Demand planning has a big impact on business performance. Planning error can put revenue at risk by driving component shortages. Persistent planning biases can tie up cash by driving excess inventory. Furthermore, the act of planning and dealing with planning error is time consuming and drives costly overhead.
Accurate and efficient demand planning requires an ongoing commitment to understanding customer behavior. Guesswork should not be hardwired into the process. Planning processes should not force people (and systems) to make “wild guesses”. An insight-based demand planning process seeks different perspectives across functions that may not normally be connected. The creative and dynamic integration of analytical models with various human inputs (sometimes from nonconventional sources) can produce transformational breakthroughs in planning performance. The goal should be a process that leverages what is known, versus what is unknown (i.e. needs to be guessed).
Demand management is about minimizing error where it matters most, then recognizing there will be a degree of error and having a process to mitigate these errors.