Collaborative Demand Forecasting Anticipates Shifts Any manufacturer that charges into the Internet Age without a collaborative

Collaborative Demand Forecasting Anticipates Shifts
Any manufacturer that charges into the Internet Age without a collaborative forecasting system does so at great risk. An electronics business that cannot accurately anticipate demand shifts may not survive the rigors of today's just- like- that expectations.
by John Hughes, senior vice president, Silvon Software Inc.

The Internet Age ushered in a culture of immediacy in which customers now demand rapid delivery or quickly move on. Electronics manufacturers are feeling this wave surge through the marketplace as much as any other industry. Whether or not your company's traditional distribution channels include the Web, you have likely fielded numerous questions from customers about using the Internet as leverage for reducing distribution costs and improving delivery time. However, any manufacturer that charges into the Internet Age without a collaborative forecasting system does so at great risk. An electronics business that cannot accurately anticipate demand shifts may not survive the rigors of today's just-like-that expectations.

Often finance, marketing, sales, and production departments have separate forecasting methods, technologies, and agendas. Finance focuses on internal cost control. Marketing relies on external statistics. Sales makes optimistic projections based on past orders. And production tries to mediate the expectations of the other three while somehow regulating the supply chain.

And in the fast-paced realm of e-commerce, the price of inaccuracy is high. Surplus is a wasted resource. Shortfall is a wasted opportunity. To survive in the Internet Age, production must be predicted at the SKU or line-item level to allow for rapid response to demand fluctuations--up or down--within supply constraints.

The secret to collaborative demand forecasting lies in synchronizing systems and point of view. At the core of any forecasting system should be a data repository that captures information from enterprise systems, such as enterprise resource planning (ERP) and customer relationship management (CRM) packages. Analytic tools should sit atop the core and generate multidimensional performance scorecards for customers based on key performance indicators (KPIs). Baseline production plans should be monitored and controlled with an exception management system, which provides performance metrics from many perspectives--customers, channels, markets, products, cross-selling results, promotional effectiveness, and external market trends. A rules-based system should alert operational teams to exceptions and trigger adjustments. Finally, the entire solution ideally is based on a Web-based platform that securely extends the supply chain to include customer, supplier and distributor data.

The pursuit of return on investment (ROI) leads some electronic businesses to lean too heavily on application suites or specialized solutions. Few supply chain management (SCM) systems include data repositories or analytic tools, and most accommodate only internal demand planning. Cost, complexity and lengthy implementation make ERP suites somewhat inflexible. CRM packages provide a customer-centric view, and thus by nature shortchange internal factors. Business intelligence (BI) tools offer in-depth reporting, but usually lack exception management capability.

SCM, ERP, CRM, and BI each have excellent features and benefits when applied to the problems they were designed to solve. But none is built specifically for collaborative demand forecasting. Any or all of these systems must be coordinated by a consensus methodology--a process that brings finance, marketing, sales, and production together to agree on a single forecast. The lynchpin here is an operational perspective--each group must seek the best production numbers for meeting demand with the narrowest margin of error.

Earlier this year GartnerGroup claimed: "Enterprises that collaboratively integrate disparate forecasting systems...will improve revenue predictability by 10 percent to 25 percent and decrease inventory carrying costs by more than 30 percent over a three-year period." Do the math for your own organization and remember to calculate the multiplier effect of Internet Time. The rewards of collaborative demand forecasting for electronic businesses will surely outweigh the risks.

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