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2 years ago
How Predictive Analytics Can Fuel Innovation for Manufacturing

 

Industry leaders like to use the term “culture” to demonstrate the uniqueness of a business and to point out how, while products may be superficially imitated, can never be replicated by competitors because of this “culture” thing. What defines a culture is complex and we are not going to get into that here. But I would like to highlight that one of the facets of business culture is openness to innovative ideas and processes. The great decline in U.S. manufacturing started a couple of decades ago primarily driven by access to cheap overseas labor. Unfortunately this shifted the focus for manufacturers from innovation to cost control.

The good news is that many experts believe that this fixation with cheap labor is coming to an end as new ways of manufacturing are emerging, new technologies for product development are breaking through and the spirit of innovation is making a rebirth. Steven L. Blue in his new book American Manufacturing 2.0 (Praeger, 2016) considers innovation as one of the seven core business values which will help re-energize this beleaguered industry. He defines two key qualifications that innovation can be measured on:

  1. Do you know what your customers want?
  2. How can you provide it to them profitably?

Ultimately companies that are truly innovative know the answers to these questions. They know what is required to answer these questions. The last few years have shown how many companies have understood technologies such as predictive analytics and big data can be harnessed to answer the first question. Recommender engines from Netflix to Amazon have mastered how to present the most relevant products to their customers to increase their propensity to buy. But predictive analytics goes beyond recommendations.

Knowing what motivates your customers by analyzing what they say in unrelated forums (such as social media) may sound creepy, but it does help business truly understand what their customers want. Traditional manufacturers like Ford are spending millions to do this.

A less sexy – but equally valuable – application of predictive analytics is in price or cost forecasting. If you are a supplier of commoditized products to a larger manufacturer, for example, you are typically locked onto a fixed price per piece contract that may run several years. However you know that your costs are not fixed. If you are buying polypropylene to make your piece, your raw material cost depends on many factors that are not under your control. But that does not mean you cannot intelligently estimate (i.e. predict) these costs over the term of your contract. Predictive analytics can help in a significant way with this.

Fortunately we are seeing a slow but steady increase in the awareness within the industry of such game changing innovations. We are also seeing a surge in the number of manufacturers who have successfully applied predictive analytics solutions in their business at our annual PAW-Manufacturing conference.

Author Bio:

Bala Deshpande, Ph.D. (Carnegie Mellon), MBA (University of Michigan), is the founding partner at SimaFore, a boutique consulting company that focuses on providing custom analytics solutions for manufacturing, marketing and non-profits.

Dr. Deshpande’s has two decades of experience in using analytical techniques. His first exposure to predictive models and analytics was in academia, in the field of biomechanics – for identifying correlations and building regression models to predict muscle forces based on electrical activity in muscles. He began his career in the industry as an engineering consultant at EASi Engineering, following which he spent several years analyzing data from automobile crash tests and helping to build safer cars at Ford Motor Company. He has been actively involved in promoting information theory based analytical techniques for a range of applications from performance measurement in organizations to healthcare. He is an active blogger and is currently wrapping up a book on Predictive Analytics and Data Mining to be published by Morgan Kaufman.

He is currently the Co-Chair for Predictive Analytics World – Manufacturing, Chicago.

One thought on “How Predictive Analytics Can Fuel Innovation for Manufacturing

  1. Pingback: State of Manufacturing Technology: Predictive Analytics, 3D Printing, & VR

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