics between retailer and supplier. When asked about the benefits of data sharing,
respondents indicated that the top benefits include enabling suppliers to better forecast and meet consumer demand (67%), allowing retailers to leverage suppliers’ category and product knowledge to improve their merchandising strategies (52%), helping retailers to strengthen partnerships with suppliers (52%), and helping retailers increase sales (41%).
Benefits of Sharing Data with Suppliers
Figure 5. Responses to “What, if any, do you think are the benefits of retailers sharing data (such as POS, inventory, and customer loyalty) with suppliers?”
Improving On-Shelf Availability with Big Data
On-shelf availability represents an $800 Billion+ problem for retailers worldwide. When executives were asked how Big Data can help with on-shelf availability, they highlighted Big Data’s ability to reduce out-of-stocks that lead to lost sales (66%), predict future demand and inform supply chain decisions (50%), reduce overstocks that negatively impact turns (47%), tune product assortments to store and channel-level demand (41%), and help enable alternative fulfillment means like ship-to-store and ship-from-store (29%).
How Big Data Can Improve On-Shelf Availability
Figure 6. Responses to “How can Big Data help retailers do a better job of managing product availability for consumers?”
Why Testing is Underutilized in Retail Decision-Making
Retailers have long indicated they struggle to make controlled testing of new innovations and initiatives part of their standard decision-making processes. The Big Data in Retail Study sought to discover why. When asked why testing is underutilized by retailers, executives indicated that retailers’ resources are stretched too thin to dedicate time to testing (45%), that they need better tools to create and analyze tests (43%), that tests are too cumbersome and costly to execute (38%), and that gathering and organizing the various disparate data sources for test results is too difficult (18%).The Challenges of Testing New Innovations
Figure 7. Responses to “Why don’t retailers conduct more tests prior to introducing a new product assortment, promotion, store format, or other new initiative?”
Big Data as a Requirement for Staying Competitive
To sum up the research, respondents were asked about the overall importance of Big Data initiatives within retail, and what the level of urgency is for retailers to get their Big Data initiatives underway. When asked what the overall importance of Big Data is to a retail chain’s ongoing competitiveness, most of the executives
surveyed categorized Big Data initiatives as “important” (38%), followed by “very important” (35%), or “moderately important” (23%), with just 4% stating that Big Data initiatives are of little importance or unimportant.
Big Data’s Importance to Staying Competitive
Figure 8. Responses to “How important do you think using Big Data is, if at all, for retailers to stay competitive?”
The Urgency of Big Data Initiatives
With 92% of the surveyed executives agreeing that Big Data initiatives are important to helping retailers stay competitive, the research sought to understand the level of urgency with which retailers are approaching Big Data initiatives, and how soon retailers believe that leaders in their industry will have capitalized on Big Data to deliver a meaningful competitive advantage. A large number of respondents (18%) believe that leading
retailers have, in fact, already capitalized on Big Data to deliver a competitive advantage. A significant number of respondents (15%) believe that retailers will realize the benefits of Big Data during 2014. The majority of all respondents (62%) believe the benefits will be realized within the next five years, with the remaining (4%) predicting that the competitive benefits of Big Data will be realized in the next ten years and beyond.
When Leading Retailers will Leverage Big Data for a Competitive Advantage
Figure 9. Responses to “When do you believe leading retailers will capitalize on Big Data to deliver a competitive advantage?”
About the Big Data in Retail Study
The 2014 Big Data in Retail Study was commissioned by 1010data and fielded by uSamp. uSamp’s online market research panel consists of 12 million highly responsive and diverse panelists worldwide, with 12,000 new registrants per day, including mobile survey panelists.
About 1010data
1010data provides a unique, cloud-based platform for big data discovery and data sharing. It is used by
hundreds of the world's largest retail, manufacturing, telecom, and financial services enterprises because of its proven ability to deliver actionable insight from very large amounts of data more quickly, easily, and
inexpensively than any other solution.
