Inside Digital Performance Management: Driving Manufacturing Efficiency with Digital Innovation

Written By: Craig Melrose
  • 10/28/2021
  • Read Time : 5 min

Since the beginning of manufacturing, companies have tried to drive throughput while lowering costs. In other words, to create business impact and world class performance through continuous improvement. There is nothing new here except digital innovation, but digital is a true gamechanger.

For manufacturers, maintaining production resiliency in the face of disruption and volatility means driving large-scale digital transformation across the enterprise. Historically, hard measurables like cost, revenue, and agility (inventory, service level, etc.) have been linked to company profit-and-loss (P&L) statements to determine the business impact of transformation efforts. But that’s only one piece of the equation.

In order to align transformation efforts with business impact – focusing on the priority improvements that have the biggest impact on the bottom line – manufacturers need visibility into the most critical performance issues forestalling efficiency. With research showing the trillion dollar opportunity provided by tech-enabled transformation, forward-thinking organizations are addressing this challenge head-on, finding new ways to drive transformation at scale with digital innovation.

Enter PTC’s new ThingWorx Digital Performance Management (DPM) Solution, a first-of-its-kind offering that delivers real-time, closed-loop problem solving. Leveraging factory hours as a business-oriented KPI, DPM provides visibility into current performance, insight into the bottlenecks and root causes that slow throughput, and outcome validation for transformational investments.

Officially launched during PTC’s Manufacturing Live virtual event, DPM addresses the most valuable manufacturing improvements, resulting in manufacturing efficiency and transformation at scale. It’s demonstrable proof of PTC’s company purpose – to use our digital innovation to transform the physical world – and it’s thrilling to see come to life.

Let’s take a look inside DPM and explore the ways it drives manufacturing efficiency:

What Is DPM?

There is a textbook definition of overall equipment effectiveness (OEE) and manufacturing efficiency but DPM fixes some of the key issues. Let’s dig into the improvements DPM can make a little deeper.

At its core, DPM addresses manufacturing throughput. It can have an impact either on the cost of manufacturing products or on the units (volume) being manufactured – or both.

Let’s say, for example, factory costs are being driven up by overtime or high-cost facilities; you can bring costs down by resourcing or moving to low-cost facilities or you can maintain the same cost and add additional hours of productivity, filling those hours with additional volume/more units.

DPM gives insight into both of these areas by using factory hours as a currency for improvement. It’s an entirely different way of thinking about measuring and accounting for productivity on the factory floor, with everything reconciled against an absolute: hours. There are 24 hours in a day, 168 hours in a week – you might see, in the above example, that you’re losing 8 hours every week to overtime and, by addressing the root cause of the overtime, free up those factory hours with additional volume. Using hours as a currency engages the frontline, pinpointing for workers exactly where the production bottlenecks are happening, and realigns focus on cost per unit.

Historically, manufacturers have focused on OEE to determine manufacturing efficiency; it’s measured in percentages, with two, three, or four different percentages multiplied against each other. The problem with this common metric is it can look very different: Some manufacturers might measure standard speed, whereas others might measure theoretical or best demonstrated speed – three different ways to measure speed, but with radically different numbers. The end result is it’s very difficult to understand where the inefficiencies are actually happening and, in turn, nearly impossible to link any operational improvements to company financial improvements.

With DPM, manufacturers have a single source of truth from the factory floor to the top floor and back. By using hours, as opposed to percentages, as a business metric, frontline workers, managers, and executives all have one universal view of performance; in essence, they are all speaking the same language. DPM is designed for enterprise scale, meaning it not only provides a single source of truth across every level of the organization, but also across all sites within the organization.

What Challenges Does DPM Help Solve?

There are tangible and intangible aspects of DPM.

From a tangible standpoint, as I outlined earlier, DPM provides visibility and insight into inefficiencies on the shop floor, directly linking the resulting improvement efforts to company P&L. This piece is critical – linking operational impact to financial impact – because that’s where you see the large-scale impact of digital transformation. In that sense, DPM validates the outcomes of any transformational efforts.

