In Digital Manufacturing

By: Nate Oostendorp, CTO Sight Machine and Ed Jimenez, VP Marketing Sight Machine

We’ve been fortunate to witness a significant number of digital manufacturing projects over the years. Often these efforts involve implementing pilots at one or two “smart factories” that serve as innovation centers for large manufacturers. Despite their namesake, these facilities can often be a hindrance to enterprise-wide innovation and transformation.

Smart manufacturing is broadly defined by the National Institute of Standards and Technology (NIST) as collaborative manufacturing systems that respond in real time to meet changing demands and conditions in the factory, supply network, and from customers. Smart factories, on the other hand, tend to be individual facilities where manufacturers pilot innovation efforts prior to scaling across the rest of the manufacturing base. Capgemini, in a recent report on smart factories, identified that 76% of manufacturers have a smart factory initiative, but only 14% are satisfied with their level of success. This is in-line with our observations, as more often than not, smart factories end up becoming a bottleneck for innovation – inhibiting, rather than accelerating, innovation from extending across the enterprise.

But why do these facilities, whose purpose is to be a learning lab for new processes and technologies, often end up stifling these learnings? We’ve found the very structure of smart factories to be a deterrent to scaling innovation:

  • Atypical organizational readiness: Smart factories are constantly deploying new solutions and technologies. Over time, they’ve built up the cultural mindset for cross-functional integration and change management to support these efforts. They also typically have close alignment between IT and operations and correspondingly, budget and resources committed from those teams to ensure the success of new initiatives. Unfortunately, most plants across the rest of the enterprise don’t have these advantages. Their operational teams are usually are not aligned to corporate transformational strategies; even if they are, their metrics are likely tied to traditional output-centric KPIs. When companies attempt to roll out technologies developed in a smart factory setting they struggle to get buy-in from local teams.
  • Favorable IT preparedness: Smart factories, by their very nature, are well equipped with an IT foundation that can support even the most demanding of technology solutions. Therefore, these implementations will have little relevance to the conditions that exist across the portfolio of facilities, making successful pilots unlikely to pencil out for broader deployment.
  • Restricted sample size: Implementing a pilot at one facility generally does not generate enough learnings to build a business case to extend an initiative across your enterprise.  Many different factors, from cultural receptivity, leadership alignment, operation and technical resources, and changes in workflow to adopt enhancements to process go into a successful initiative.  Any one plant may be exceptional or a disappointment, but only by getting data from multiple experiments and successes provide a roadmap for transformation.

So how can you increase the potential for your innovation efforts to deliver enterprise-wide transformation?

  1. Tackle foundational issues, such as enterprise data integrity, that are applicable to multiple facilities instead of developing applications that address use cases unique to a single facility (such as scrap/defects). Applications that address sophisticated initiatives such as predictive analytics will have limited extensibility or will require too much investment to scale more broadly.
  2. Watch out for vendors that position end-to-end, services-heavy custom solutions. Lighter platforms that integrate and leverage data from multiple systems will quickly expose integration issues across plants at all levels of readiness and enable operational teams to broadly understand technical and organizational adoption challenges.
  3. Don’t expect perfection from pilots before expanding initiatives. As discussed, most facilities have significant differences that will only become apparent as you scale efforts. Attempting to ensuring that everything is working perfectly before pilots expand beyond a single facility can delay the effort to the point where the project outcomes are likely to become irrelevant.  Instead, learn from both good and bad outcomes and work consistently towards building a foundation that supports your end goal of smart manufacturing.
  4. Leverage the market to accelerate your innovation. Many manufacturers attempt to leverage in-house IT and process resources to develop innovative tools. Unfortunately, even if these efforts are successful, ongoing development, maintenance and support costs are sure to limit the long term viability of these efforts. Today’s innovative application is likely to become tomorrow’s obscure legacy system, understood only by people who have long since moved on.

As more and more manufacturers invest in smart factories it’s imperative that they adopt the right strategies to ensure innovation can readily scale across the enterprise. By choosing the right types of projects, setting the appropriate expectations, and leveraging market innovation, manufacturers can accelerate their ability to transform their organization into a smart enterprise.

[Webinar] Overcoming and avoiding digital manufacturing failures Sight Machine  & Bain Gain insights on lessons learned from Joe Terino and Peter Hanbury of  Bain and Jon Sobel of Sight Machine on successful implementations by  manufacturers who are conquering complexity and making faster, smarter  decisions to drive change that sticks! Watch Now

Recent Posts

Leave a Comment