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Published: January 9, 2002

 
 

Marketing and Operations: Can This Marriage Be Saved?

Marketers worry about top-line revenue, while operations people fret about cost. Differentiated Service Policies allow them to coexist.

Ongoing battles between marketing and operations provide fodder for everyone from humorists to organizational behavior specialists. Cartoonists mock the narrow-minded views of each discipline, while organization experts propose new compensation schemes to drive alignment. CEOs often laugh at both.

The stark truth is that marketing and operations do have fundamentally different perspectives — and for very good reason. Marketing focuses on top-line revenue and, accordingly, seeks product variety (available on short notice) from well-stocked inventory pools. Operations worries about cost, looking for efficiencies in manufacturing and the supply chain. Seldom does either function seriously examine value as perceived by the customer. This being the case, conflict is inherent, and organizational incentives alone cannot solve the problem (though a good cartoon can sometimes reduce the tension).

Rather than debating binary options from functional points of view, companies must seek to balance the trade-offs between costs of different service options and their value to customers. We refer to the decisions resulting from these explicit trade-offs as Differentiated Service Policies. Although they are a powerful tool, few companies fully understand them, and even fewer apply them appropriately. More often they fall back on “the way we do things” that reflects long-forgotten compromises.

Cost/Value Trade-Offs
Remember the last time you ordered a book from Amazon.com? You might recall that Amazon.com Inc. offers a variety of different shipping promises, such as “usually ships in 24 hours,” “ships in three to five days,” or “special order.” The reason? The economics of inventory. Although Amazon offers some 4.5 million titles, it can’t afford to keep all those books in inventory.

Amazon holds the most popular titles in its own distribution centers and typically can ship those books in 24 hours. A second tier of books is stocked by book wholesalers. Some wholesalers can fill an order in 24 to 48 hours, enabling Amazon to meet its promise of “ships in two to three days.” Other wholesalers may take a few more days, so Amazon promises “three to five days.” At some point in the life cycle of a book, wholesalers stop carrying inventory and only the publisher can fulfill an order — usually from inventory, but sometimes through a new print run. The longer lead time from the publisher forces Amazon to extend its promise to “one to two weeks.”

So, a simple Differentiated Service Policy — in this case, based on lead time — allows Amazon to address the inherent conflict between marketing and operations. Marketing wants to offer the broadest possible array of titles to reinforce Amazon’s positioning as having the “Earth’s Biggest Selection,” and to deliver those titles instantaneously to reinforce the convenience of online shopping. Operations, on the other hand, cannot support such a proposition — at least not cost-effectively. So, by examining the economics of inventory and understanding the value of lead time to customers, Amazon sets shipment lead times to define the appropriate compromise between marketing and operations.

Airline pricing offers another familiar example of Differentiated Service Policies. As any frequent traveler knows, airlines offer widely varying prices for the same seat depending on when the consumer books a reservation. The lowest prices are intended to capture incremental sales to travelers who might not take a trip otherwise — but without cannibalizing the sale of higher-priced tickets to business travelers who may not have a choice. To ensure that the low-cost seats go to incremental travelers, the airlines traditionally have imposed Saturday-night-stay requirements that the typical business traveler rarely meets. Over time, the airlines have become quite sophisticated in pricing the seats, dynamically adjusting the quantity of openings allocated to each price option based on real-time demand patterns from the reservation system.

 
 
 
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