Predictive Analytics Takes Its Place in the Electronics Supply Chain

Supply chain volatility, stemming from demand and yield uncertainty and generating shifting lead times and product obsolescence, is something the electronics manufacturing industry must deal with on a daily basis. Because of its fast pace, the electronics sector could benefit from the application of predictive analytics to identify supply chain risks and increase agility.

A number of companies are introducing products claiming to apply predictive analytics to supply and demand risk problems and to logistics management. These tools can provide early warnings of shortages and overstocks, and, optimally, assign manufacturing tasks and shipments routing in order to reduce stock levels, increase revenue, and decrease manufacturing costs.

Predictive analytics represents the next generation of business intelligence tools. Traditional business intelligence looks backward. It provides visibility into the historical supply chain and can provide explanations of where a company is doing well or poorly. But in a fast-moving and ever-shifting landscape, relying on historical data alone is like driving a car while only looking into the rear-view mirror. Predictive analytics promises to uncover challenges and opportunities that are coming down the pipeline, providing the chance to act on them proactively.

“Predictive analytics enhance the quantitative value of raw data, allowing logistics managers to analyze current and historical facts to make predictions about future events,” according to Freightgate, a company that applies predictive analytics to logistics problems

Precogs, a Paris-based startup, recently launched its cog-Watch solution, which claims to apply predictive analytics to the electronics supply chain space. The company attributes its predictive algorithm to the historical data of a corporations enterprise resource planning (ERP) system, as well as to logistics data picked up from suppliers and distributors to identify early warning signs of component supply chain problems. This, the company says, enables manufacturing teams to focus on those components most likely to present supply problems.

Freightgate tackles the supply chain challenge with predictive analytics, but from a different angle.

When multiple orders come in simultaneously, suppliers must determine where to most effectively manufacture the components and deliver them.

Freightgate's cloud-based Freightgate Universe Platform (also known as Freightgate's Logistics Cloud Platform), which benefited from the introduction of enhanced predictive analytics earlier this year, aims to make sense of the huge volumes and diverse sources and configurations of logistics data that every company collects.

Freightgate Universe includes several tools which enable “what-if” scenario analysis to satisfy multiple competing constraints. This allows companies to manage suppliers by exception, collaborate across the supply chain, and procure global transportation services.

Freightgate's innovations build on new advancements in data aggregation and pattern recognition, and in the investments the company has made in its cloud-computing infrastructure. Freightgate claims its predictive modeling helps logistics professionals “see the future” by “providing opportunities to create better service performance while reducing operational costs and mitigating risks.”

Of course, Freightgate is one example of many companies in this space. What are your thoughts on predictive analytics? Share them below.

6 comments on “Predictive Analytics Takes Its Place in the Electronics Supply Chain

  1. Eldredge
    September 17, 2013

    I have always heard that the one thing you can be certain of is that predictions will be wrong. Of course, the key become, how wrong (or how close) wiill they be from reality. Sounds like an interesting and exciting aspect of supply chain management!

  2. ahdand
    September 17, 2013

    Predictions will go wrong when you do not analyze deep into the subject. Analysis should be done thoroughly. It should not be done for the sake of doing it. As long as its been done in a proper manner and have been analyzed at different levels, the predictions going wrong will be minimized.  

  3. Hailey Lynne McKeefry
    September 19, 2013

    Eldredge, have you ever heard the saying “All generalizations are false, including this one.” 🙂 that being said, predictive analtyics may not be perfect, but i suspect that it gets us closer to the target and any movement in the right direction yeilds good benefit.

  4. Hailey Lynne McKeefry
    September 19, 2013

    Today's systems yield so much rich information, and when it's brought together, it can yield really fruitful results. At the same time, I wonder about the cybersecurity implications of all this data being collected and stored. It seems like it would be a rich haul for some smart cybercriminal. Do you think the supply chain is thinking about this issue much?

  5. Eldredge
    September 19, 2013


       Yes. And a similar addage that I particularly like is ” I thought I was wrong once, but I was mistaken.”

        After all, where would we be without predictions? They add order to our world. Sometimes, they provide easy targets (i.e. weather forecasts).

    September 20, 2013

    Precogs ?  Was this not from a movie called Minority Report.  I hope their software is less dramatic that what I saw in that movie 😉

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