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The objective of
this article is to highlight how critical a three-tiered, demand
management, forecasting process is to successfully exercising supply
chain optimization.
The introduction will briefly describe the existing distribution
network and business environment, where this three-tiered process
is emerging.
The first segment will describe the definition of demand
management. This will include a discussion involving marketing and
sales in scenario playing for price increases, promotions, market
penetration, margin management, channel management, and demand
creation.
The second segment will touch on the forecasting aspect of the
three-tiered process. This discussion will focus on the tool or
forecast engine, "pick-best" statistical concepts, management of
the forecasting engine, calculation of forecast error, and measures
of performance over time.
The third segment will profile the process. This will highlight the
consensus forecast approach, with customers, marketing, sales, and
supply chain folks all collaborating towards an agreed-to corporate
forecast that drives the supply side of the business. This
sweet-spot, within the three-tiered process, is the ultimate goal.
The final segment will highlight the benefits to be derived from the
three-tiered process that speeds up demand feedback to and
synchronizes real demand data with the supply side engine.
BACKGROUND: THE DISTRIBUTION NETWORK
The organization produces roofing products for the residential and
commercial industries and ships over nine billion pounds of product
per year. The base business environment covers the domestic United
States and includes shipments into Canada, Mexico, and offshore. The
corporation maintains 28 manufacturing plants and approximately 10
sales warehouses to distribute its products. The business maintains
5 sales jurisdictions, over 100 territories, and approximately
13,000 traffic lanes or distribution patterns.
This vast supply-chain distribution network is integrated through
the use of HP computers and a wide-area network (WAN). The
corporation and manufacturing facilities manage the day-to-day
business transactions through the use of a fully functional,
integrated ERP system. Several decision support systems (DSS)
provide what-if analysis capabilities to multiple departments as
well.
DEMAND MANAGEMENT: THE INSIGHT
The classic definition of forecasting is that it seeks to predict
levels of weekly or monthly product activity over a time horizon,
typically two years. The reasons for forecasting are much more
varied. Marketing wants to use forecasts to set goals for market
share and performance management. Accounting wants to utilize
forecasts to predict financial performance and capital requirements.
Manufacturing wants to use the forecast to decide what to produce,
how much, and when. Business managers want to utilize forecasts for
setting strategy and improving the bottom line.
The forecast team defined its forecast mission as follows: "The
forecast mission is to acquire, develop, and implement a system
that can provide a single corporate forecast that enhances the
return on inventory investment while maximizing customer service
and profitability."
We mentioned earlier that there are several different reasons for
forecasting. The key is enhancing both the demand and supply side of
the business ledger. How?
On the demand side, the forecasting approach will provide
• one forecast of demand that will drive the supply side
• a what-if tool for sales and marketing to assess outcomes due to
price changes, promotional events, and new product introductions,
before the organization commits resources
• a process that assists sales and marketing in channel management.
This will allow marketing to profile different channels of
distribution, their wants, needs, and financial impacts on the top
and bottom line sales numbers.
• sales, marketing, and finance a vehicle for differentiating
profitable versus unprofitable channels of distribution and
customer partnerships. (See figure 1.)
On the supply side, the forecasting approach will attempt to
• leverage the forecasts for production/inventory planning
• leverage the calculated forecast errors to drive down inventory
investment
• increase inventory turnover
• standardize the production/inventory planning process
• synchronize demand and supply planning to produce the right
product at the right place at the right time.
To Be Continued
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