Getting Past Pilot Purgatory And Developing The Workforce Of The Fourth Industrial Revolution

Between the health challenges that COVID-19 poses, the economic pain from partial and complete business closures, and the ongoing operational disruptions, these days it can feel like there are more unknowns and uncertainties than ever before. Yet against this backdrop, the Fourth Industrial Revolution has taken a rapid step forward in the integrated set of technologies it brings to bear—particularly digital, analytics, and automation—in helping organizations grow and work through the volatility.

In many ways, the manufacturing industry has been ahead of the curve, as continuous improvement and lean management were applied in manufacturing far earlier than in other industries. Manufacturing has hosted a broad set of applications of digital, accelerated by the industrial internet of things, the digitally connected enterprise, the broad expansion of data, and artificial intelligence. At the same time, however, manufacturers have faced significant challenges in developing a digital strategy: determining how quickly and how deeply to invest, which technologies to deploy, how to manage the operational transition, and how to best develop a skilled workforce to execute it.

As we emerge from COVID-19 and enter the next normal, manufacturing and supply-chain leaders have an opportunity to navigate the shift to automation and artificial intelligence–enabled operations and build a more resilient and connected future, grounded in digital capabilities.

The crucial ingredients? Getting past pilot purgatory and giving workers the skills they need so they can lead and support the change, at pace and at scale.

Pushing past pilot purgatory

Manufacturing has historically gone through spurts of development that have been driven by the emergence of new improvement levers. These spurts have reshaped not only manufacturing, but often the global economy as well. The first industrial revolution saw the introduction of the steam engine. The second industrial revolution was grounded in interchangeable parts and mass production, and the third in computing and telecommunications.

Technological advancements have accelerated our ability to “test and learn” in the fourth industrial revolution (4IR). Many organizations, however, have found themselves stuck in this phase. We often see companies adopt new technologies early, but in small pockets across the organization that are not scaled to yield significant impact. Instead, they end up in years of pilot purgatory, with small pilots scattered all over the organization and very little impact to show.

Rather than focusing on the market’s newest, shiniest technologies, the most successful adopters first identify the business problem they need to solve, taking an approach that is  business-backed rather than technology-forward. Not digital or analytics for its own sake, but a pressing business challenge to solve, using a range of levers that could become full or partial solutions. They also recognize that business problems require human skills to drive change, as tomorrow’s manufacturing jobs can change how work itself is done and require very different (and more) digital and technological skills.

Set a timeline to test and learn, then scale

Limiting test and learn phases to four to six months—the range for a minimal viable product to show real value—enables companies to move much more quickly in evaluating the value a pilot has delivered and determining when to move beyond the pilot phase. One failure mode I often see is the implementation of new technologies without a clear governance structure, where there are pockets of expertise in many parts of the organization, but without a common and shared backbone of capabilities. To avoid pilot purgatory, a phased implementation, with a set timeline for testing the technology, is critical to determine whether and where it can be broadly scaled.

Being in pilot purgatory can come at a high price. I have seen many organizations stuck in the experimental phase five years after developing a use case for automation, leaving a significant amount of value on the table. Even more pressing, it often leaves highly repetitive work to be done by employees rather than spending their time on a higher value activities, such as customer interaction or creative problem solving.

My McKinsey manufacturing colleagues and the World Economic Forum have done a deep assessment of the digital capabilities across 1,000 manufacturing sites, and so far 54 have of those have demonstrated how to excel in the 4IR at scale. This collection of leading-edge manufacturers make up the Global Lighthouse Network (GLN)—following a more structured path and demonstrating how companies can work toward achieving the full potential of innovation.

Technological progress requires at-scale reskilling

As organizations are more connected than ever before, the decisions they make have a ripple effect throughout the organization, and extend across the entire supply network. Lighthouse organizations have seen productivity improvements of up to 160%, together with lead-time reductions of up to 90%, as well as significant inventory reductions through end-to-end digitization. They have also shown remarkable agility from the start of the COVID-19 pandemic and have strong experience in driving transformations while guiding employees through change. With a deep understanding of the skills needed for the evolving work at hand, these leading companies are able to determine what reskilling and training is needed as a result. There are a range of digital and soft skills all leaders will need in the next new normal—including adaptability, creativity, problem solving, and ability to interact well with and learn new technology. On the other hand, there are a range of skills more targeted and technical skills that will be required at a smaller scale as well—from cutting-edge machine learning to advanced data analytics.

The most successful manufacturing companies have defined learning journeys for different roles, and encourage employees to go above and beyond those journeys to explore their areas of interest. In this next normal, we will all have to continuously upgrade our skills to keep up with this accelerated pace of change.

While organizations typically try to use attrition to address workforce imbalances, sometimes employees need to shift into a new role where at-scale reskilling efforts are needed. Here too, moving beyond small pilot programs is critical. For example, some companies have piloted shifting call-center representatives to entry-level IT positions. Other companies have shifted employees from finance and reporting functions to analytics teams, as financial-reporting activities are streamlined and automated. Most of these tests have not yet exceeded a dozen or two employees, however. Driving this type of reskilling at scale will help create meaningful career paths for employees, with far less disruption for companies.