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Perfecting the Supply Chain Balancing Act

Achieving the perfect balance of supply and demand is every supply chain professional's dream. Unfortunately this is a dream that rarely comes to fruition — at least within the current command and control reactive supply chain paradigm. Let's face it, supply chain decisions driven by long-term forecasts are inherently flawed.

But there is hope. Demand-sensing is an emerging model that allows companies to take a more proactive approach to fulfilling their supply chain demand. According to {complink 7039|AMR Research Inc.}, demand-sensing is characterized by the “translation of downstream data with minimal latency to understand what is being sold, who is buying the product, and the impact of demand-shaping programs.”

Unlike current upfront forecast-based supply chain models, a sense-and-respond supply chain takes actual consumption data and continually adjusts inventory based on near real-time demand signals. When properly executed, this model dramatically reduces the need for JIC (just-in-case) inventory, lowers obsolescence risk, improves supply chain sustainability, and increases return on investment. The larger the number of supply chain nodes in a company's supply chain ecosystem, the higher degree of communication and collaboration needed to make productive use of sensing data.

The benefit of the sense-and-respond approach is exemplified by Coca-Cola's Freestyle soda fountain machine. Introduced in 2009, the Freestyle features over 125 different Coca-Cola drink products, allows consumers to customize flavors, and has about the same footprint of a traditional beverage dispenser. How could a machine like this possibly be profitable?

It uses electronic links to detect and transmit supply and demand data, including brands sold, time of day of sales, troubleshooting information, and service data, to both Coca-Cola and the unit owner. While many people think of this machine as a delivery mechanism to improve the quality of the product (which it does), it really helps Coke decide which flavors to market and bottle. It is a great example of sensing and responding to demand right at the source.

Of course, applying this method to the supply chain for aerospace flight systems or even high-volume MP3 players may not be quite so straightforward, but there are techniques that can — and should — be integrated into the high-tech supply chain.

Sensing and response tools have existed for quite some time. A kanban system is a form of sensing and responding. The challenge with Kanban, for example, was establishing the visibility and collaborative framework between supply chain ecosystem partners to take advantage of this information. The next step is to hone the supply chain interactions and connectivity as sharply as possible in order to be able to adapt supply levels as consumption inputs are received.

Another key to establishing an effective sense and respond supply chain model is a strong command and control framework. These approaches are not mutually exclusive; they must be executed in tandem.

Understanding the value of a supply chain paradigm built around actual consumption — rather than forecast — is fairly easy. Transforming age-old processes and mindsets isn't. The best place to start is by having a conversation with your supply chain ecosystem partners. With their buy in, creating the collaboration necessary to use this data efficiently may be easier than you think.

3 comments on “Perfecting the Supply Chain Balancing Act

  1. Barbara Jorgensen
    February 7, 2012

    Great information, but I have a question: would widespread application of demand sensing everntually render distribution moot? What role does the channel play in this model?

  2. Gerry Fay
    February 7, 2012

    Barbara,

    Great question. Given our role in the electronics equipment supply chain, where we need to be agnostic when it comes to electronic interfaces and out 100K customer base, we are uniquely qualified to manage both command and control and sense and respond supply chains.

    The core values that customers depend on distribution for don't change in this model. The just make us better to respond to customer wants.

    Gerry

  3. DataCrunch
    February 7, 2012

    @Gerry – Another great article.  I would just like to add that demand-sensing can complement demand planning by going beyond the traditional approach of forecasting based on just historical sales data.  The field of analytics and specifically predictive analytics is constantly improving and innovating, especially in important areas as the supply chain network.  New and better pattern recognition and mathematical algorithms are being developed to interpret a wide array of varying demand signals that can help retailers and manufacturers gain more accurate near real-time insights into important activities.  These demand signals can include what products are selling well and which ones aren't, what products are popular at which retailer, where products should be located at the retailer, etc. 

    In demand-sensing, volumes of data from manufacturers, retailers, suppliers, etc., are analyzed all to help companies better determine what customers will order and automatically crunching all these demand signals and volumes of data to basically provide daily forecasts.  The sense-and-response approach you mentioned utilized by Coca-Cola is a great example.    Demand-sensing can definitely be a competitive advantage on how companies manage their supply chains, and I expect we will be hearing much more about this methodology in the years to come.      

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