Dejå vu all over again?!
The last posting started the buildup to using data (from where ever) to drive innovation, clarity and transparency, business model/economics, institutionalization, and benchmarking for industry in general and, ideally, for green manufacturing as well. This data should include information on what any specific process or system is doing, what it is consuming or emitting, what the impact per unit process output is, what is the efficiency of conversion of resources into product, what it the efficiency of the cycle, how does one system or process compare to another doing the same thing, and how does the overall performance match up with competitors in the same market, company, division, or factory, and so on.
The upshot of the discussion is that it should be possible to close gaps between what is needed to understand the items above and what is available. Further, the idea is to leverage the capabilities of big data and the digital views of an enterprise to help close this gap.
First, it is helpful to try to understand what big data and digital enterprises actually mean and then how they relate to our conversation here. A web search for the term “digital enterprise” turns up a lot of product pitches and some useful definitions. For example, WhatIs?TechTarget has a posting which offers the following definition - “A digital enterprise is an organization that uses technology as a competitive advantage in its internal and external operations.” The “technology” is referring to information technology. This is rather broad.
Let’s take a look backwards to see what can be learned. In November 1994 Fortune magazine published an article by Gene Belinsky titled “The Digital Factory.” This turned up the other day when I was rummaging through some old files in my office. The article predicts a range of impacts that the digital factory will have from customization of products “literally in quantities of one while churning them out at mass production speeds” to allowing supply chain integration, micro factories and breathing new life into the “beleaguered U.S. machine-tool industry.” Referring to it as “soft manufacturing” it even proposed that the most astounding effect could be on employment where it “could stabilize or even increase the number of production-worker jobs in the U.S.” The article gives a number of excellent examples where this is being employed circa 1994 and the improvements realized and highlighting that “software is becoming more important than hardware - more important than machine tools - in American factories. And smart humans are back, replacing dumb robots.” It even predicted the importance of 3-D printing for prototyping.
Well, the first part is right … software became more important than machine tools - in the U.S. at least. Since this report the U.S. machine tool industry has essentially collapsed and in its place are builders from Japan and Germany with machines of incredible sophistication. They figured out that software AND the machine tool was a powerful combination. We didn’t. The second part is not. Robots staged a comeback, thanks to capable planning software, better cheaper sensors and efficient motors and controllers combined with a better understanding of where they work best and with what tooling systems. Pick up any trade magazine or “Google” robots and you’ll see an amazing array of co-worker robots doing sophisticated tasks. And productivity in the U.S. is up (see the post in July 2013) but manufacturing employment has not keep up with growth.
Is this current buzz about digital manufacturing just another Fortune 1994 article that, 20 years later, will look equally out of touch? Not likely. The downfall of the last prediction was that as software was growing in importance and capability, the “network” (or what was then connecting things) was infantile compared to what we now enjoy. Ditto for data flow from machines and systems. Sensors on production machinery (not just the position feedback data for machine tool axes or robot arm positions) were expensive, intrusive, slow to respond and often measured things that did not truly reflect the process or element being observed. One could go on at length about this but we’d be way off the path.
Not so now. The examples cited in an earlier posting on the internet of things showed systems communicating an impressive volume of data at high rates - enabling essentially real time behavior and response. The companies that make machinery that link into these systems (the folks that picked up where most U.S. machine builders stopped) learned how to employ the better cheaper sensors and efficient motors and controllers combined with a better understanding of where they work best and with what tooling systems that made robots more pervasive.
So, where does that leave us with respect to greening manufacturing and sustainable production?
Maybe to focus this a bit, let’s go back to the deep well of knowledge provided by McKinsey! In a May 2014 article titled “The Seven Traits of Effective Digital Enterprises,” authored by T. Olanrewaju, he and his colleagues go over examples of “transformational” traits of the successful digital enterprise. These are, in usual McKinsey style, rather high level and inspirational rather than execution oriented. But there are some nuggets of practical ideas - where practical here means “what can we do on the shop floor?”
One is “measure digital value not digital interactions.” This is the digital interactions are “digital-washing” equivalent to "green washing." Results or progress against a benchmark or a fiducial is what counts. But first you need the yardstick.
Another is “don’t accept historical norms; question the status quo; create a plan covering every function, product, business unit and location.” This is none other than the “Google earth view” of manufacturing identifying the elements, interfaces and value at all levels - leave no stone unturned. And, more over, it is looking for effectiveness and not only efficiency. Doing the suboptimal or wrong thing well is not a substitute for doing the correct thing and doing it well (some of this was covered in earlier postings). The last one to note (and please do read the whole article at the link above to get the full story) is “follow the money.” This addresses the “reduced impact for higher value” that has been trumpeted in this blog for some time. But, too often, follow the money is replaced by “follow the energy” and ignores other important consumables - materials, time, water, even labor. Energy is important for sure but many other econsumables are important too - maybe more important in some situations!
The report states “Many organizations focus their digital investments on customer-facing solutions. But they can extract just as much value, if not more, from investing in back-office functions that drive operational efficiencies. A digital transformation is more than just finding new revenue streams; it’s also about creating value by reducing the costs of doing business.” Wow. We can use that. Do a “search and replace” here for digital investment, back office functions and finding new revenue streams replace them with sustainability initiatives, manufacturing processes and systems and reducing utility bills, respectively. And insert “environmental” between “costs” and “of” in the last line.
Or … following all the substitutions it looks like this.
Many organizations focus their sustainability initiatives on customer-facing solutions. But they can extract just as much value, if not more, from investing in manufacturing processes and systems that drive operational efficiencies. A digital transformation is more than just reducing utility bills; it’s also about creating value by reducing the costs of doing business. And, digital enterprises should be able to do this better and insure measurable progress.
But there is also a “customer-facing” aspect to this of course. That’s where the circular economy comes in. Every enterprise has customers and is a customer to some other enterprise. That’s what’s shown in the Ricoh Comet Circle and, more abstractly, in the circular economy.
It is necessary to explore this with a circular economy in mind … starting with how to inform the customers our enterprise serves as well as those to whom we appear as the customer. And this has to be done both external to the organization as well as inside. We’ll continue with this in the next posting.
