Industrial Analytics: SMB Ready or Not?

Analytics aren’t just for the big boys. Small and mid-size manufacturers might be in a better position to get them in place and see quick results.

Diane Murray, LNS Research
Diane Murray, LNS Research

Shifting from metrics to analytics isn't something just the behemoth manufacturer is doing. In fact, in many ways, small and mid-size businesses (SMBs) are in a better position to make the move quickly and without a lot of angst. After all, the SMB won't have to worry about replacing a lot of other solutions, or the more troublesome effort of integrating with legacy systems. The industrial SMB is much nimbler and can leapfrog over the big guy to get its hands on the right analytics and get them installed and delivering value quickly.

In our most recent examination of metrics and analytics among industrial companies, LNS Research found that 40 percent of companies have already started putting analytics in place. However, the majority of SMBs still rely on dashboards to gauge the health of their business and operations performance. That lack of complexity is often mirrored in the small manufacturer’s operational architecture. In fact, the SMB’s operational architecture is and should be radically different than a large company. There are many reasons why this is true, but the fact is a small manufacturer doesn’t have the need to build—or the resources to support—a highly complex analytics infrastructure.

Getting ready for analytics

Even though the SMB’s operational architecture is much less complex than the manufacturing giant’s, you can’t shift from metrics to analytics overnight, or without some thoughtful planning. Before you even get started, you might need to educate others throughout the company on the differences between metrics and analytics, why one compliments but doesn’t replace the other, and what considerations the company must evaluate before making the leap. Again, the considerations are much different for a small or mid-size manufacturing enterprise than a large one. While a big company will likely need to gather a cross-functional team of 10, 20 or more people, the smaller company will likely have thorough representation with as few as three, five or 10 people.

The big company will also need to take steps to avoid “pilot purgatory,” a pilot project that never ends and never scales. The nimbler SMB is unlikely to experience such a fate, since it can just as quickly shut down or swap out an analytics choice as it chooses and flips the on switch. As a result, the SMB is less likely to hit a dead end with no quantifiable results. Where an analytics initiative is concerned, the risks are far less and the timeline much shorter for the SMB.

The analysts across LNS consistently advise clients, “Define your data model, and work within your defined operational architecture.” But what exactly does that mean for the SMB? We’re not suggesting that any SMB build a complex operational architecture—quite the opposite. The operational architecture should reflect the size and needs of the organization, the type of manufacturing it conducts, the market it serves, and every other characteristic that makes it unique. Consider this: Your architecture might be cobbled together, or perhaps non-existent, since many are still using whiteboards, spreadsheets or even a manufacturing execution system (MES) that churns out mountains of data. There are a lot of SMBs that can get going with high-impact analytics with only minor adjustments, depending on their current architecture.

Everyone needs a use case

Though it’s relatively easy for the SMB to ramp up with analytics, it still needs to ferret out specific opportunities for its market and choose which one or two to capitalize on first. This is your compass for the initiative—the way to deliver quick wins to fund future efforts and fuel enthusiasm at all levels of the company. But that’s not the end of the road as you champion your company’s effort from metrics to analytics.

If you already have enterprise resource planning (ERP) system or even MES, the organization might not ever need a dedicated platform for analytics. Look to your current solution providers and check out their newest releases. Even if you’re using a version that’s only two or three years old, their current offerings might have more analytics functionality than the version you have now. Whether your metrics tracking is manual or running through a current system, the vendors might surprise you with analytics that can do vastly more than what you can today. “Analytics” doesn’t always mean having to invest heavily or in an entirely new system or vendor. Look to your use case and what your company wants to achieve to guide your choices along the way.

Evaluate readiness

Most importantly, ask yourself (and the people around you) if the company is ready for analytics. For example:

  • Do you consistently employ a metrics framework that helps define your metrics hierarchy and relationships?
  • Are you selecting the most meaningful metrics that measure business value and impact, not just throughput and downtime?
  • Do your metrics go beyond machine and shop-floor activity, and include quality, customer and business metrics on your operations dashboard?
  • Are you relying on a multilevel dashboard that serves the leadership team as well as operations, and can it be used to facilitate real-time course adjustments and strategic recommendations?
  • Will your analytics initiative enhance the quality and availability of data?
  • Are you going to use a formal process to collect and manage data (often known as an operational architecture)?
  • Have you considered where you'll need to keep data and how long you’ll need to keep it?
  • Who will be on your cross-functional team to guide the initiative?

Your company doesn’t need a “yes” for every one of these questions to signal true readiness for analytics. However, these topics will require attention for you to be successful with and get genuine value from industrial analytics.

>>Diane Murray, diane.murray@lns-global.com, is a senior marketing and research associate at LNS Research, which provides advisory and benchmarking services to help line-of-business and IT executives make critical decisions.

 

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