Conversations: Factoring in Data Science in Factories

Remember the Discovery channel show “How It’s Made? A lot has changed since then…

Pretty cool, huh? For the longest of times, this show was one of the few insights that we get into the wide world of manufacturing and, well, making things. Tech and industry news always gravitates to the industries that are the “coolest” or “most innovative”. As a result, sometimes it’s easy to forget that there is still a massive industry dedicated to making the products and tools that we use in our daily lives.

To shed some light on the world of manufacturing, and how it’s changing to respond to innovations in data science and predictive analytics, we reached out to our friend Kasim Ahmad at FactoryFour to hear more about how they are enabling manufacturers across several industries to manage production with the full power of modern technology!

Humanlytics: What’s the industry standard with regards to data science and predictive analytics?

FactoryFour: Excel, and that’s charitable. We’re a very traditional industry, so you still see the typical overuse of Excel for almost every business application conceivable.

H: How do you see your industry adapting and changing in response to the rise of data science and predictive analytics?

FF: At some point, the entire industry is going to have to bite the bullet and start spending a LOT more money on software. Like I said, Excel is really the most that people are using on the tech side, and of course the standard years-old enterprise solutions. That’s part of what we’re doing at FactoryFour — equipping modern manufacturers with a future-proof tool that will help them take control of their processes for years to come.

H: Are you “changing the game” in any particular way, especially with regards to using data science/predictive analytics?

FF: Real-time data tracking! It seems basic and maybe even simplistic, but the biggest thing that we’re doing that is a radical innovation is simply tracking and analyzing data as it is made available in real-time from the factory floor.

H: How do use data science and predictive analytics to make that happen?

FF: Ultimately, just like any product that uses data science or predictive analytics, it may be easiest to think of our tool as a little super smart data analyst who lives inside our software, but has a real-time feed of all factory floor incoming data. Basically, it’s just taking the standard data analytics process, and speeding that up using standard analytic tools and procedures.

H: What tools do you/your company use for data science and/or Predictive Analytics?

FF: Chartio!

H: How can businesses like yours use data science to make products/services better and more accessible for the average consumer?

FF: As with almost any industry or business — data science just improves almost every aspect of the production and delivery process. Raw numbers and real-time feedback allows manufacturers to make rapid-fire and agile changes to their processes to make their own systems more efficient. What this results in is a consumer getting a better product faster.

H: Do you have any personal thoughts on the future of data science, machine learning, predictive analytics, artificial intelligence, or anything like that?

FF: Nah — but I’m optimistic about the direction that our own industry and the others surrounding it are heading, and I’m looking forward to seeing what the future holds!

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