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A scalable IIoT tech stack starts with business-focused use cases

Use cases are the building blocks of any digital transformation. Selecting and prioritizing them to drive real business impact is a critical first step.
Ani Bhalekar

Based in McKinsey’s Singapore office, Associate Partner Ani Bhalekar is Vice President for the Internet of Things (IoT), serving clients across sectors on smart cities, connected transport, Industry 4.0, analytics, mobile and digital technologies.

Karel co-leads the Firm’s Operations practice and Internet of Things (IoT) group in Asia. Since joining the Firm in 1997, Karel has worked across multiple industries including advanced industries, automotive, electronics, energy and materials, technology, as well as private equity.

In an earlier blog post, we demonstrated how manufacturers’ efforts to capture value from the Industrial Internet of Things (IIoT) are often stymied by a breakdown at the convergence between their existing operational technology (OT) systems—their things—and the new information technology (IT) systems needed to drive a transformational digital operation.

We refer to this as the “last-mile IT/OT problem,” which results from the failure to properly plan, design, and build an IT/OT architecture from the outset that is capable of driving use-case pilots to scale. We identified the steps manufacturers should take to ensure that their IIoT stack isn’t holding them back, with this post as the first of a series of deep dives into how to put these steps into practice. Bear in mind that the steps aren’t strictly linear: in trying to deliver a whole program of IIoT initiatives, a pragmatic, integrated approach considers steps in tandem as needed to keep initiatives on track and out of one another’s way. But there is a general interplay between them.

Because selecting use cases is the starting point of any transformation, getting this step right is critical (Exhibit 1). All too often we see manufacturers start with technology in mind and then try to build a business case around it, and this sets them up to fail. From the outset, it’s essential for business KPIs to lead IIoT transformations, and for each potential use case to be tested against the business value that it is trying to create. In some cases, the best solution may not be a technology play at all.

Carefully choosing business-driven use cases helps digital transformations succeed on a wide range of metrics.
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But before making any judgment, bear in mind that it’s also important to avoid looking for business problems only within the four walls of the plant. By extending your gaze all the way from the supply chain to marketing, sales, and after-sales service, you can see opportunities to reinvent the complete value chain through digital technologies, rather than simply installing multiple “point” solutions that convert analog practices into their digital equivalents. It’s the difference between using technology to make an inefficient process run faster, and using technology to create a new process that dramatically opens up new opportunities and increases value creation.

Because use cases are typically selected to address immediate business needs, they are not enough on their own to deliver the sustainable new business model that an end-to-end digital transformation promises. But they are the building blocks of this transformation, and stack enough of them together and you can reap enormous dividends. Use cases also have a second, often under-appreciated, role. Because they solve for a particular problem or business need, they deliver the short-term wins necessary to capture immediate impact and prove the benefits of transformation to everyone from the frontline to the boardroom.

While we recommend implementing multiple use cases to drive a significant business transformation, this is not to say that single use cases or a related group of use cases in one area of a business cannot deliver significant impact. For instance:

  • A global basic-materials company introduced driverless trucks into several of its larger sites, which not only cut costs and improved safety but also outperformed the manned fleet by an average of more than 10 percent.
  • An automaker improved job satisfaction and reduced the time workers spent waiting between tasks by more than 75 percent—by teaming workers with collaborative robots on one of the most important assembly tasks for final product quality.

But by multiplying these gains across use cases spread throughout the value chain, the truly transformative power of digitizing operations starts to come into view. The implementation of each new use case also part funds the establishment of the IIoT platform infrastructure by delivering its own positive ROI, so the number of use cases a manufacturer could implement can be quite large.

Once an ambitious list of potential use cases is confirmed, they need to be tested against several criteria in addition to their impact on the business. These include whether technology to drive the use case is mature and readily available from established vendors, and whether the organization currently has the capacity to deliver the use case using that technology. While there are clear benefits to being a first mover, it’s also worth looking at what competitors are doing and whether the use case has been adopted at scale elsewhere in the industry to deliver significant benefit.

One way of testing use cases against these criteria is to feed them into a prioritization funnel with successively tighter filters at each stage. Only use cases that pass through all the filters and emerge from the narrow end of the funnel get sequenced for implementation. Because a typical manufacturer is likely to need 10–15 use cases just to drive the manufacturing part of its IIoT transformation—expanding this to all functions up and down the value chain will require many more—this approach is not for the faint at heart. One manufacturer put around 50 potential use cases through a prioritization tunnel to end up with around 15 use cases they needed to meet their game-changing business objectives around quality and cost optimization, as well as worker productivity (Exhibit 2).

A prioritization filter can help select use cases and sequence them for implementation.
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The prioritization filter should also give a good idea of how to sequence the rollout of use cases. The next steps are to determine which technology solutions from the many options in the tech ecosystem will power them, identify the tech stack requirements for each one, and select the platform that will tie them all together. We will come back to these steps in future articles.

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