How many people will be running your plant?
Process manufacturers have to deal with basic head count challenges. The answer may be fewer people than you think, but how do you find the right number?
The question of how many people are necessary to run a process plant is not a new one. Producers in competitive industries have been trying to figure out how low they can go since the earliest days of automation and probably before. It has taken on new significance in recent years as companies are dealing with the great shift change as baby boomers retire and millennial workers take their places.
Naturally, the universal answer applies: "It depends." Some of the relevant factors include the nature of the plant itself, its level of automation, and the types of people that make up the immediate workforce.
The conventional wisdom says that qualified engineers and operators who are happy to work in a typical process plant environment, say an oil refinery for the sake of argument, are going to be fewer in coming years. There's no doubt that people will be available, but the ones who have relevant education and training will be scarce. Companies may be able to outsource some of that need (see sidebar), but having the right people on-site, 24/7, will be a challenge.
To answer the question, or at least fill in some of the qualifications, Control Engineering turned to two industry experts who spend a lot of time thinking about such topics. Stan DeVries is senior director, solutions architecture, and Peter G. Martin, PhD, is vice president, business value consulting, both with Schneider Electric. Control Engineering contributor, Peter Welander, asked the questions.
CE: So, how many people does it take to run a plant?
DeVries: Some of the customers I'm dealing with now are investigating that question for several reasons. It's more than simply cost. People have been talking about the "great crew change" for a long time. But this is the first time in my experience that we have hard data from a customer, driven by their human resources managers, saying that when the aging workforce leaves, the new mix of people, whether they're hired or contracted, won't be the same number. It will be far fewer, and they won't be the same kind of people who will take on the same ways of doing work. That's not just knowledge going out the door, it's a whole culture change. Everybody's dynamic differs, but they're saying that it takes so many years for their wave to completely go, and it will take them the same number of years for them to get ready to do whatever they think is the right thing to do. It's not just people leaving. It's not just a productivity issue, but asking a deeper question: What can the workers of tomorrow do to run a plant safely and effectively?
Now, for petroleum refiners, one of the KPIs that Solomon Associates has people subscribe to is a personnel performance index. You take the number of people you have and compare it to some sort of business measure, unfair as it might be, that you can benchmark against others. That's dangerous with gross benchmarks, but it's an attempt to establish a productivity measure and determine how that's shifting from year to year.
CE: So regardless of the relevant measures, we have to find new ways to do things to replace the people who won't be available?
DeVries: Yes. It extends to the maintenance of the technology. So maybe you say, "I have the answer-I'm going to throw more technology at the plant." You have to be careful if you're assuming that it takes a given number of highly paid bodies to do that, whether you're paying somebody else or your own people. All that factors into the cost and productivity.
Martin: I just completed a study as part of a talk I was giving on the differences of the characteristics between the baby-boom generation and the millennial generation, because to a large degree, it's not going to be Generation X people that will be replacing the baby boomers, it's the millennials. Some of those generational characteristics support Stan's points.
Baby boomers had the tendency to learn things from the view of wanting to know everything down to the last nut and bolt. When we learned computer science, we learned how a computer worked-how an arithmetic logic unit worked, binary and-gates, or-gates-it's just the way we are. Therefore when baby boomers are running plants, the run them from the perspective of the way they learn. If everything goes wrong, the baby boomers know how the plant runs, they know it down to the last valve, and very often, they can bring upset conditions into a steady state because of they way they learn.
Millennials don't learn that way. They don't learn how the tool works down to the nut and bolt, but they know how to use the tool better than the baby boomers. Millennials are really good at technology and very comfortable using technology, but they don't have the deep need that baby boomers do to understand every nuance. Baby boomers panic when they think that there won't be anybody left who understands how to change the rivets on a distillation column. The good news is that the baby boomers came before the millennials, so a lot of the base knowledge that the baby boomers developed has been embedded into the technology.
When you think about it, the technology base that the millennials are walking into may just be perfect for the characteristics that they're bringing to the table. They're very good at collaborating across organizational structures, they don't need to know everything about everything, they're very connected, and they're oriented to immediate gratification so the feedback from a real-time engine fits right into the millennial mind-set. A lot of the tools that baby boomers have been developing for the last 35 years are really better suited for millennials to use than baby boomers. Millennials have the perfect mind-set to pick up on what the baby boomers put in place. That might mean, going forward, that you can do things in plants with far fewer people, to the same degree of efficiency and proficiency, because of the background work that's been done for the last 35 years.
DeVries: I'll give you an example of one of the questions that people are re-asking: "How many control loops per operator?" The answer is always, "That depends." You have to ask who the operator is, and what people and work processes are supporting that operator. People don't think through the problem. They assume that nothing else changes and that maybe there's some mystical new kind of displays and alarms. That's a wrong and dangerous way to think about it. You can't assume that more loops can be handled by a single operator if you think they're going to be doing the same kind of work and be the same kind of people.
Martin: We believe that some of the KPIs, such as productivity and others, are valid for keeping your fingers on the pulse of things, but the truth is, the objectives that these producers and manufacturers have is to maximize the profitability from their operation. The fact of the matter is that it should not be reducing headcount. It should not be productivity in the traditional sense. It should be asking what is the exact mix of technology and talent that I need to optimize the profitability of what I'm doing. In some operations, the number of people may go up because they're more craft-oriented operations and they don't have the degree of scientific experience, working in specialty chemicals and industries like that. Other operations are very scientifically driven and may need fewer operators per output and unit of profit.
The danger is blindly following a couple of KPIs that can max out, while the overall profitability of the organization declines. There's no easy answer to this question. There's a lot of opportunity, but the opportunity should be strictly aligned with the business measures relevant to the business in question, and the objective should be to maximize the profitability of that operation.
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