The Factory of the Future is Fueled by Data
But in the background, big data and data analytics has been gradually building capabilities in another critical part of the enterprise – the factory floor. Data-driven transformation is playing a huge role in moving to the factory of the future (which actually is here today).
That’s the word from Justin Hester, senior researcher in the IoT Lab at Hirotec Corporation, a global manufacturer headquartered in Hiroshima, Japan. Hester recently spoke with Dana Gardner as part of the BriefingsDirect series, noting that “manufacturing has been very good at collecting data…. a lot of data has been there for years; for decades.” At the same time, many manufacturers simply found the volumes of this data – emanating from production systems, from tools, from equipment and from applications – has been too overwhelming to contemplate. “The challenge we’ve had is bringing in that data in real-time, because the amount of data is so large,” Hester days. “How can we act on that data quicker, not on a day-by-day basis or week-by-week basis, but actually on a minute-by-minute basis, or a second-by-second basis? And how do we take that data and contextualize it?”
Moving from the simple gathering and reporting of data and applying it to broader analytics with implications for productivity and innovation is still too huge of a leap for many manufacturers. “It’s one thing in a manufacturing environment to say, ‘Okay, this machine is having a challenge,’” Hester illustrates. But it’s another thing if I can say, “This machine is having a challenge, and in the context of the factory, here’s how it’s affecting downstream processes, and here’s what we can do to mitigate those downstream challenges that we’re going to have.”
Hester sees Internet of Things (IoT) initiatives as delivering value in this expanded context. “The analytics, the real-time contextualization of that data that we’ve already had in the manufacturing area, is very helpful,” he says.
We’re still in the early days of seeing data applied to build and run the factory of the future – what many call industrial analytics. A recent survey of 151 analytics professionals in the industrial sector, conducted by the Digital Analytics Association e.V. Germany (DAAG), finds 15% view industrial data analytics as a crucial factor for business success today, while 69% think it will be crucial in five years. While 68% say they have a company-wide data analytics strategy, only 30% have completed actual projects so far.
The three main emerging applications of industrial analytics are related to predictive and prescriptive maintenance of machines (79%), customer/marketing-related analytics (77%) and analysis of product usage in the field (76%), the DAAG survey finds.
Hester says it’s important to build industrial analytics capabilities incrementally, and it’s going to take time. “In manufacturing areas, there’s been a lot of delay, confusion, and hesitancy to move forward because everyone sees the value, but it’s this huge change, this huge project,” he told Gardner. “At Hirotec, we’re taking more of a scaled approach, and saying let’s start small, let’s scale up, let’s learn along the way, let’s bring value back to the organization – and that’s helped us move very quickly.”
One technique to drive the impact of data analytics home is what Hester calls “the Tuesday Morning Meeting. We talk about this idea that in the morning at a manufacturing facility, everyone gets together and talks about what happened yesterday, and what we can do today to make up for what happened yesterday.” The goal of data analytics is to “get the data to the right people with the right context and let them make a decision so they can affect what’s going on, instead of waiting until tomorrow to react,” he adds. “It’s a huge step-change. We’re really looking at it as how can we take small steps right away to get to that larger goal.”
The power of data has visibly reshaped today’s office, and the roles of knowledge workers. Now, the manufacturing side is poised for data-driven transformation as well.