Over the past few years, retailers have rushed to build a huge customer-facing omnichannel infrastructure. And for good reason: Omnichannel is critical when it comes to saving the sale, improving customer satisfaction and loyalty, and providing a localized experience.

But this massive omnichannel edifice was built without an omnichannel planning foundation. And while leading retailers have succeeded in achieving customer-centric operational goals, these successes have come without addressing the underlying issues of data integration and organizational change. As a result, it’s the rare retailer who has fully realized omnichannel’s promised improvements to inventory turn and efficiency.

In retailers’ defense, there was no way to build a solid omnichannel planning foundation before first implementing the customer-facing aspects of omnichannel, as this was the only way to get the needed consumer-demand data to inform their omnichannel inventory strategies.

But newly armed with this demand data, retailers now need to change the way they track and estimate total omnichannel demand—or their omnichannel infrastructure could start to crumble.


In omnichannel inventory planning, fulfillment demand isn’t equivalent to consumer demand, so retailers have to know where to place inventory to best meet consumer demand. Fulfillment demand addresses only part of the issue and will end up costing more in the long run—retailers may have enough product, but not necessarily in the right places. That’s why, although sales have grown since 2011, inventory turn has fallen, as illustrated in Exhibit 1.

zoom iconOmnichannel has helped retailers grow sales, but the lack of a planning foundation led to efficiency declines.

To better understand the problem, let’s consider the case of a Kurt Salmon client we’ll call DressMart. DressMart customer Dianne buys two dresses from her local DressMart store—one is in stock and one will be shipped from the DressMart.com fulfillment center to her house. Should DressMart plan future inventory for the location that sold the dress or, rather, for the location that shipped the dress?

And what about when DressMart customer Maria buys a dress at DressMart.com and returns it to the store—which is the case for roughly 30% of returns across apparel categories—and when that DressMart door resells the online purchase, should DressMart incorporate that sale into future sales plans and allocations? Or if the return is not resold, then how can corporate avoid penalizing that store for having the dress in inventory and not selling it?

DressMart, like all retailers, needs to know not only the origination of demand, but also the details of the actual selling transaction, including what was purchased, from where it was fulfilled, plus the traditional transaction information. They need a way to tag and identify demand—a new but essential piece of information.

As the DressMart cases illustrate, categorizing new combinations of demand and fulfillment requires untangling many separate purchase paths and their corresponding data. From there, the challenge is logging that data and intelligently feeding it back into merchandising, planning, inventory management and reporting systems.

Since this new data will look different, these systems may now require new sets of tools to ensure that the data is accurate and consistent across systems— connecting seasonal tasks and day-to-day business performance. This challenge will be even greater for retailers with separate inventories by channel.

Accomplishing this will likely require new technology, but new organizational practices will be even more critical. It will be essential to see omnichannel demand and inventory levels together—a far cry from the siloed organizations many retailers now have—and many organizations will have to transform as they align their merchandising and planning, inventory management, and analytics capability.

This process won’t be linear—planning inventory in an omnichannel world will continue to build on itself as retailers gather and learn to analyze more transaction and demand data.

Still, starting the transformation now will be well worth it. Retailers will have to understand how much inventory—across channels—they need, how each channel will sell it and precisely where it should go to recover margins, optimize turns and ultimately fulfill the omnichannel sales promise for their customers and their bottom lines.

zoom iconTransactional data needs to feed the decisions of interrelated merchandising and inventory planning phases.

27 January 2016