THE PROFIT LAB // Top 10 Ways to Pull Profit from Allocation

Strategy #6: Update plans with changes in customer demand as frequently as possible

There’s no disputing that having a good plan is important in retail. In the context of allocation within retail – especially fashion retail – it’s common to see adetailed plan as the driver of allocation execution. The philosophy is sound: invest in creating a solid plan that you can simply execute to. Unfortunately few tools enable users to manage detailed plans with the appropriate metrics and frequency to keep up with changes in demand.

In the last two or three years the pace of change in customer behavior has increased dramatically. Over this time the use of last year data has not been a valid indicator of trends, especially when servicing individual stores. Customers are changing their buying patterns regularly and in many cases the entire demographic makeup of shoppers in stores has shifted. The only way to keep up with these variations is more frequent updates to our understanding of customer behavior.

Traditional store planning approaches are not suited to being updated as frequently as needed to keep up with these changes. This is especially true when we are updating detail level plans to drive allocation. Allocating to an outdated plan that doesn’t reflect what demand will be is not of much help when striving to achieve strategic company objectives such as increasing volume, turns or profitability.

The underlying objective of these plans is often to ensure a presentation or image is maintained or to set a capacity ceiling in given locations. This process can often be shifted to (and is often better served in) assortment planning processes. When that objective is accommodated, the remainder of allocation execution must be more responsive than a static, manually managed store plan can be. What can you do to understand and respond to the rapid changes in customer behavior?

What you can do now

The simple answer is to update your store plans more frequently. Much more easily said than done (if feasible at all) within resource and time constraints.

Another option to consider is to change the role of your store plans. If you can limit them to becoming vehicles to define only higher level image, presentation and/or capacity requirements by driving min and/or max parameters, you then may be able to free up your allocation system to interpret the trends within recent activity and weigh them more heavily into the final allocation decision. This is true for both initial allocations as well as in season allocations. It may even be possible to shift the responsibility of defining these parameters into other, existing planning activities such as assortment planning. If that happens, you can free up valuable time to do more analysis and determine superior allocation criteria. While you may still be limited in how reactive you can be, this can enable you to continue supporting brand or lifestyle images while increasing your ability to be more responsive to the constantly changing trends of individual stores and products.

What you should consider when looking for new capabilities

The objectives of maintaining an image while still being responsive to unique store/product demand can often be difficult to balance. Technology has come a long way over the last 5 or so years in its ability to apply more intelligence to defining and solving these problems.

Look for the ability to understand, interpret and execute to changes in store and product behavior at a very granular level. With the pace of shopping patterns changing so rapidly, manual planning and updating can’t meet the objective of allocation anymore. Modern software can define the strategic economic objectives of individual products and allow allocation to maintain an image while still being free to react to the most current reality of customer shopping patterns.

In fashion this means going beyond historical sales activity. As discussed earlier in this series, understanding historical demand is hugely important to making the right decisions going forward. Even store plans created by product that could be updated daily would not be as effective as they should be if they’re based on historical sales rather than demand. Understanding behavior also means gaining insight into the seasonal characteristics of products and stores and understanding the unique selling patterns across the lifecycle of individual products.

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Follow this series to learn all 10 strategies for improving allocation. We will be deconstructing the allocation process and exploring opportunities to improve within your current allocation processes and technology limitations. We will also review key areas to think about if you are considering investing in improved allocation capabilities.

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