In this week’s mini-sode, we talk to D4M International COO Jean-Yves Durocher about the origins of the “need for speed” for data in manufacturing and how it compares to the current trends of data (lead by the AI revolution) today.
But, before we hear from JY, let’s hear Alan’s thoughts on origin of the data craze:
Alan: Jean-Yves, you’re kind of an advocate of the topic of data, especially regarding this idea of digitalizing. Now, one of the things that digital transformation promises and provides is lots of data. To Chuck’s point, in the past, we either didn’t have good data or we had a lot of data, but had no efficient or effective way to use that data.
Alan: So as part of the digital transformation process, it seems like a lot of companies are getting into some real time monitoring because there are now sensors that can provide some real time insights in the production processes and the customer orders, etc. On top of that, there’s also a trend in the industry to get to a point where you’re making some data driven decisions that aren’t just based on a limited amount of data. By having more of it, you’re able to make finer tuned decisions.
Alan: Jean-Yves, what do you think of the idea?
Jean-Yves: You’re absolutely right. I think we like to think digital transformation, as something that just happened the last quarter or it started last year. The reality is that the world has been going through digital transformation for the last three decades, if not more.
Alan: You’re saying it is not a new process, but the speed of it is up right now.
Jean-Yves: Correct. The speed is picking up! But if you look at it today, in today’s context and how it is affecting different industries, the foundation behind this moment of manufacturing is still being able to process data from many sources.
Jean-Yves: Regardless of the industry you’re in – if you’re manufacturing, banking, insurance – when you look under the hood, it always comes down to having sets of highly integrated processes to collect good data in a timely manner.
Jean-Yves: So, this has always the foundation to getting into more sophisticated, advanced manufacturing or for an insurance company, having the ultimate Ui/UX customer experience. Again, when you look under the hood, it always comes down to collecting data, processing data, and – for lots of corporation – the data now is coming from many, many sources; it could be coming from your shop floor, it could be coming from your vendor, etc.
Jean-Yves: Obviously, the systems have to be a fully integrated ecosystem. You got data coming from your vendor. If you work in an EDI Mode, your vendor – by definition – have to be more and more partners as well as a crucial parts of your operation and manufacturing strategy. So, you’ve got your partner on one side, the supplier, and you got your clients.
Jean-Yves: If you’re a B2B environment, obviously it’s a business to business; so connectivity with your partner could be a nice chain of process with data operating in a seamless environment. But, this is ultimately the foundation of digital transformation and – at the end of the day – the process is not just “technology for technology”. At the end of the day, there has to be business value and it has to fit in the corporation goals. No matter where it fits in your operations, you want to have the best customer experience or the cheapest product in the market.
Jean-Yves: All these processes have to be lined up with business objective and there needs to be many tools in the arsenal, AI being one of them. AI is the one technology that brings this process right in our face, because the ultimate AI engine will most likely process data from many sources. Nowadays, you’re dealing with structured data and the whole concept of unstructured data that today we can process. So, all this comes down to the top of the pyramid, which is the AI.
Jean-Yves: But at the end, like Chuck was saying, your AI engine will still be a beast to crunch data. So, if the data is not right or collected right, you’re not going to go very far regardless. And that hasn’t changed over time.
Chuck: Just to add to what Jean-Yves is saying, what I’ve seen in the AI space these days, (since that seems to be the latest buzz and craze in technology now, right?) is that there’s a lot of people out there just trying to get attention that are talking about AI based on all of its potential. “You can use it to do this and use it to do that. You can use it to write your proposal to your girlfriend, you can use it to write crazy stuff!” That’s what we’re seeing out there, which – to me – is a lot of noise.
Chuck: I think if one piece of wisdom I could give to someone who’s watching this video is like, look at getting your data right and break it down by use case. One of the things that I’m seeing is valuable out there is that companies are saying, “okay, let’s look at it on a use case basis, because a, there’s more isolated data around that use case or process, and b, they don’t have as much data right to deal with, and it’s more of a controlled environment.
Chuck: So if you stop and think about it, automation period started – like Jean-Yves said – 30, 40, 50 years ago, by basically asking the question “how do we utilize these computers for the good, for the better”, right? We know they’re fast, so that drives efficiency. And now we’re getting the point, where we’re going, “okay, now how do we take it to another level of speed?” And again, it all boils down to data.
Chuck: The encouraging thing for me is that some of the software providers out there are keeping it more on a simple level to where they can really prove the value of that technology, as opposed to just trying to throw technology at you. Because we all know if a vendor comes in and says, “here’s some fancy whiz bang technology”, if you don’t see the value, you’re not going to buy it.
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