The consumer goods industry has been working with their retail partners for decades to maximize their store shelf exposure in order to drive increased sales. More recently, some CPG companies and major retailers have collaborated to tailor local store assortments to match local demographics and buying patterns and have seen significant sales uplift as a result.
What has been the impact of these efforts and how does the advent of “Big Data” change the equation? To explore these questions, I reviewed a recently published paper by Gordon Wade, Managing Partner and Director of Best Practices for the Category Management Association.
The paper, titled, “Category Management Mastery: The Key to Growth!” purports that category management is the key to addressing what the author sees as the three major trends in the marketplace today:
- The ever-increasing power of retailers
- The digital empowerment of shoppers
- The emergence of Big Data
Wade’s premise is that category management is at the heart of leveraging these three trends through a combination of advanced category management technology, better training of category management professionals, and sophisticated analytics to leverage Big Data. While acknowledging that ongoing training of human capital is always important, I would like to discuss the technology and analytics issues and add some flavor to the topics beyond what the author covered.
Localized Assortments – Blessing or Curse?
A major underlying theme throughout the CMA paper is that the move to localized store assortments has been both a blessing and a curse. It’s a blessing for CPG companies and retailers who can better match product placement to local demand, thus increasing sales while reducing slow-moving inventory, spoilage and markdowns. However, for category managers and supply chain professionals, it’s a curse because it adds so much more work and complexity to their jobs.
In the paper, Wade makes it clear that category management technology is a requirement to address both the blessing and the curse. He states that “having the right software is critical” and graciously adds that “the software from companies like JDA is a Godsend.” We appreciate the mention, but you have to dig a bit deeper to understand how category management and assortment optimization software can address these issues.
Four Step Category Management
The problem with localized assortments is the sheer volume of planograms involved. Wade cites an example of Dr Pepper having over 5,000 store beverage planograms for its retail customers. Similarly, one of our CPG customers was challenged to meet the store-specific planogram requirements of one of its major retail partners. The category managers’ role shifted from strategic planning and collaboration to very tactical hands-on work developing planograms. In the long term, will this be as productive as their strategic efforts? Our planogram management technology now generates thousands of planograms for this customer in just a few hours instead of tying up valuable category management resources for three to five weeks.
To effectively handle localized assortments and become category leaders, CPG companies must help their retail partners maximize revenue potential per square foot. There are four steps required to accomplish this.
First, merchandise assortments must be optimized by store or store cluster to reflect local demographics and shopping patterns. The assortment optimization software must be smart enough to take into consideration the space available within each store. These space-aware assortment plans feed planogram development systems so the two are always in sync.
Second, intelligent floor plans are developed based on store dimensions, flow patterns, fixtures and local assortment plans to help position merchandise within the footprint, end-caps or special displays. This maximizes exposure of the right product mix based on local preferences and merchandising plans.
Third, using the assortment and floor plans, space planning applications can create store-level planograms that optimize merchandise space allocation within the fixtures and facings based on local demand. There are even 3D virtualization tools available to display and direct this process visually.
The fourth step is one often overlooked by category managers – getting the assortments stocked on store shelves. Without the connection to the in-store human resources to execute the planogram and keep merchandise stocked on store shelves, the best assortment plans will have little impact. Therefore, store-level workforce management systems with detailed task management capabilities are required to direct store associates to set planogram assortments and keep them stocked.
The benefit of this four step methodology for category management is a more holistic approach to matching assortments and space planning with local customer demand to maximize sales potential at each store. Using category management, assortment optimization and workforce management software makes this store-level planning and execution possible without over-burdening your category management team. Our customer experience suggests that transitioning into localized assortments and executing store-level planograms has produced three to five percent growth in sales. Think about what this type of sales growth would mean for your company.
Advanced Planning and Analytics
The four step process for category management will not be effective without solid data and science behind the analysis. Advanced planning and analytics systems are needed to gather relevant information from diverse sources and synthesize it into meaningful input for the category management and assortment systems. Store-level POS data and loyalty program information must be combined with customer feedback to define demand at the local level. Intelligent clustering analysis can be performed to discern preference patterns by geographic area.
What’s new in this process is the availability of Big Data and inline analytics. The digital empowerment of shoppers has brought a wealth of new insights into shopping behavior through digital transactions and social media. This unstructured data must be systematically gathered and analyzed to decipher shopper trends and preferences that can be used to better understand channel and local demand at the household level. Inline analytics can combine these insights with traditional demand data to formulate much more meaningful input to forecasting and planning systems. This enables much more precise targeting of merchandise plans and assortments by channel and store.
In the following video interview, I outline what the new age of category management means, what’s driving this change and how manufacturers can leverage consumer insight and data to build more targeted assortment strategies and a localized shelf execution plan to drive sales growth and profitability. If this topic interests you, you might also want to read an article I recently wrote titled New Age of Category Management, published in JDA’s Real Results Magazine.