How to avoid one-off efforts and instead implement across the enterprise
These days, manufacturers are looking to jumpstart operational productivity, efficiency, and profitability via cutting-edge digital technologies like IIoT, AI, advanced analytics, and machine learning. With billions in near-term gains and cost savings projected across industries, this new wave of digital innovation at scale has been dubbed Industry 4.0 — no less than a fourth industrial revolution.
The potential is very real… but there’s a lot of ground to cover to achieve it. Just a few short years ago, digital initiatives were mostly marked by false starts and major expenditures on one-off pilots that, disappointingly, didn’t scale. More recently, hard-won lessons and newer solutions are fueling some successes. Still, the vast majority of manufacturers are having a hard time pivoting away from “pilot purgatory.” We still see too many companies flailing about in too many directions, with internal teams independently targeting tactical initiatives that don’t span across the enterprise and translate to bottom-line value. Why do so many companies get so stuck? Well, most seem to fall victim to the same set of mistakes.
Siloed approaches going every which way
Often, the fundamental problem is a lack of cohesive, unified vision: projects undertaken without a long-term strategy, executive ownership, or explicit endorsement from senior management. In the resulting vacuum, IT and OT continue to chase innovation as they’ve done historically: on separate tracks, without much thought to what their counterparts are doing. As for the new data-focused “hit squads” within IT — composed of data engineers, data architects, and UX specialists — they have yet to be embraced by either of the traditional groups.
Happily, our experience of working with manufacturers has yielded a few examples of effective digital innovation at scale. Here are guiding principles distilled from these notable successes.
Start with Strategy
Drive the digital vision from the top down. As mentioned earlier, digital projects typically originate autonomously at the team level. IT, for example, may come up with an intriguing idea and execute on its own, only to discover at rollout that the solution doesn’t integrate with production processes and systems, or isn’t aimed at the gains OT values and therefore has little benefit for the organization as a whole.
The answer is to start at the top by building conviction for digital innovation with senior management: decision-makers and influencers with a broad understanding of the resources required and the power to marshal them across the enterprise. Success at scale takes careful management of technologies, use cases, investments, and cultural ramifications. Work together with management to develop an ROI roadmap geared to the size and nature of the objective, and allocate IT and OT resources accordingly.
Avoid “shiny object syndrome.” Rather than getting seduced by exciting-looking technology, begin with a clear-headed analysis of how a solution can address your particular pain points, build competitive advantage, and drive bottom-line impact. For instance, 3D printing is all the rage right now. It should be, in sectors where it enables designs that would otherwise be impossible to manufacture, or provides on-the-spot support for operational needs (such as spare parts). In other industries, though, it’s not much more than an expensive distraction. Apply the same logic to help focus your own efforts. For example, if you’re asset-heavy, prioritize predictive maintenance. If your primary cost is labor, concentrate on digital performance management.
Take the long view. More than a few vendors are pitching spot solutions that provide only limited value. Look past immediate fixes and go for a sustainable approach that builds long-term competitive advantage.
Design Your Technology Stack
IT deficiencies can sink digital strategies if not caught and corrected early on. So carefully plan your architecture upfront. Too many companies don’t and end up with massively over or under-engineered technology stacks. On one extreme we find single bloated solutions deployed on the mistaken belief that they “can do everything.” On the other, we see 30 different platforms. Either scenario puts you in a hole that’s hard to dig out of.
Ask the right questions in the right order. As suggested earlier, start with a vision of where you want to go. What are you trying to improve? How can digital do it? Make sure that IT’s goals are aligned with what OT seeks to achieve. Secondly, identify technology tools and infrastructure that enable the benefits, and work up use cases for them. Here too, the importance of cross-functional collaboration cannot be exaggerated: if OT co-ownership is not solicited early on, the project is unlikely to achieve strategic impact down the road.
Check all the infrastructure boxes. Namely: collection, connectivity, data transformation, analytics, and applications. Pay special attention to scalability, especially for your data-ingestion pipeline and complementary analytics capabilities.
Mobilize all your data. Capturing and harmonizing your universe of data is foundational to embracing digital innovation at scale. It takes an engine that unifies both IT and production data — especially the streaming kind — to unlock the transformative power of technologies like AI and machine learning. Design and develop your IT architecture to enable this integration.
Don’t try to build everything yourself. Technology is changing rapidly, and attempting to keep up on all fronts internally is a tough task. Choose partners that provide the underlying capabilities you don’t have and can’t develop quickly in-house. Look for solutions and providers that accommodate open integration standards and allow you to tailor the system to your business needs.
Build the Skills and Bench Strengths You Need
Everyone wants digital innovation at scale to “disrupt” — that is, to dramatically enhance profitability and competitive advantage. Frequently overlooked are the internal disruptions that new deployments also bring: major changes to accustomed processes, workflows, job requirements, and company culture. These upheavals and transitions must be diligently managed. Otherwise, digital initiatives can languish in the “science project” mode. Translate your objectives into concrete business processes and train employees to apply them. It’s not feasible to just drop a technical solution in and expect people to learn how to use it on their own.
Empower a dedicated team to lead the charge. It takes a village — a company-wide effort — to drive and manage change, led by specialists fluent in both operations and technology, who can serve as “translators” to bridge traditional departmental silos. You’ll also need technical experts who understand the implementation, along with change management coaches and project managers with a PMO-style ownership mindset.
Nurture cross-functional collaboration. OT understands production assets and processes. IT lives in a world of data, networking, and connectivity. Building collaboration and synergy between the two disciplines is a critical and early assignment for project owners.
Fill your capability gaps. It’s rare for a manufacturer to possess all the digital transformation know-how they need in-house. Focus on talent. Blend internal training with external recruiting and collaborate with solution providers and specialists. Selectively choose targeted partners with deep expertise and involve them in development as early as possible.
To keep things in perspective, bear in mind that new ideas and technologies can take a little while to reach the business and consumer mainstream. E-commerce, social media, and the Internet itself started as fringe novelties but soon went on to change the world. With today’s accelerated pace of change, astute value-focused decision making, and leveraging of new technologies and solutions, digital manufacturing will deliver the same magnitude of impact within an even shorter time frame.