Price Optimization Software Helps Seagate Boost Profits - InformationWeek

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Price Optimization Software Helps Seagate Boost Profits

Hard drive titan replaces 'Excel Hell' pricing methods with a systematic, intelligent approach.

Price Optimization Software Helps Seagate Boost Profits
You can't change the basic dynamics of supply and demand, but you can get smarter about extending discounts and absorbing selling costs. Seagate Technologies, the well-known hard drive supplier, has joined the growing list of companies using price optimization software to do just that. With better insight into customer segments, Seagate is counting on an improvement of at least 2 percent in its margins.

Seagate took its first steps toward better profitability by recognizing it had a problem. The pricing team, which has nearly 50 employees, resets prices on hundreds of products each week, responding to changes in costs and market demands. Using these ever-shifting prices as a guideline, the team then strikes hundreds of individual deals and contracts each day, extending volume-based discounts and special service and delivery terms as requested by retailers, distributors and original equipment manufacturers (OEMs). The team also handles quarterly demand and revenue planning with input from sales, the product lifecycle management (PLM) team, marketing and finance.

The problem was that the information needed to drive all these decisions was scattered. "We were living in 'Excel Hell,'" explains Jenny Bhatt, who oversees distributor and OEM deals and contracts as director of Global Pricing. "It was very hard to respond to market dynamics in a high-transaction environment when the information we needed was on multiple systems and multiple spreadsheets."

The company launched an RFP for price optimization software in late 2007, seeking a comprehensive environment with a strong analytical tool so it could focus on "analyzing and making decisions rather than collecting data," as Bhatt explains. After a six-month review, Seagate selected the Vendavo Pricing Suite in May 2008. Unfortunately, the phase-one implementation took longer than anticipated due to ETL-related delays unrelated to the software.

"The biggest thing we learned -- and anyone who implements pricing software will probably tell you this -- is that you tend to underestimate the data challenges you will run into," Bhatt says. "It's great analytical software, but you have to feed the beast. It took us a bit of time to develop clean and accurate data that could be fed into Vendavo in a sustainable way."

With the first phase of the deployment completed in December 2008, data started flowing from more than seven different systems, including enterprise resource planning, customer relationship management, PLM and legacy data warehouses. The analytic software then screens the data to spot transactional attributes. For example, deal volumes, product selections, pricing demands and delivery terms tend to break into segments. The more consistent their behavior, the more likely customers are to fall into specific segments.

"What Vendavo really lets you do is separate out your true price buyers from your convenience buyers from your cherry pickers from your big-hat, no-cattle customers," Bhatt explains, using a few of the segment descriptors. "Cherry pickers," for instance, tend to buy only selected products or at special prices (or both), whereas "big-hat, no-cattle" customers promise big deals to win favorable prices but don't follow through with expected purchasing volumes.

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