Making Cents Out of Demand Sensing

Making Cents Out of Demand Sensing


As a supply chain professional, we need to consider how actions in one part of the supply chain affect both upstream and downstream operations. This is especially true for those that work in and manage the demand planning process. Sometimes demand planners focus too much on forecast accuracy and miss seeing the forest for the trees. I was guilty of this from time to time when I led a demand-planning group because we were evaluated on forecast accuracy as one of our key metrics.

The value generated by improved forecast accuracy comes from how that improvement is used to enable cost reductions, synchronize production and enhance customer service. Here in lays the crux of the issue with demand sensing. Does demand sensing actually improve a company’s ability to reduce cost and improve customer service? Before I get ahead of myself, let’s explore what demand sensing is, where the concept came from, and the reported value of implementing it.

Gartner defines demand sensing as “the translation of demand information with minimal latency to detect who is buying the product, what attributes are selling and what impact demand-shaping programs are having.” Gartner reports that the predominant inputs to demand-sensing solutions are daily point-of-sale (POS), customer inventory, transactional data, and order and shipment history. This sounds a lot like the definition for demand planning to me. However, proponents for demand sensing say that it occurs more frequently (near real-time) within the periodic process of demand planning and usually within production lead-time.

Demand sensing did not come out of the academic community, so there have been few unbiased descriptions of what demand sensing is. Supply chain software vendors who offer demand sensing solutions primarily control the definition which results in multiple definitions for the same term each biased towards the strengths of the particular supply chain software vendors.

And now back to that crux. Since periodic forecasts should be set up to account for the product lead-time and demand sensing takes place inside of that periodic process then demand sensing is the adjustment of a forecast inside of the product lead-time. Therefore, demand sensing is the adjustment of a product’s forecast for which the supply plan cannot respond. Ex: If lead-time is 2 weeks, then demand sensing means changing the forecast less than 14 days out. Because demand sensing changes the forecast within the lead-time, demand sensing really can’t be considered a forecasting approach. Demand sensing does not help supply planning and has no effect on inventory management. It does; however, create the illusion of improved forecast accuracy by changing the forecast in the way that can never translate into an improvement in supply chain performance.

In almost all cases, companies that have reported the value of demand sensing have only reported forecast accuracy improvements. Since these improvements are within lead-time no corresponding supply chain improvements are quoted. In reality, if a change in demand is known sooner rather than later the mix of product produced and distributed could potentially be adjusted to maximize customer fill rates and/or profits. Of course, this depends on a company’s ability to conduct inventory and supply planning what-if scenarios taking into account the appropriate facility, lane and time constraints.

Demand sensing is just one tree in a forest of capabilities that can be used to improve a company’s supply chain capabilities. Used in conjunction with other demand management capabilities and downstream capabilities like inventory planning and optimization, supply planning and optimization, and manufacturing planning and finite scheduling, demand sensing can provide value in certain situations, i.e., engineer-to-order and configure-to-order products.

When looking at demand sensing capabilities consider these observations.

  • Many of the capabilities that are often touted as part of a demand sensing solution can be enabled through the use of an advanced supply chain planning system.
  • Making short-term changes to the forecast introduces a significant amount of noise into the forecast. Forecasts need to be set and left unchanged to facilitate stable and efficient downstream purchasing, inventory management, and manufacturing capabilities.
  • All statements of value gained from demand sensing are in terms of short-term, within lead-time, forecast improvements.
  • Little evidence has surfaced showing demand sensing actually leads to supply chain cost or service level improvements.

Additional Reading:

Hank Canitz
Hank Canitz

Product Marketing Director Hank brings more than 25 years of experience building high performance supply chains. This experience includes evaluating, selecting, implementing, using and marketing supply chain technology. Hank’s graduate degree in SCM from Michigan State, numerous SCM certifications, diverse experience as a supply chain practitioner and experience in senior marketing roles with leading supply chain solution providers helps him to bring a unique perspective on supply chain best practices and supporting technology to the Voyager Blog.

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