From an intangible standpoint, DPM gives the ability to actively engage the frontline, focusing on the priority improvements that will have the biggest impact on the bottom line. For many organizations, cultural change is the hardest part of large-scale transformation; the challenge is there is a usually a small group of people (engineers, managers, and continuous improvement teams) doing the problem solving, all focused on different problems. Unfortunately, my experience has been (and I think most manufacturers would agree) that this accidental fragmentation means a lot of people aren’t delivering large-scale impact even though they’re trying to.

With DPM’s single source of truth, everyone, across all levels of the organization, is focused on solving the same priority problems, resulting in an order of magnitude transformational impact. Let’s say you have 50 people solving 50 different problems and you can get them laser focused on the highest priority problems (e.g., out of 80 hours a week, you’re losing 8 hours to changeovers and 4 of the 8 hours changing from product A to product B – now your focus is reducing those 4 hours to 2 hours). You’re going to see a radical improvement, not just with frontline engagement, but with better buy-in, ownership, and conviction across the organization.

How Does DPM Drive Large-Scale Transformation?

Imagine a factory has a hundred pieces of equipment – and, of that hundred, maybe 10 pieces of equipment are constrained, or bottlenecked, assets. You could be working on one of the 90 assets that isn’t constrained, meaning, even if you were to make an improvement, it wouldn’t change the company P&L because you don’t have more volume going through the facility and you don’t have the facility making the same volume at less cost. In other words, you’re not focusing on the right transformational improvements.

If, however, you’re working on one of the 10 constrained assets, you’re focusing on the critical bottlenecks that are constraining productivity. Using hours as a business metric, you can see that, out of 80 hours of scheduled production time, you’re losing 8, 9, or 10 hours in one area – that’s where you want to focus.

The key is to get a big picture understanding of repetitive versus one-time bottlenecks – and that’s exactly what DPM provides. With built-in functionality that provides analysis of performance over time, teams can rapidly identify the right performance issues to drive throughput, give visibility to the root cause of the bottlenecks, and create an organizational improvement plan.

Another way to think about it is as a balanced scorecard; DPM triangulates in on what’s important, which is prioritization of bottlenecks and constrained assets. It’s a T-shaped solution: The horizontal is broad, giving a view of the entire factory or enterprise, whereas the vertical portion gives the ability to drill down and filter by business unit, region, or facility.

The end result is step-function change in manufacturing efficiency. PTC intentionally took a clean sheet approach on how to think about throughput and capacity to help manufacturers overcome the most critical issues impacting operational and financial performance.

Final Thoughts

For years, manufacturers have struggled to realize large-scale transformational improvements; more commonly, they see incremental improvements because it can be difficult to determine which transformations drive the biggest impact. With DPM, companies can rapidly identify the right performance issues to drive throughput; empower frontline workers to take corrective action; give visibility to bottlenecks, root causes, and potential remedies; and measure results with performance data to ensure actions produce the desired outcomes.

It’s a revolutionary approach to driving efficiency – and it’s one of the many ways PTC is using our digital innovation to transform manufacturing.

ThingWorx Digital Performance Management

Discover more with the videos and material on PTC's DPM microsite.

  • Industrial Internet of Things
  • Thingworx
  • Digital Transformation

About the Author

Craig Melrose

Craig Melrose is the Executive Vice President of Digital Transformation Solutions at PTC. In this role, Craig works to build customer-facing, (operationally transformative) solutions that incorporate PTC’s industry-leading CAD, PLM, IoT, and AR technologies. His responsibilities include interacting directly with the customers to develop, scale, and roll out tailored industry 4.0 programs based on their unique operational excellence goals and needs.


Prior to joining PTC, Craig served as a Partner at McKinsey & Company for over 20 years, leading numerous operations and digital transformation initiatives, working directly with customers to understand their challenges, and identifying both tactical and strategic solutions globally and across dozens of industries. Throughout his career, he has helped companies dramatically enhance their factory automation strategies, including Toyota Motor Manufacturing, where for five years prior to joining McKinsey, he led the improvement of the Toyota Production System and Toyota’s operating performance through the introduction of new products across North America.


Craig earned a BS in Mechanical Engineering from the University of Kentucky.