Article Series

Unified Commerce: Implications on Traditional Back Office Systems

Unified Commerce: Implications on Traditional Back Office Systems Part 3

Jan 31, 2017
   |   by 
Rick Boretsky

This is part 3 of an 8-part series where we examine each of the cornerstone back office systems to reveal the issues in integrating them to the world of unified commerce. This blog focuses on Planning and Assortment Management systems. To start with, let’s begin by explaining what we mean by assortment management and planning systems:


Assortment management systems help plan the depth and breadth of local assortment to reflect the demands of targeted customers.


Planning systems bring together data from all channels in order to come up with plans for each merchandise category across all commercial activities for the next period.

What’s new for Planning systems in the world of Unified Commerce?

Most Planning and Assortment Management systems unfortunately do not deal with the three realities of Unified Commerce. These realities are:

1. Local inventories are no longer just for local in-store demand

2. “Endless aisles” alternatives, that more and more retailers are now developing, mean that in-stock inventory is not essential.

3. The customer path to purchase is changing rapidly which means that basing plans solely on prior performance might be dangerous

In addition, most of the local assortment management systems we’ve seen ignore customer segmentation despite the information’s availability.

At the heart of planning inventories for Unified Commerce lies two new requirements that Planning systems never had to do in the past. Planning systems must now:

• Sanitize information to reveal true customer demand

• Glean insight into customers’ path to purchase

In the graphic above you can examine the flow of information between Unified Commerce applications and the Planning and Assortment Management systems. You’ll see that there is no direct interface between the customer facing apps and the back-office systems. In fact, all of the selling information (demand) comes the Sales Reporting Applications which, as we previously pointed out, doesn’t typically contain any information about the customer path to purchase.

The Planner’s Dilemma

So, given the lack of data about the digital path to purchase, how is the planner supposed anticipate the digital demand? In our graphic we suggest three significant new flows into the Planning and Assortment Management apps. Fortunately, most planning systems are highly flexible and can be readily adapted to new information. This brings the focus back to data integration, namely:

1. OMS flow

2. Wholesale flow

3. Customer segmentation

From the OMS the planner can obtain information about order cancellations, orders shipped, and whether local orders were filled by local stock, the warehouse, another store, or the vendor. Moreover, the planner might consider such juicy tidbits as:

• What margin erosion occurs for each type of path to purchase

• How customer in-store pick up stimulates additional demand

Planning for Returns

Obtaining great information about Returns is also essential to plan inventories in the world of Unified Commerce. Many merchandise classifications report online order return rate in excess of 20% of sales. Unified Commerce retailers are remarkably liberal in accepting returns at local outlets. So, should planners begin to plan for these inventory additions? We believe so and your data integration roadmap should anticipate it.

Sanitizing sales to derive true demand

As more online orders are fulfilled from store inventory, inventory distortion will become more of a causal factor in fulfillment decisions. For example, if you are overstocked in XL sizes at a particular store, your fulfillment logic will disproportionately draw from the stores with the most inventory availability. Unless you are careful to reassign such sales to the correct source, you and your systems will replenish the store with even more XL’s in the next season. This might be a minor factor now, but as the share of digital commerce continues to climb, the distortions will soon lead to significant inventory problems which can be entirely avoided with expert data integration. Path to purchase data in the Planning input stream will help the data integration specialists remove these false positives.

Planning for Pooled Inventories Across All Channels

So, back to our graphic. You can see a flow of data from the wholesale channel into the Planning applications. This takes the form of EDI sales from individual retail customers, shipments to consignees and international affiliates, as well as shipments to retailers. Luckily, we’ve had the pleasure of working with several brands in the last couple of years who are successfully sharing inventories across retail and wholesale channels. In fact, as Retail Research reports in its August 2016 study of Omni-Channel, 86% of retailers see value in allowing inventory allocated to one channel to be used for another channel’s fulfilment.

The secret as always is to pass key data to permit downstream applications to distinguish demand from each source. EDI information from wholesale customers can be organized into geographic markets based on the store locations of each retail customer. At the local level, this means you can learn what inventories (fulfilled by wholesale channels and local stores) are actually required to meet local retail demand.

Customer segmentation

When as we talk about the challenges of Unified Commerce Planning, we also need to consider the power of using customer data with planning assortments. In our sales blog (link) we spoke about the immense value of enriching sales transactions with customer data (this data is readily available in Unified Commerce transactions). If retailers were to feed this data into their Planning and Assortment Management applications, Planners could potentially slice demand by desired customer segment. What follows are some segmentation schemes to isolate stores and categories which are out of alignment with customer attributes such as:

• Customer Loyalty

• Customer Age and Demographics

• Customer Lifestyle

• Customer Buying Habits

• Customer Proximity

We’ll deal with this more thoroughly in the upcoming blog on Customer Analytics.

Our Recommendations

1. Feed PATH TO PURCHASE data to the Planning Systems .

2. Bring CUSTOMER SEGMENTATION information in Local Assortment

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