Retailers faced unprecedented adversity the past few years and, in the process, learned much about their strengths and weaknesses. Some fared better than others but all learned from the experience of managing through pandemic disruption, supply chain challenges and erratic shopper behaviors.
One of the biggest learnings was that traditional category management processes are broken. That may sound harsh, but if we are being honest is there really any disagreement on the point that retailers’ legacy assortment and space planning systems were no match for the dynamic demand environment of the past two years? Or even the years prior? Demand had become increasingly dynamic prior to the pandemic thanks to growth of digitally engaged shoppers, the popularity of e-commerce and an acceleration in how quickly new products or trends could emerge and decline. The pandemic simply exposed shortcomings of legacy approaches.
Category Management Tough Love
Fixing a problem requires acknowledging it exists and that is the spot in which many retailers find themselves. Keeping pace with shoppers, or even following them closely, has never been more difficult, elevating the need for insights. A red-hot influencer with serious Tik Tok skills can cause sales of an obscure product to surge, quickly leading to on shelf availability issues. The same is true of headline-driven pantry loading or product trends which gain momentum fast but can fall out of favor just as quickly. Then there is the prevalence of local items in product assortments, a key element of many retailers’ merchandising strategy
This is just a sampling of the complexities that now exist and have put retailers behind the shopper-driven pace of change. This pace of change combined with the abundance of variables that impact demand and the external competitive environment means one thing for retailers. They must make a break from tradition and the processes and technologies of the past to think differently about category management overall and what will be needed to win in the future.
The Continuous Reset and Category Planning
When category management emerged in the early 90’s it was a big deal. It changed how retailers ran their businesses as data volumes increased, supplier collaboration became a thing, and shopper insights were being used more effectively to inform decisions about entire categories. Despite all the changes in the industry, the definition of category management used by the U.S.-based Category Management Association (CMA) sounds familiar. CMA describes category management as, “the process by which retailers and manufacturers develop a comprehensive plan based on facts, insights, sound strategies, and proven tactical success models to meet shopper needs in a superior manner thereby producing superior business results.”
That’s a workable definition, but at Symphony RetailAI we think the phrase category planning is also important. It is a way to think more broadly about category management and is reflective of current marketplace realities and future possibilities. Category planning is about looking ahead to how retailers will need to leverage technology to operate effectively in the dynamic demand era.
Dynamic Demand Meets Its Match
It stands to reason that if demand is dynamic then planning and execution processes must be as well. Retailers need to fight fire with fire, a process that begins with an understanding of where an organization is at in terms of technological capabilities, but also its willingness to embrace new ways of working. To aid in that process, Symphony RetailAI’s Chief Product Officer Cheryl Sullivan developed a proprietary “maturity model” that allows retailers to put themselves in groupings based on their capabilities and process. Think of it as a self-assessment tool.
For example, on one end there is a grouping that relies on historical approaches such as the manual creation of assortments and planograms via desktop tools. From there, other organizations may use more modern tools, but processes haven’t changed much so there remains a reliance on calendar-based category resets. Moving further along the maturity model we begin to see retailers who make greater use of cloud-based AI solutions but persist in their reliance on infrequent calendar-based resets and are lacking in store-level insights.
Eventually, more advanced retailers move into usage of solutions such as shelf intelligence that offer predictive analytics and recommended actions, helping to close the loop between insights and execution. Ultimately, retailers reach a desirable end state on the maturity model where the prescriptive powers of AI are leveraged, and they have broken free from calendar constraints to engage in near real-time dynamic planning and execution. Thus, the challenge of dynamic demand is countered by dynamic category planning processes that don’t adhere to predetermined schedules that are reflective of real-world shopper behavior.
Retailers aren’t there yet, but the tools exist for all types of organizations to advance from wherever their starting point is on the maturity model. In the end, if consumer demand is dynamic, and growing more so every day, then category planning processes should be equally dynamic.
(To learn more about dynamic demand, category planning and the new maturity model, join Cheryl Sullivan, Chief Product Office and General Manager, Retail & CPG, and RSR Research Managing Partner Brian Kilcourse for a May 31 webinar with The Grocer.)
Want to learn more about dynamic demand and the insights to execution vision of category planning? Speak with one of our solutions experts today.