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 can focus too much on forecast accuracy that they cannot see the forest for the trees. I know this because I was guilty of this from time to time when I led a demand-planning group because we were evaluated on forecast accuracy.
The value generated by improved forecast accuracy comes from how that improvement is used to enable cost reductions 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. In reality, there are as many definitions for demand sensing as there are software suppliers that offer demand sensing solutions.
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 has very little impact on down-stream planning processes such as supply and manufacturing planning.
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.
So, the promise of using statistical algorithms, forecasting and predictive analytics is now added to the list of a company’s number one priorities. T
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