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In 2000 Hewlett-Packard faced a supply crisis. The flash memory used in its highly profitable printers also was being used by fast-growing cell-phone makers and HP was unable to obtain sufficient supply to meet its demand. As a result, the company failed to ship about 250,000 printers, which translated into a revenue loss in the tens of millions of dollars. Moreover, to ensure supply HP was forced to sign a three-year fixed-quantity, fixed-price contract with significant non-performance penalties for what historically has been a highly volatile component.
This experience served as the catalyst for HP to develop a framework for measuring and managing supply chain risk. Known today as Procurement Risk Management (PRM), the framework, which encompasses both process and technology, has become a key initiative at the company and is being applied to about $6bn of spend annually across numerous HP business units. Incremental savings to date total more than $100m.
The task of developing the risk management solution fell to a research and development team led by Venu Nagali, distinguished technologist at HP. "One of the first things we did when we started this program was to look out and see how other manufacturers were managing supply chain risk," says Nagali. "To our surprise we found that few manufacturers had any processes at all in place." Indeed, he adds, the team found numerous high-profile cases where failing to manage supply risk had resulted in significant losses of revenue and of shareholder value. These failures fell into three primary categories: price risk, demand risk and availability risk. "These three-demand, cost and availability-are the key uncertainties that have to be measured and managed," says Nagali.
All industries experience these uncertainties, but they can be especially volatile in the high-tech sector where HP is the biggest single purchaser of many components, including memory, hard disk drives and LCD panels. "It is good to be number one in any given market, but that also forces you to take on substantial risk, just by virtue of the large volume of components you have to buy," says Nagali. Additionally, high-tech components are among the most volatile in terms of cost and availability. Nagali offers an example of DRAM memory used by HP, which dropped in price by more than 90 percent in 2001 only to more than triple in 2003. "Except for the electricity market," he says, "I have not seen a market with more price volatility than high-tech."
Availability also is often uncertain. In addition to general disruptions caused by natural disasters or political acts, Nagali notes that in periods of high demand, suppliers place original equipment manufacturers like HP under allocation "whereby they supply only a fraction of an OEM's total demand."
The final variable, demand, is intensified by high-tech's notoriously short product life cycles. "If your product is successful, it lasts for six to nine months," says Nagali. "If it is a failure, it can last less than a month."
Wall Street Model
Since Nagali and many of his team members had prior experience working with risk management in financial markets, they studied the Wall Street model carefully. While many of the principles were applicable to the supply chain, the underlying stratagems used on Wall Street were not easily transferable. "Financial engineering practices enable the management of cost uncertainty through such instruments as call and put options," says Nagali. "But such instruments are not available for high-tech components." Financial risk management also fails to address demand and availability uncertainties, he says.
Conversely, current supply chain management practices emphasize the management of demand and availability uncertainties through inventory buffering strategies, but have little if any focus on managing component cost uncertainties. "The philosophy seems to be that all the risk can be pushed onto suppliers," says Nagali. "But what is not really well understood is that suppliers charge a premium to manage that risk. This is a hidden cost."
The bottom line, he says, is that in the supply chain, demand, cost and availability uncertainties all are equally important and are correlated. This means that they all need to be managed together.
"What we had to do was invent a completely new framework for managing risk," says Nagali. "It was not possible to simply take the math from Wall Street and apply it." This framework also required new technology, since existing supply chain management and enterprise resource planning software do not support risk management.
The first challenge the team tackled was how to measure and account for uncertainty in each of the three areas: demand, cost and availability. To do this, they developed new algorithms that are embedded in a software solution called HPHorizon. This solution begins with a typical point forecast, which it analyzes and corrects for biases. Then, using historical forecasts and current demand trends, the software builds statistically significant scenarios that calculate how high and how low demand could go, attaching to each scenario a probability number. Generally, the low number defines the 10th percentile, where the chance of demand falling below this level is only 10 percent. The high number defines the 90th percentile, which has only a 10 percent likelihood of being exceeded. Between these two numbers is an 80 percent range that is expected to encompass most demand.
The same type of tool is used to develop a high, low and middle range for the cost variability of component parts, typically looking six months out. "We have developed proprietary analytics that model the unique cost dynamics of high-tech components," says Nagali, "but these analytics also could be adopted to forecast the cost uncertainty of other manufactured commodities, such as plastics, chemicals or steel."
Determining availability uncertainty has been more difficult to automate. "What we are trying to gather from this scenario is the likelihood that we will be able to meet our demand without any contracts-just by going to the spot market," says Nagali. Unfortunately, he says, there are not enough data points to build a model at this time, so HP determines this variable through interviews with market specialists.
Measure, Then Manage
Once uncertainties have been calculated, with probabilities assigned, the question becomes how to use this information to make decisions differently, says Nagali. "The answer to this question is the more powerful aspect of PRM and it involves developing a portfolio of procurement contracts designed to share risks with suppliers," he says. "The risk sharing nature comes about by HP taking ownership of the risks that we can bear more cheaply and asking suppliers to take risks that they can more easily manage."
For the segment of demand where uncertainty is low, for example, HP enters into fixed-quantity, fixed-price contracts for a reasonably long period of time. "This is different to what manufacturers do now, which is simply to send a full point forecast to suppliers-just a forecast, not a commitment," he says. By just sending a forecast, "manufacturers are pushing the entire demand risk onto suppliers, which is unfair," says Nagali.
"We had to invent a completely new framework for managing risk. It was not possible to simply take the math from Wall Street." - Venu Nagali of Hewlett-Packard | |
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