Pull Back the Curtain on Digital Technology: What Manufacturers Need to Know

manufacturing operations technology

In recent blog posts, we’ve been exploring what it will take to escape the manufacturing “Oz” created by the economic disruptions caused by the ongoing COVID-19 pandemic. So far, we’ve covered what courage means in manufacturing, how to get the heart of your organization back to work, and the brains behind manufacturing success going forward. Now it’s time to pull back the curtain on the “Wizard,” or manufacturing solutions in our case, and explore how to avoid being led toward solutions you actually don’t need or that aren’t optimal.

Avoiding unnecessary frustrations and costs

Near the end of the Wizard of Oz, Dorothy and her companions finally reach the Emerald City and get a chance to meet the Wizard in the hopes he can solve all of their problems. But after traveling the entire length of the Yellow Brick Road and dealing with harrowing challenges involving witches, and flying monkeys, they come to the harsh realization that the Wizard isn’t everything he’s cracked up to be. An analogous phenomenon happens in manufacturing operations all the time; leadership teams experiencing a problem start gravitating toward solutions to challenges without first pulling back the curtain on options and figuring out what’s best and why.  And in some cases, are sold technology or new equipment that often leaves them disappointed because it really didn’t solve the problem or bring the business value they anticipated. Just consider a quick example for how this can play out.

One of our past clients had invested $3 million in a new piece of equipment that was supposed to replace the equivalent of three direct labor individuals from a process. The problem is that although the direct positions were no longer needed, the company had to add three indirect people to the process to make it run. In other words, the purchase ended up being a net wash. It’s a simple but good example of spending a lot of money and time that had no real impact on the business.

Where are you really trying to go and why?

Avoiding these types of situations starts with having a clear road map for where you’re trying to go and why. Before even considering new technology, whether it’s computer systems, machines, robots, or something else, it’s important to understand what business issues you are really trying to address like…

  • Where is the opportunity and what is the value of that opportunity in your business?
  • Is it around spending on indirect labor—how much is that indirect labor really costing you and what drives it?
  • Is it that you move materials with that indirect labor?
  • Is it that you experience significant downtime, or that five points of OEE could generate another million dollars of incremental margin?
  • How do you measure and capture the benefit?

You must look at your current and your future state processes to really understand what improvements are required and why.

Once you’ve answered critical questions and have a roadmap for where you should be going, then it’s important to remember to be pragmatic; you don’t always have to buy a top of the line Rolls Royce when a Toyota Camry might be equally effective for the task. But in other cases, you may need the top of the line Rolls Royce. Part of the value of having a clear grasp of the business problem you need to solve is that it enables you to think more practically about potential solutions. For example, a food manufacturer was interested in using video recognition technologies on their equipment to understand when and why issues like conveyor belt jams happen. It would be easy to gravitate toward an expensive solution that uses AI to identify issues. But the combination of a GoPro camera along with factory floor connectivity (syncing the time stamps from the video with the IoT data in the factory) might be effective enough and much less expensive.

Putting data into perspective

When considering what’s behind technology curtains and what that could mean to your business, it’s critical to not lose site of the importance of effective data management.

At TBM, Dploy Solutions parent company, we’ve segmented our customer bases using the combination of data, KPIs and analytics so we understand them in all kinds of different ways. By ownership status, revenue size, types of service offerings, engagement timeframe, how often we reengage, and how much revenue they generate for us. We also use dashboards of KPIs with analytics behind them for weekly reviews at all levels. So, not only do we know how we perform but we also know what is driving the performance be it optimal or sub-par.  Bottom line, we’re taking advantage of digital technologies to help us make smart business decisions not just every single day in the short term, but also in the longer term from a strategic perspective.

So, really bringing your data together is a critical part of being successful with digital technology. But there is also a challenge in combining all of the different sources of data using master data management. In 30+ years of consulting, I have never seen a company achieve 100 percent data accuracy. But I’ve seen plenty get very close through careful efforts around understanding how to bring different data sets together and creating standards that deliver as close to a single point of truth as possible. Once you have a good single source of the truth, the challenge is figuring out how to use it to drive actual performance. And that may not be as straightforward as it seems, depending on the type of solution, in-house expertise and other factors.

Take the example of a client who was trying to segment their data around warranty claims. Their analysis was too detailed and was actually blurring the lines of what was really happening. After ingesting their data and slicing it differently, we came up with some clear conclusions that they used to address what was becoming a significant issue.

Ultimately, it’s important to think carefully about the types of data you collect and how you should be using it. After all, data collection doesn’t come free and there’s little to no value in having a lot of data you can’t tie back to operational or financial performance. The ability to connect what it is you’re tracking, capturing, reporting on, and tie it back to how it makes things better in your business is what’s key. Remembering this is especially important if you start looking at IIoT solutions on the factory floor. Sure, it’s easy to add sensors all over the place, but are they going to change anything for the better or just add “noise” to process analysis?

Moral of the story: Realistic expectations and thorough vetting pays

In the end, it’s become almost impossible to build or keep a competitive advantage without the smart use of technology. And with the chaotic state of the world, there will be a lot of opportunities over the next 12 – 36 months where digital solutions could prove invaluable to improving the performance of your business. Just consider how quickly remote capabilities became essential during the pandemic. The thing to remember is that it’s smart to define what you need and why and then be pragmatic about solution choices, even if that means getting creative. “Pull back the curtain” on your operations and assess what exactly is the right technology your manufacturing needs to solve the problem and create the business value you are looking to capture.  Give us a call to discuss the best approach to digital technology decisions. In the meantime, listen to our 15 minute webcast recording below on “The ‘Wizard’: Ingenuity & Innovation for Long Term Success in Manufacturing”. 

Subscribe to the Dploy Solutions’ YouTube Channel.

 

About the Author

Ken Koenemann, VP of Supply Chain and Technology at TBM Consulting Group (parent company of Dploy Solutions), is a 25+ year veteran of manufacturing, operational excellence and supply chain optimization. At TBM, Ken is actively leading the effort to our suite of services to include emerging technologies that improve productivity and convert complex data into information for improved decision making.

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