Supply Chain Trends and Issues: Our Weekly Feature Article on Important Trends and Developments in Supply Chain Strategy, Research, Best Practices, Technology and Other Supply Chain and Logistics Issues  
 
 
  - Feb. 16, 2015 -  

Supply Chain News: Consumer Goods Companies Need to Up their Demand Sensing Game, Gartner Says

Few Manufacturers have Really Yet Connected the Supply Chain to the Store Shelf
 
     
     
  by SCDigest Editorial Staff  
     
 

Recently, SCDigest editor Dan Gilmore highlighted supply chain predictions for 2014 from a number of supply chain gurus. You can find that column here: Supply Chain Guru Predictions for 2015.

As promised, we then are the full text predictions from pundits Gene Tyndall, Mike Regan, George Stalk, Marc Wulfraat, David Schneider, and Chris Gopal. Good stuff. See Predictions from Supply Chain Gurus for 2015 - Full Text Version.

SCDigest Says:

It is expected that most large consumer products companies already on their demand-driven value network journey will be leveraging downstream consumption to drive supply execution through manufacturing and with key suppliers," Gartner says.

 

 

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After also summarizing predictions from some leading supply chain analyst firms, such as Gartner and IDC Manufacturing Insights, this week here we are going to again provide some additional detail with one of Gartner's "predicts" for supply chain planning.

 

In that report, Gartner say consumer goods companies will continue to get better at using POS data and near-term demand signals to improve short term forecast accuracy and replenishment plans.

Forecast accuracy, of course, remains quite an issue.

Gartner's recent benchmarking survey of key consumer products metrics found SKU-level forecast error calculated one month out had on average an error rate of 21.9%, though it fell to a 11.7% error rate at the top performing companies. For new products, that error rises to 48.3% and 34.7%, respectively.

"The results were not expected, as we did not anticipate seeing demand forecast error performance as strong as reflected here," Gartner says.

Of course, forecasts with high levels of error lead to a host of other supply chain woes, which Gartner notes include the following:

• The wrong product mix - excess inventory of some products and not enough of others

• Higher overall inventory - excess cash tied up in inventory and poor cash flow

• Increased cost and waste in the end-to-end supply chain - reactive breaks in production schedules, unplanned production changeovers, shipments from non-primary sources and obsolescence if stock ages past its shelf life date

• Service problems - if reactive execution and expediting actions or excess inventory does not cover customer orders that are different than the forecast

Gartner says some consumer products leaders are beginning to realize that, in addition to working to improve their forecasts, they also need to leverage downstream data to better predict what, where, when and how much to replenish based on what is being consumed downstream.

It says leading manufacturers "are already working closely with their key retail accounts to manage vendor-managed inventory (VMI) replenishment based on retail warehouse inventory and movements, and some point of sale (POS) data reflecting consumer pull through the pipeline. Some of these companies are using demand sensing technology to better predict the near-term forecasts based on downstream data, pattern recognition and predictive analytics, and they are experiencing improved demand projections."


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However, Gartner says only a handful of consumer products companies are piloting or already aligning upstream production and materials replenishment from suppliers for some part of their business based on downstream pull signals. In other words, few consumer goods companies have really connected the supply chain to the store shelf.

But it says that those few that have done so "have seen a decrease in inventory, more predictable supply operations and the same or higher customer service. They set inventory buffers based on product level, average daily demand, range of demand variation and supply reliability. These buffers are reviewed regularly to reflect recent patterns, rather than averaging two years of history to take out the highs and lows."

This is significant change, Gartner believes.

"Interest in better aligning near-term supply execution with what is actually happening downstream is growing - a capability Gartner calls "respond planning." It is expected that most large consumer products companies already on their demand-driven value network journey will be leveraging downstream consumption to drive supply execution through manufacturing and with key suppliers by 2018," Gartner says.

The bottom line: Use of demand-sensing technology that leverages downstream data, pattern recognition and predictive analytics will provide more accurate near-term demand projections for more consumer goods companies, Gartner says.

In addition, increased analysis of actual SKU-level demand to determine average daily usage, near-term demand patterns and range of variation will improve alignment of buffer inventory to cover demand volatility with less reactive disruption in the upstream supply chain than we see today.

As a result, overall inventory will be reduced because the mix is better aligned with what is selling. There will be less slow-moving and obsolete inventory for those products replenished based on downstream consumption. This will improve cash flow and cash conversion cycle time, and it will reduce write-offs due to obsolescence.

Gartner concludes that "Supply chain leaders need to select a portion of the business, develop the business case for change and conduct a pilot as proof of concept to becoming truly a demand-driven responsive supply chain. Once this pilot proves the business case, expand to other parts of the business to reap the full benefit potential of aligning supply execution with downstream consumption. Use this pilot to help with the change management issues of moving from a forecast-driven replenishment model to a demand-driven one."

Do you see consumer goods companies increasingly focused on "demand sensing?" What does that term mean to you? Let us know your thoughts at the Feedback section (email) or button below.


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