Academic journal article The Journal of Business Forecasting Methods & Systems

Demand Planning and Forecasting in the High Technology Industry

Academic journal article The Journal of Business Forecasting Methods & Systems

Demand Planning and Forecasting in the High Technology Industry

Article excerpt

Forecasting practices have to utilize more sophisticated methods to avoid some of the of the biggest planning pitfalls...overall firm performance will be maximized if the demand forecasting processes are collaborative, sophisticated, oriented towards the product life cycle, and developed using non-constrained consumer demand data.

Most high tech firms are experiencing significantly more turbulence in the operating environment than in previous years. Wall Street has reacted negatively to most dot-coms, as well as to large computer hardware and software companies. The Amex computer technology index has fallen over 40% during the last twelve months. Additionally, the average net profit margin has fallen to a modest 5.6% level.

So how can forecasting impact these profitability measures? Those firms that did a better job of forecasting had significantly better control over their inventory and customer service levels. For example, while the average days of cost of goods (COGS) sold held in component and finished goods inventory is 16 days on the average for the hardware industry, those firms that more closely matched their supply with demand predictions reported less than 10 days on the average.

Furthermore, better demand forecasting helped many high tech firms to beat the average of 23.2 for inventory turnover (i.e., the number of times you sell your inventory per year) by nearly 25%.

KEY CHARACTERISTICS OF HIGH TECHNOLOGY INDUSTRIES

Despite the staggering range of products manufactured within such abroad classification, many companies in high technology industries share several common characteristics:

Markets for high technology products are generally young, sometimes less than a decade old. There is a dearth of historic examples and patterns to analyze for planning future demand.

Product life cycles are often short, while supply chain lead times for some components are relatively long.

Tactical planning is crucial, but requires so much attention that the strategic outlook is sometimes neglected. The rapid pace of technological evolution makes long range planning extremely difficult; new developments can create new markets almost overnight, or drive existing products into early obsolescence.

Demand for high technology products is influenced not only by the state of the economy, but also by fads and cultural shifts that can be difficult to anticipate. Consumers are increasingly demanding unique configurations, especially in the computer hardware industry segment, which creates havoc for procurement and production planners alike.

Profit margins often start out high, but quickly fall as competitors enter the new market. Inventory management in the early phases of a new product is therefore very critical.

Many key components are manufactured by a relatively limited number of suppliers, who may have to deal with several companies engaged in active competition. Failures to manage forecasts and maintain supplier relations are therefore not only injurious to a manufacturer, but also may inadvertently result in an advantage to its direct competitors.

There are some key elements, which produce most of the supply chain headaches for forecasters and demand planners. Those elements are discussed below.

RATE OF TECHNOLOGY DEVELOPMENT

Many people are familiar with the story of how Intel Corporation's cofounder, Gordon Moore, who predicted in 1965 that the density of transistors in an integrated circuit would double every year. This observation became known as Moore's Law. This was later amended to double every 18 months, which has proven to be remarkably accurate for over 30 years.

The Moore's Law produces an incredible rate of improved performance in electronics technology. With nearly every new chip generation, transistors are scaled down by a factor of 0.7. Compared to the previous generation, each transistor takes up only half of the surface area on the chip, can be switched in 30% less time, and requires only a third of the power for operation. …

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