Written by Kurt Kendall, Steven Pinder and Tom White for Chain Store Age
Retailers are being squeezed by growing consumer individualism, globalization and evolving preferences. These pan-industry pressure points are causing a proliferation of SKUs that retailers must now nimbly administer. And with online competition eating into already-low margins, the challenge for brick-and-mortar retailers is clear: Find a better way to manage assortment practices.
To do so, retailers should focus on localization and efficiency in assortment planning, which will improve customer-centricity at the same time customer bases are diversifying.
Given the breadth of relevant factors, designing and implementing an assortment optimization program requires a comprehensive approach. Yet many retailers still rely on outmoded spreadsheets to aggregate and analyze data, and they lack company-wide best practices for data management. Assortment optimization cannot be brought to life within such a desultory system, nor can spreadsheets handle the growing consumer complexity. However, by following a few tried-and-true methods, retailers can improve their back-end assortment practices to synthesize and analyze customer intelligence and make more strategic decisions.
Four Steps to Operationalizing Localized Assortment Planning
Optimized local assortment planning requires aggregating data from multiple sources into a single set of systems; developing logical rules and goals to support the overall assortment strategy; regularly reviewing sales data and trends to iteratively build assortments; and sharing this information across the enterprise to facilitate execution. Current methodologies often shortchange the science behind assortment planning, leaving retailers reliant on gut reactions—or on vendors pursuing different metrics and agendas. By adopting enhanced localized assortment planning concepts, retailers can gather and apply data that helps determine which SKUs to add and which to eliminate.
Consider the recent boom in yogurt: Category managers had to pick which brands, styles and flavors to add and, therefore, remove. If customers don’t remember what was on the shelf before Chobani 2% Coconut, the category manager made a good decision. Without the right performance data, category managers could easily alienate customers by switching out the wrong product.
To identify and capitalize on data-driven assortment opportunities, retailers must:
1) Identify the strategic “who”
To stand out, retailers must first determine whom they serve, their value proposition for that customer and how to measure success. Only after defining this customer base can retailers determine what to put on the shelf.
Factors informing the “who” have grown tremendously as part of the great data explosion. For example, psychographic and demographic analyses are recent additions to what defines a target consumer base. If analysis recommends pursuing customers who adhere to a healthy lifestyle, this may mean swapping out double fudge chocolate ice cream with a low-fat alternative. In another example, rural customers may prefer lower-cost, private-label brands. Operationalized assortment planning depends on such customer insights.
2) Break down operational silos
Many retailers possess a treasure trove of customer insight, but it’s too often siloed within departments. Gathering data from the marketing department can help a retailer understand buying patterns and common item combinations. Insights from the Web analytics team can provide an understanding of what items consumers search for, items they consider instead and which products receive minimal attention. Knowing how to effectively partner with vendors and share data is essential to unlocking cross-banner insights. Such insights enable improved customer-centricity by providing the right product offerings at the right time and by better coordinating promotional efforts within the assortment.
3) Invest in your team
Overseeing data-driven assortment practices requires a complex combination of skills, which may necessitate creating new positions or revamping old ones. It’s not enough to generate a 100-page sales report week after week. Instead, those driving assortment optimization planning must have the analytical skills to aggregate, analyze and draw actionable conclusions from big data. They must know how to manage details as well as drive a larger strategy. Relationship and negotiating skills are also necessary to achieve recommendation buy-in and to liaise with vendors and other businesses.
Many retailers will be hard-pressed to find internal personnel with this hybrid combination of skills. Initially, they will likely need to seek outside talent to fill these specialized roles. As the positions become established, retailers can develop internal talent. Finding the right balance is key but, in all cases, investment in personnel is critical.
4) Pilot your program
Once the new way of operating has been defined, consider piloting a data-driven assortment program in select stores. Choosing stores that serve myriad demographics can help ensure your program captures each customer base’s unique needs. This pilot process facilitates change management, as it lets a retailer establish what works and what doesn’t prior to developing an end-state solution. They can see and apply the recommendations they drew from the aggregated data, as well as tweak inputs, outputs and staffing, within a controlled environment. Retailers will also benefit from live user input and being able to test the assumptions expected to drive the benefits. Upon the pilot’s completion, initial savings or new revenue can be applied to future program buildout.
Assortment Optimization Challenges
One of the greatest challenges in operationalizing assortment planning can be balancing art (or gut instinct) and science. Take, for example, the case of the Korean ice pops recently introduced at a Vancouver grocery store. Despite intuition pointing to the contrary, the category manager trusted the numbers recommending the unknown product, and they soon became a bestseller.
Too much emphasis on data, however, can ruin the art of assortment planning. If implemented correctly, improved assortment practices will soon produce a host of top sellers: Resist the urge to chase these results with rapid, sweeping changes. Instead, believe in your data’s longevity and implement gradual changes to protect margins and the customer’s experience.
No data can replace the human element of merchandising an assortment. Balance data-driven recommendations with intuitive experience to achieve the benefits of enhanced assortment practices. By combining a small, healthy dose of data-skepticism with a clearly defined strategy and process, retailers can improve their assortment practices to achieve better margins, increase sales and ultimately lead the market.
13 October 2014