Thursday, February 5, 2015

A Tale of Two Factories: Chapter 5 – Studies in Change

By Patrick Weber, MESA International Technical and Education Committee member

“Is it us, or is it the technology?” Whenever MES/MOM technology is discussed, the importance of change management is emphasized. Chapter 4 of this series examined the architectural aspects of change – the importance of having a platform that flourishes with change. This chapter delves into the “soft skills”, perhaps the most difficult part of successful integration of technology into operations. Once again, we examine change at two plants: Deuxieme Botte Manufacturing (DBM) and Premiere Chaussure Industries (PCI).

Change at DBM

Brian looked over the monthly figures again; as COO, he had a problem that needed solved. While some areas of the plant were meeting asset effectiveness targets, others were not. The software DBM implemented nearly a year ago was supposed to improve the visibility of the asset effectiveness so that plant personnel could address the issues and make corrections. Brian saw the numbers in his monthly operations report, but the metrics were available on the plant floor on a real-time basis. They had instituted process improvement teams – PIT crews, one NASCAR fan suggested – to deal with the causes of downtime, but it seemed to Brian – based on the metrics he saw – that those teams weren’t all that effective, at least in some areas of the plant. The system implementation costs and ongoing support costs had been justified based on meeting those effectiveness targets.

“Are we getting the ROI we were promised from this technology?” Brian wondered to himself.

John picked up his ringing phone and before he could even say hello, he heard “Hey John - Brian. I need you to do something for me. I’m concerned that we’re not getting the value from that asset effectiveness system we installed. We’re going to be invoiced for annual support on this soon, and I just want to make sure the expense is still justified. Can you investigate and make some recommendations?”

“Uh – Hi Brian.” As a Lean Facilitator and Industrial Engineer, John knew several techniques he could apply to answer the question. “I think there are a few approaches I might use to help come to a definitive conclusion. I might like to blend problem analysis, kaizen, and value stream mapping for this evaluation. I’m going to need several other people – perhaps a machine operator, a production supervisor, a maintenance tech, a PIT crew leader, an accountant, an engineering rep, and someone from IT. Could you help me secure those resources for perhaps 3 days?”

Brian and John did the necessary haggling and horse-trading with supervisors and managers until they finally had the necessary people, place, and agenda for the event. John’s planning and pre-event preparation allowed the analysis to be completed in two days instead to the expected three. Here’s some of what the evaluation team learned:

The technology was not delivering the expected return on investment. While the process changes implemented did provide a positive net present value, they did not meet the corporate standard for payback period or rate of return.
Process changes to improve asset performance were not effective:
Many equipment operators weren't using the system. “It doesn't tell me anything”, one stated flatly.
Some downtime causes required engineering changes to correct; there were no processes in place for PIT crews to engage engineering.
Supervisors were managing to metrics obtained using methods other than the automated system.
Some supervisors paid lip service to the new effectiveness metrics, but still managed based on production counts.
There were multiple opportunities to integrate information from various systems to reduce paperwork, eliminate custom software applications and spreadsheets that would further enhance the value of the technology and improve ROI.
At the report-out, the primary recommendation from the evaluation team was that DBM continue to use the software in spite of the discouraging financial metrics. Some organizational changes would be necessary to maximize the value of the technology investment. Additional recommendations included a laundry list of applications and spreadsheets that could be eliminated through additional integration efforts plus a number of process improvements as depicted in the future state value stream map. After he heard the recommendations, Brian thanked the team for their efforts, but left them with yet another question…

“Didn't we know that we would need to change the way we work after we implemented the system? I really thought we had planned for these kinds of changes. Were we not ready of the technology, or was the technology not ready for us?”

Change at PCI

As he looked at the walls upon which once hung the various line product counts and pace setters, Joe (VP of operations at PCI) recalled the conversation which initiated their removal.

“Organizational change is hard work”, Joe remembered the MES/MOM consultant Steve saying. “Far too often I've had clients who believed that just implementing the technology and making a few process changes would be sufficient to get the promised ROI. Too bad it doesn't work that way. You know, people were able to accomplish their work before the technology was installed – they had procedures and ‘rules of thumb’ that allowed them to be successful enough that the company could turn a profit. Often these things were so ingrained within the culture that people couldn't see the benefits of the technology. Eli Goldratt calls these ‘local optima rules’ – because people lack a complete understanding of what’s happening within the entire production process, they implement methods to optimize activity within their scope of control. These practices are so strongly tied to the plant culture that they can inhibit an organization from gaining benefit from their systems.”

Joe could see this was a hot-button issue with Steve – the passion was evident. “Could you give me an example of ‘local optima rules’”, he asked.

“Sure! Let’s look at the MOM system we’re putting in. Without the technology, the management metric is total production per shift. Do you recognize all of the unwritten rules that go along with this metric? For example, what happens when multiple lines are producing for a specific order and the order quantity has been satisfied? I know I’m over-simplifying here, but this is just an example for insight - when you’re managing to production per shift, the line operator just keeps on producing. Her other option is to become idle unless another product is scheduled and she can change over the equipment. So what do you think would happen if her supervisor found her idle?”

Joe considered for a moment. “I think I see what you’re getting at. The operator over-produces either because she doesn't know the order quantity has been filled – incomplete knowledge, or she knows but also understands that she’s not being paid to be idle. She can’t be faulted if she meets her per-shift quotas. She optimizes based on her ‘local’ understanding of what’s going on in the system.”

“Goldratt has an axiom: ‘Technology may only bring benefit if and only if it diminishes a limitation.’ He says that in order to obtain the benefit, you must not only understand the limitation and how the technology reduces the limitation but also understand the rules that allow operations with the limitation in place and the new rules once the technology has been implemented. Change management needs to go beyond business processes – it needs to dig deeply into the culture as well. If you say you are changing management metrics, you cannot leave the old metrics in place” Steve said as he gestured toward the production counters. “They are entwined with the culture and the local optima rules – as long as those remain, people will not embrace the new rules which allow them to beneficially use the technology.”

Joe remembered the capital request for installing the counters some years back. “Sunk cost”, he thought with a sigh. He could see Steve’s point – those counters would need to come down.

“So is that what people mean when they talk about ‘technology adoption’?” Joe asked.

“’Technology adoption’ is an implementer’s perspective. This is organizational change – it cannot be ‘managed’ into place, it must be led. Can I tell you a funny story about leadership?” Steve asked.

“Sure!” Joe was always interested in anecdotes – you never knew when one might come in handy.

“My wife and I were at a funeral with several other out-of-town people in attendance. As we were driving between the cemetery – where the gravesite service was held – and the church for the after-service gathering, my wife remembered that a relative had recently purchased a home near the church. She had wanted to see it, so she asked me to take a slight detour. We found the house down a residential cul-de-sac and stopped briefly in front of it. As I looked in my mirror, I noticed six other cars behind us stopping in front of the house as well! Without my knowledge, these folks had decided to follow my car to the church. We had a nice little parade! But here’s the point: if people think you know where you are going, and that you know how to get there, they will follow you. It is human nature.”

Joe chuckled – thoughtfully.

Two Worlds

The term ‘change management’ is not sufficiently comprehensive; change must be led as well as managed. DBM uses several change management techniques, but the company is still not getting the expected value from its technology investments. The management team at PCI is discovering that the cultural aspects of change are significant as they consider the gap between “as-is” and “to-be”. As manufacturers consider MES/MOM technology, they must also consider how they will deal with change.

Thanks for reading this installment of “A Tale of Two Factories”. If this is the first chapter you've read, you can check out the previous chapters beginning with Chapter 1 by clicking on the links.
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