Every day, retailers of all kinds discover that driving profit margin growth isn’t always easy if store and department managers are using plans that don’t reflect local buying patterns, demand trends and price sensitivities.

If managers on the floor want forecasts and promotions that zig every time consumers zag, they’ll need planning, forecasting and analytics systems with more flexibility below the category level. The Holy Grail, of course, is SKU-level analytics. Yet most retailers are locked into environments that aren’t built to ingest and analyze transaction data across thousands of SKUs several times a day. And they certainly aren’t built with the computational scale and elasticity required to accurately forecast how much of a certain SKU to stock, especially if demand isn’t easily predictable. Limitations like these lock retailers out of the granular insights they need to pounce on profit-growing opportunities when they arise, to prevent over- and under-stocks, and to avoid promoting middling products when far more profitable stock is left to languish in a low-volume location. 

The SKUs Have It

Exponentially faster analytics, particularly at the SKU level, isn’t a trivial pursuit. The average supermarket stocks more than 42,000 SKUs, and that number is growing. SKU proliferation is rife throughout multiple categories as consumer packaged goods (CPG) makers target ever-narrower market niches with new products – gluten-free crackers, caffeine-free cola, fruit-sweetened jams, BPA-free everything. In the beer industry alone SKUs have virtually exploded: craft and specialty beers lit the fuse, causing SKUs to increase from 300 to more than 1,000 in the past decade.  And with retailers putting more locally sourced items on their shelves, forecasting from corporate or even regional levels becomes either much more difficult or much less helpful – sometimes both.

Local buying is key for one retailer we work with. This globally known brand, with over 400 stores throughout North America, initially brought in Tidemark to generate more responsiveness and flexibility with payroll planning at the store level. With planning now taking place in real-time on mobile devices, right from the store floor, the company is using Tidemark again, this time to analyze profitability and purchasing trends at the SKU level. With Tidemark’s computational cloud processing multiple transaction updates a day, managers have a much more granular view of what’s selling, what isn’t, and where potential profit may be hiding. The next step includes the incorporation of big data finance. Tidemark customers will soon combine in-store transaction records with external data from Nielsen and IRi to understand what triggers purchase decisions, so stores can create an environment that serves as an “on ramp” for buying. They will also use the data to benchmark their performance in an unprecedented way.

Retailers know that the secret to growing profits is right there on the store floor. The key is to find a way to unlock those insights, even as the task grows more difficult with each new SKU.