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Why can't manufacturing intelligence systems be more like Yelp?

August 26, 2015

This blog originally posted on Jim Gavigan's LinkedIn page here.

 

Whenever I go out of town and am hungry (or frankly, even when I am in town and

hungry), I search Yelp to find a good restaurant. If I want to find a reasonable priced Italian restaurant, within 5 miles, open now, and with good reviews the last 3 months, I can just put all of that in my search criteria in, do a little filtering, and Voila', I get choices, nearly instantaneously. 

 

If it is that easy to find a restaurant in a strange town, why is it not that easy to find the information that I want in my factory about how well it is performing? Why can I not immediately understand what is going on in my business by punching in a few quick queries on my phone? It just seems strange to me that I see engineers, operations managers, directors, and executives at our customers use their phones or computers to find all kinds of information on the web about whatever topic that interests them, but yet, they have to call someone in IT to run a query, scrub the data, and hopefully get some reasonable facsimile of what is happening on their plant floor(s). In most cases, the data has been collected for years! It also isn't like the technology isn't readily available either. OSIsoft, Rockwell, Wonderware, Transparra and many others offer mobile solutions for their data gathering suites. For some reason, people haven't found it valuable to shape and organize the data from their enterprise and make it available on mobile devices, even though it is data that is time-series or relational in nature - not in an unstructured form like Yelp. It just shouldn't be that hard!

 

When I was at OSIsoft, I used the Yelp analogy a lot, although I used it to explain the power of AF (asset framework). I would explain it like this: Imagine, if you will, something that gets data from Yelp, Urban Spoon, Google, Chow, Foursquare, and Facebook and gives you a rudimentary interface to parse all of the data and make some sense of it. That is what the PI system with AF and OSIsoft's client tools is. You get data from every source in your organization, and get the most information possible, and there is at least one client tool (or multiple) that can get you what you need. Maybe the client tools aren't exactly what you need, so OSIsoft gives you the ability to write your own apps on top of the system. However, data can and should be organized to be consumed easily. Again, the goal is to turn data into dollars. Context is the first step.

 

It seems to me that if we can get reasonable data on Yelp of pertinent restaurants and other establishments, we should be able to get our manufacturing data in the same manner, just as quickly, and just as accurately. So, why aren't we doing that more in the manufacturing world? Why aren't we doing it with utilities' operational data? Why not other types of operational data? It just seems like it would be so valuable to do so, and the data is there, just often in disparate systems - but it isn't like it can't be put together. It just isn't being done because I still believe people are struggling with quantifying the value of doing so. Why? Why is it that hard to quantify? What would your people do if they could ask the data any question they want and get an accurate answer to the question they ask? It isn't that the technology isn't there. It just seems as if we can't afford not to do this. I will write more on why I think companies are struggling to quantify organizing data for better analysis in future posts.

 

 I would like input from the field on these questions, so please respond…

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