4 Pillars of Demand Planning

4653 Words Feb 22nd, 2013 19 Pages
L O G I L I T Y V O YA G E R S O L U T I O N S

An Executive White Paper

Four Pillars of Demand Planning Excellence
Achieving higher supply chain performance with more powerful, accurate demand planning

L O G I L I T Y V O YA G E R S O L U T I O N S

An Executive Whitepaper

Table of Contents Pillar #1: Go Beyond Simple Forecasting .....3 Pillar #2: Beat the “Devil in the Details” Using a Demand Aggregation Hierarchy........5 Pillar #3: Take Planner Productivity to the Next Level ............................................7 Pillar #4: Make Collaboration a Core Demand Planning Competency ......................8

Four Pillars of Demand Planning Excellence
Achieving higher supply chain performance with more powerful,
…show more content…
Advanced demand planning technology surpasses spreadsheet-based efforts by calculating the best possible demand prediction based on several inputs, including past performance of related products or unrelated products that share key attributes in addition to any data generated by pre-launch market testing. According to Gartner, “New product launch forecasting is overly reliant on sales and marketing for demand inputs. Opportunities exist to remove forecast bias by utilizing attribute modeling techniques and solutions that use similar product introductions to understand consumer/ customer trial and repeat, as well as volume build assumptions, to improve the forecast.” Sell In, Sell Through, and Maturation The demand profile ramps up as introductory promotions, advertising support, and word-ofmouth combine to create an initial strong demand, then dips as the sell-through period gives way to the maturation phase, with its own promotions and marketing programs attempting to shape demand over time. As the product life cycle unfolds, the demand planning solution compares actual demand versus the forecast. Statistical matching algorithms can be used to determine just how significantly actual demand has deviated from the prediction. The predictive accuracy of other demand profiles can be compared, and when a different profile provides a better match to the actual demand signal, it is swapped into play.

“The primary way organizations manage
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