April, 2004   |   John McPartlin — Companies have grown accustomed to using information technology to design, manufacture and ship products, and to slice and dice the numbers in every conceivable way after the fact. But what’s less well known is the role IT can play in determining the optimum price for a product or service. Since “optimum” equates to “most profitable,” the technology at the heart of these efforts goes by interchangeable names: price-optimisation or profit-optimisation (PO) software. While not new, PO software is poised to go from the fringe to the mainstream, say analysts, vendors and, most important, customers. That’s being driven by a number of factors, including the pioneering companies going public with their successes and large software vendors taking an interest in adding PO “solutions” to their product line-ups. Despite the still considerable implementation challenges, the financial rewards from these products may now outweigh the risks—for some customers, at least.

One of PO’s ancestors is the yield- management software that gave a boost to the airline and hospitality industries in the 1980s by squeezing profits from the last-minute sales of vacant seats and rooms. More recently, the retail industry has been an enthusiastic user of such products, often employing PO software as a defensive move against larger rivals. That has led the charge in this niche from vendors such as KhiMetrics, DemandTec, ProfitLogic and Manugistics. Other vendors, such as Acorn Systems, Rapt and Metreo, have concentrated on providing PO software to companies beyond the retail sector.

The software puts its arms around a lot of data, both internal (some of it builds on work done in activity-based costing) and external (analysing past customer response to price promotions, for example), to help users determine an ideal pricing strategy.

Early adopters talk about PO with the zeal of religious converts. David Feinstein, CFO of metals distributor Klein Steel, says he’s not someone who is easily impressed, but he’s been consistently surprised by the information the company’s Acorn system has helped uncover. Klein Steel, which distributes steel, stainless steel, aluminium and fibreglass products in upstate New York, has been using Acorn for the past two years. “Now we have a better understanding of where the actual costs occur on a customer and product basis for the purposes of allocation,” he says.

The impetus for looking into PO solutions came from Feinstein’s boss, who came to him after attending a trade show at which profit optimisation was mentioned. “I was very sceptical,” Feinstein says, “which I guess is typical of finance. But I agreed to meet with the company. After a two-hour session, I was convinced that we needed to install it. Looking at the software, the algorithms, and the detail in which the software could delve into our business, I was very impressed. They were not approximating our costs but isolating them on a department-by-department basis.”

Costly customers
Many companies say the benefits of PO software are not hard to quantify. One of the key things Klein Steel discovered after implementation was that the company had the wrong idea about who its most profitable customers were. “You make a profit at the end of the quarter, but then you find out that you’re losing money on a third or half of your customers and you would actually be more profitable without them,” he says. By using PO software and having access to more relevant data, the company found that, although it consistently coddled its larger customers, it was actually the mid-sized customers that were the most profitable. “So we changed our orientation to the customers that fed our bottom line the most,” says Feinstein.

In addition to lavishing more attention on certain clients, Klein Steel also made some operational changes based on the data its PO software uncovered. In some cases where customers were receiving several deliveries a week, the company was able to cut deliveries down to one a week. This reduced delivery costs for Klein Steel and cut receiving costs for its customers. The company was then able to lower its expenses while keeping prices flat, essential in its highly competitive market. “If I could not pinpoint where my costs are, I would not be able to do something like that,” says Feinstein. “And if I could not pinpoint [the factors underlying] my net profit, then I wouldn’t even know we had a problem in the first place.”

Canadian clothing retailer Northern Group Retail implemented a PO solution from ProfitLogic in 2002, embarking on a remarkably tight, 13-week implementation schedule so that it could have the product in place for the holiday season, which accounts for 40% of its annual sales. The company’s CFO, Michael Stanek, says the software, which monitors sales data and inventory levels from Northern Group’s 278 stores and performs historical comparisons, helped the company move from uniform chain-wide pricing and discount strategies to an approach more attuned to regional needs, weather patterns and other trends. As a pilot test of the software, the company offered discounts across the country and didn’t mark down prices at all in some cases. “We saw we didn’t need to be so aggressive in marking down in some areas,” he says. “We are now managing markdown dollars and generating as much gross margin as we can in certain regions. We are not leaving any nickels on the table.”

Even with the rapid advancement in software and hardware, price optimization remains an inexact science. Various applications are likely to churn out different results. Why? Because PO programs are driven by proprietary forecasting engines. These engines are based on sophisticated mathematical algorithms originally developed for scientific research and military planning. "It's almost like rocket science," says Kosin Huang, a senior business applications and commerce analyst at The Yankee Group, a technology research and consulting firm. "It's like the secret sauce that's behind the whole thing."

For her part, Rosenblum says potential customers shouldn't be overly concerned about finding exactly the right software. "Wherever [the programs] have been put into use," she asserts, "they have proven results."

Maybe so, but better pricing doesn't come cheap. PO vendors, which clearly use their own software, have affixed some pretty high price tags to their products. Analysts say license fees for the software range from $300,000 to $1 million. Rosenblum says vendors can charge nosebleed prices, however, "because the return on investment is so high."

To gain, some pain
The big obstacle facing any firm trying to implement PO software, according to CFOs, vendors and analysts, is the cultural resistance from those at the front lines—salespeople, pricing managers and department heads—who have been making pricing decisions on their own, largely based on spreadsheet data and gut instinct. Many of these people feel threatened by software that tries to tell them what to do.

“[Cultural issues] represent one of the single greatest obstacles to rapid market adoption,” says Tim Manning, vice president of marketing at Arizona-based KhiMetrics. “You have a new technology that, while proven, makes you no longer reliant on the ‘art’ of pricing.”

The best way to increase user buy-in is to position PO technology as an enhancement rather than a replacement for individual expertise, according to Scott Langdoc of Boston-based consultancy AMR Research. “Instead of ‘price optimisation,’ it should be looked at as ‘price recommendation,’ complementing the experience of the people who are using it,” he says. “Adoption will increase when users are comfortable that they can combine their pricing strategy with recommendations from the software and then deploy prices that are defended by strong analytics.” One other factor will help, he adds: increased profit margins, which have a way of turning sceptics into fans.

The optimal optimiser
Price-optimisation software products are often tailored to specific needs, which can include:

• Pricing new products
• Pricing inventory for clearance, promotions or incentives
• Setting price lists for families or bundles of products
• Establishing contract pricing
• Designing what-if strategies for a number of circumstances

While many vendors play well in more than one category, analysts say none addresses them all effectively. Shop carefully.

Source: Forrester Research