Settle for optimal, not average using a tailored approach – and reap the rewards

Let's cut to the chase. Using averaged data to inform your decisions will result in average outcomes. By its very nature, relying on averages derived from aggregated data obscures the insights required to avoid misguided strategies and missed opportunities.

When it comes to space planning in retail stores, defaulting to plans based on averages is a convenient shortcut, but the trade-offs are significant, and often hidden, with underperformance embedded in KPIs, flying under the radar with little or no accountability, or at worst, simply accepted as part of the challenge of retailing at scale.

Here are four reasons why defaulting to using averages leads to lost opportunities, inefficiencies and store network underperformance, and how you can move your business towards localised space optimisation.

1. Masking local preferences

Customers are at the heart of retail success. It’s a universal truth that each store serves the needs of its local customers, who are unique to each location, and by using averages based on space performance across a large store network, you’re never truly meeting the needs of the customers who shop a particular store.

Failing to accommodate local preferences in space planning results in misalignment between what your customers are looking for when shopping your store and the way space, assortment and inventory weight is allocated versus this demand.  More frequent shelf out-of-stock are likely leading to customer dissatisfaction and missed sales.  At the same time stock will be tied up in unproductive areas, likely contributing to high waste and markdowns too.

2. Identifying successful stores and scaling for success

Analysing averages, or comparing performance of individual stores against an average, will fail to identify what’s working and where demand truly lies. Localised, store level analytics makes it easier to identify and replicate successful strategies across other locations. By analysing specific store level factors, such as product assortment, space allocation and pricing strategies, you can scale success rather than settle for mediocrity.

3. Concealing underperforming stores

Just as working with averages makes success factors difficult to identify, it also conceals drivers and features of under-performance. Store-level analytics will help identify the nuances that are bringing store performance down, including misalignment in product assortment, too much or too little stock to meet demand, or lack of accounting for differences in floor design and storage space. Optimising for these differences will improve customer and store outcomes.

4. Ignoring operational limitations and requirements

Just as the customers shopping each store differ, so do the physical attributes of each store, and these need to be considered when planning and allocating product assortments and space.  Floor size and design, access points, foot traffic and flows, stock room storage space, ease of replenishment and a raft of other factors related to the physical store will have implications for space strategies and must be taken into account.  

Analytical clout is more accessible than ever

Making decisions based on robust, insightful data drives better results. Here at Scalene, we see this first-hand, time and again. Taking a store specific approach recognises that each store operates in a unique environment with different challenges and opportunities and distinct customer preferences. The results speak for themselves, with sales and margin uplift between 5-10%, and waste and/or markdown reduction of up to 9%.    

The single biggest challenge in achieving optimised, strategic space planning at a store level is the analytical power required to accurately process vast datasets and deliver trusted recommendations that can be acted upon.  

Space planning technology provides your business with the analytical clout to ensure you are making space allocation decisions based on the most robust data-driven insights, not averages. Advances in data science and cloud technology has driven greater accessibility and improved outcomes for retailers ready to invest in their space function to improve commercial performance.

In an environment of low growth and increasing costs, now is the time to start on your journey to localised store space optimisation and we’re here to help.

 

We help retailers transform how their Range and Space team delivers maximum value. To learn more please get in touch at [email protected].