Now what?! Challenges and Strategies in Scaling Digital-transformation Efforts

By Roy Kok, CESMII marketing director

Scaling Digital TransformationRather than relying on a digital-manufacturing solution, businesses operating in the modern industrial landscape are utilizing (or at least piloting) about eight different digital-manufacturing solutions to enable them to capitalize on the buzzworthy elements of Industry 4.0—big data and analytics, cloud computing and IT/OT convergence, etc. That’s according to a recent McKinsey study.

And while business of all sizes, varied verticals and diverse maturity levels reap the benefits of these solutions to varying degrees, they all struggle with a common challenge: scaling successes. Pilots are plentiful; less common are clear roadmaps to move forward with rollouts and achieve positive impact at scale.

Congratulations—your test project with digital transformation was a hit. Now what?

We know the projects at play here. Many of you are likely engaging with them right now. Advanced data collection and analytics—automated, ideally—providing an accurate, real-time view of what’s happening on the plant floor. And you know the tools most commonly in play here—smart sensors and hi-def cameras, IoT-monitoring networks, smart glasses, and collaborative software. Cloud computing is enabling the management of all this information, where systems and data are run and stored offsite and accessed online, allowing companies more possibilities for remote work and collaboration.

We know that these projects are directionally correct. They are the paths to success in our data-driven future. But calculating the true ROI of these initiatives and scaling them up continues to befuddle even the savviest among us.

Why is that? Every Fortune 1000 industrial company has IT and OT teams are collaborating like never before. Even the smallest mom-and-pop shops recognize the value in digitizing their processes. But a recent MCA Trends Report found that only about 30% of organizations are rolling out relevant solutions company-wide. Yikes.

And the most common response to the question about implementation in Smart Industry’s latest State of Initiative Report was that projects are “problematic but ongoing.”

Clearly, scaling ain’t easy.

Go big or go home?

When it comes to scaling digitalization projects, size matters. Successful digital-program scaling campaigns seem skew toward larger businesses, which have the deep pockets and bandwidth that enables the ramping up of these projects. If the Fortune 1000 are only experiencing a 30% success rate, what is the world of small and medium manufacturers (SMMs) to do, especially with their limitations in internal technology expertise, their lack of data scientists, and their restricted budgets?

Clearly, there is a fundamental problem that needs to be overcome to deliver progress in technology, broadly across industry, especially the SMMs that make up 98% of companies.

Just how can the little manufacturers go big? The problem is that, unlike other industries, the world of industrial products has remained a collection of siloed technology solutions from a global array of product vendors. While standards for interoperability have improved, as exhibited by the success of technologies like OPC and MQTT, the silo problem persists.

Complexity causes challenges, too. If I wish to add advanced analytics, predictive maintenance, asset management or any other new application to my industrial environment, the first step might require an analysis of available data, the accessibility, and the mapping of that information to the application that needs it. And as I add another application, the same mapping process happens again. If I have 10 applications, or 10 sites, I incur 10x the effort, time and cost. That’s a tougher pill to swallow for smaller, leaner, scrappier enterprises than global companies with those resources in house and ready for action.

Consider that a $1 spend on a vendor software license will typically require a $6 expense in configuration and software maintenance. These factors can be managed and justified by the larger enterprises, but for the small-to-medium companies, these solutions just can’t scale affordably and sustainably, thus they remain out of reach.

How to solve the problem of scalability while avoiding pilot purgatory

There are two solutions to the scaling problem.

The first is selecting a vendor that offers a complete stack of fully integrated technology. For most, this isn’t a viable option because XX.

The second choice is to implement a new architecture; leverage a solution that models your data and delivers context to the uses of your data. You may be familiar with information models such as S-95 and examples of such used in technologies like OPC UA. These are excellent solutions, and empower users to configure solutions more effectively, as they represent the available data more effectively. However, they do not significantly improve upon the scale problem as system integrators are still required for implementation.

New technology is needed to deliver the additional context to the data, beyond the basic information model, so that layered applications have the opportunity to programmatically discover and auto-configure in order to deliver their value.

And there are resources at the ready.

Consider, if you don’t mind, the organization I represent; the United States government has created a non-profit institute for the development and promotion of smart manufacturing and associated technologies. CESMII—The Smart Manufacturing Institute—works with industry in the definition and  development of a Smart Manufacturing (SM) Innovation Platform.

Platforms such as this enable a wider pool of employees within an organization to build apps and bring new solutions to market. They democratize digital transformation. Tools like this are force-multipliers for enterprises looking to scale early wins.

We believe that aggressive investment in platforms such as this (complemented by associated standards), is the key to fully unleashing productivity and innovation within a digital enterprise. This approach assists energy-reduction efforts and opens up new opportunities for greater scaling of programs.

But the right vendors must be on board, with whatever platform is implemented. Our strategy is to involve a small group of what we believe to be the most innovative and domain-specific vendors. I suggest partnering with vendors that are 1) already focused on core functional capabilities that you’ve identified as mission-critical to your roadmap, and 2) are willing to engage with you in shaping your strategies.

With a smart-manufacturing platform in place and the right vendors on board, it is then critical for industrial business owners to engage their entire industry ecosystem, from end-user consumers of the product to the system integrators, from the software and equipment vendors to the workers on the plant floor actually implementing these process changes.

The result of these approaches is an environment where all can participate in (and benefit from) the performance improvements that are delivered through the full catalog of Industry 4.0 technologies.

Challenging? You bet. But the successful escalation of digital strategies becomes more common each day. I see success stories all the time as we work with industry organizations around the world to highlight the need to accelerate adoption…to scale up efforts to scale data-driven manufacturing.