Available-to-promise, originally developed for master planning in manufacturing, is particularly suitable and adaptable for omnichannel fulfillment decisions. A new capability called multisource ATP is emerging in omnichannel. It
allows retailers to rapidly view ATP across multiple sources
of supply—warehouses, stores, factories, and in-transits—
and make decisions based on the most profitable supply
location at a given point in time (Figure 5). While this type
of analysis is not entirely new, it can now be done instantaneously and on an enormous scale, across huge numbers of
orders and multiple sources of supply. The new solutions
allow for flexible decision rules that can rapidly traverse the
supply sources and decide the source for each individual
order. These capabilities are even more powerful in orders
with multiple line items, where the seller may or may not be
able to source all of the items from a single location.
There are added complexities when sourcing from locations such as retail stores. The primary demand source for
physical stores comes from shoppers who walk in and buy
items off the shelf. In this situation, they may be holding
inventory (thereby making it unavailable) from the time
they remove something from a shelf until the time they
check out. A further complication is that shoppers often
pick up items from one location and place them at some
other location in the store. This creates the problem of
“floating inventory,” in which a certain amount of inventory is not in its intended location.
Thus, shoppers’ behavior can lead to discrepancies
between what a store inventory system says it has on hand
and what it actually has available. Rules used for fulfilling
online orders from such supply sources must take this
uncertainty into account. An effective omnichannel fulfillment program should understand such complexities but
not try to conquer them all at once. It is better to focus on
order fulfillment reliability first, and then add more sophisticated capabilities that increase profitability.
ATP that has to deal with these types of situations, which
cannot easily be calculated or quantified, may have to
employ approximations, or “fuzzy logic.” Saving a sale by
sourcing the product from an undesirable location could
be the best decision in some situations but not in others,
and the ATP capability must be able to recognize and pri-
oritize those trade-offs. For example, if a product is not
available in the location that offers the best margin, then it
may make sense to source it from farther away, depending
on the demand dynamics for that product at that location.
Inventory age at the more distant location may indicate
that a markdown is impending, but the online customer is
willing to pay full price right now, albeit with free shipping.
If the cost of the markdown is greater than the cost of the
shipping, then this is a win for both the company and the
customer.
When customer profiles and history are available to the
order management system, omnichannel provides a rich set
of fulfillment options for engaging in this sort of demand
shaping. Companies can start with decision-making pro-
cesses and general rules, followed by more sophisticated
rules that can be codified and configured into the software.
These more sophisticated capabilities allow for more com-
plex sourcing decisions. For example, the least-cost source
for an online order may be the local store, but the forecast
for that item in that store shows a planned promotion that
will cause a spike in demand. Sourcing from that store, then,
may cannibalize planned sales, and from a holistic stand-
point, it would be better to source it from somewhere else.
This logic can be served up to all sales interfaces, includ-
ing e-commerce and store associates, to not just provide
endless-aisle visibility, but to also ensure that sales are made
with the best profit profile for the business.
8 Synchronize product returns with assortment, buying, and demand planning. The return rate for e-com-
merce sales is significantly higher than for traditional brick-
and-mortar sales. E-commerce returns can range from
approximately 5 percent for basic items to as high as 60
percent for high-priced fashion items.
This makes returns management a major concern in
omnichannel retail. As previously noted, it is important
to forecast and process returns as part of the planning and
execution processes. At the execution level, decisions must
be made about the best disposition of returned inventory,
Multilevel,
Profit-Based
Available-to-
Promise
Decision Factors
Inventory?
Location?
Number of moves?
Markdown?
Shortages?
Excess?
Sources
[FIGURE 5] MULTISOURCE AVAILABLE-TO-PROMISE (ATP)
