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There’s only ONE answer to Demand Management By Mike Hennel In a demand-driven environment where the focus is on meeting customer expectations, accurate demand forecasting is only achieved when a collaborative process integrates various forecasting systems. By adding performance analytics to measure the iterative plan and understand trends, Companies managing their supply chain can become even smarter about anticipating shifts in demand. The end result of improved forecast accuracy is reduced inventory costs, better customer service and improved fill rates. 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. The blunt truth is any business that forecasts demand in silos is just guessing. The price of inaccuracy is high. Surplus is a wasted resource. Shortfall is a wasted opportunity. To survive, production must be accurately 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 ERP and CRM packages. Analytic tools should sit atop the core and generate multidimensional performance scorecards for customers based on Key Performance Indicators (KPIs) and business rules. 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, provide answers as to root cause and point to adjustments. Finally, the entire solution ideally is based on a Web-based platform that securely extends the supply chain to include supplier and customer-distributor data. The pursuit of Return on (previous) Investments (ROI) leads some supply-chain- centric businesses to lean too heavily on application suites or specialized solutions already installed. Few Supply Chain Management (SCM) systems include data repositories or analytic tools, and most are only used for internal demand planning. Cost, complexity and lengthy implementation make Enterprise Resource Planning (ERP) suites somewhat inflexible. Customer Relationship Management (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 the analytics and event detection and management capability.

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  • Theres only ONE answer to Demand Management

    By Mike Hennel

    In a demand-driven environment where the focus is on meeting customer expectations, accurate demand forecasting is only achieved when a collaborative process integrates various forecasting systems. By adding performance analytics to measure the iterative plan and understand trends, Companies managing their supply chain can become even smarter about anticipating shifts in demand. The end result of improved forecast accuracy is reduced inventory costs, better customer service and improved fill rates. 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. The blunt truth is any business that forecasts demand in silos is just guessing. The price of inaccuracy is high. Surplus is a wasted resource. Shortfall is a wasted opportunity. To survive, production must be accurately 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 ERP and CRM packages. Analytic tools should sit atop the core and generate multidimensional performance scorecards for customers based on Key Performance Indicators (KPIs) and business rules. 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, provide answers as to root cause and point to adjustments. Finally, the entire solution ideally is based on a Web-based platform that securely extends the supply chain to include supplier and customer-distributor data. The pursuit of Return on (previous) Investments (ROI) leads some supply-chain-centric businesses to lean too heavily on application suites or specialized solutions already installed. Few Supply Chain Management (SCM) systems include data repositories or analytic tools, and most are only used for internal demand planning. Cost, complexity and lengthy implementation make Enterprise Resource Planning (ERP) suites somewhat inflexible. Customer Relationship Management (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 the analytics and event detection and 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 management. Any and/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. Recently GartnerGroup claimed: "Enterprises that collaboratively integrate disparate forecasting systems...will improve revenue predictability by 10% to 25% and decrease inventory carrying costs by more than 30% over a 3-year period." Do the math for your own organization. I think youll find that a tool that can help you produce ONE agreed upon forecast can be a very lucrative investment.

    About The Author Michael J. Hennel is President & CEO of Silvon Software, Inc., a Chicago-based developer of Business Performance Management solutions for manufacturing, wholesale distribution and retail enterprises. Mr. Hennel founded Silvon in 1987 following a successful career in ERP solution sales, marketing, consulting and development management. Today, his company serves the business performance management needs of more than 1,400 businesses worldwide.

    About The Author