What can industry experts and advisors to policy makers do when it is known that 95% of the businesses in their industry do not have access to the latest tools and process innovations? Just think about it for a moment: if a significant majority of companies in your industry cannot compete at the most advanced level in today's global marketplace because they cannot afford the latest technology, what needs to be done?
This was one of the four main discussion themes at the regional meeting of the Advanced Manufacturing Partnership (AMP) yesterday at the University of Michigan. The AMP program was convened by the President's Council of Advisors on Science and Technology and holds these regional meetings across the US to seek out ideas and forge collaborative partnerships between industry, academia and professional groups.
A very pointed question was brought up at the meeting: this year marks the 50th anniversary of the invention of the industrial robot, but today most US manufacturers import their robots from Germany and Japan. Why? The answer, it appears lies in the priorities assigned to applied research: Germany spends 6 times more on applied research compared to the US. (The US on the other hand spends 6 times more than Germany on basic research).
So what is stopping manufacturing companies from adopting state of the art technologies which would help them compete better? From our narrow vantage point as providers of analytics tools and services, we see that something as basic (in today's world) as managing and leveraging data using advanced analytics tools is out of reach for these 95% of manufacturers. Most of them are small and mid-sized entities (SMEs) who exist in a complex ecosystem of the manufacturing supply chain.
These tools can be used for a range of activities: from implementing better designs and developing optimized manufacturing processes to supply chain management. All of these activities are predicated on the availability of large amounts of data. But data is not the problem. The real issue lies in being able to afford, use, and interpret analytics tools.
The analysis tools are expensive for SMEs on several fronts: initial purchase and maintenance. The maintenance cost comes from having to retain expert staff who can effectively use them. To solve this issue, the AMP plans on setting up "Digital Manufacturing Hubs" which would provide utility access ("pay-per use") to these tools, expertise and training on tap.
SimaFore's accessible analytics model is very much alike in spirit to this formula. Our experts will work with SMEs on a consultative basis to understand the unique business issues (for example cost forecasting, key driver identification, customer lifetime modeling etc), train and help with data management for a specific activity. Once this step is taken, building a predictive analytics model is accomplished via crowdsourcing and hosting the model is done on the cloud. The SME can deploy the model via a web interface or an app. All of this results in signifcant savings from not having to invest in tools or experts. There is only a one time investment (in the consulting cost) for addressing a specific business need. The cost for cloud computing and maintaining the model is minimal.
On a closing note, it was mentioned in the AMP meeting that 3% of US energy consumption goes to maintain data centers! But that is another article, for another day...