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How to Cut Through the Noise: Manufacturing Analytics is Your Next Big Win

Manufacturing is ever-evolving; nothing stays the same. For that reason, manufacturing leaders are tasked with growing with the times. Make changes, try new things, update processes consistently. 

To grow, manufacturers should look at embracing manufacturing analytics software. 

Manufacturing analytics is well beyond the pilot stage at this point, that much is clear. It’s no longer a want, but a need for manufacturers. To collect and contextualize data from the plant floor to make data-driven decisions, manufacturing analytics is required.

There is a proven, worthwhile strategy that ensures success. That strategy includes 5 key steps. 

Manufacturing analytics is your next big win. Here’s why:

  • Manufacturing analytics fills a gap created by other “solutions” 
  • Contextualized data is more important than ever 
  • Manufacturers fully embrace the cloud
  • Manufacturing analytics is a small investment with a great return  
  • The start small, think big, grow fast strategy gives manufacturers the power to scale
  • Use of analytics provides a huge competitive advantage

Why is Data in Manufacturing Important? 

We’ve shown time and time again that manufacturing analytics actually works and will improve the efficiency of your plant floor. So, why haven’t all manufacturers jumped on board? The answer is that, before now, there were preconceived notions that manufacturing analytics wouldn’t provide many benefits. That, our friends, is simply not true. Quite the opposite, actually.

For you specifically, it’s your next big win; manufacturing analytics can provide increased productivity on your floor and a strategic continuous improvement goal.

There are a number of factors that have resulted in manufacturing analytics becoming a need, rather than a want.  

  1. We used to think comparing IoT or analytics solutions associated with an ERP or MES to a true manufacturing analytics solution was, all things considered, equal, but found that’s just not the case. Manufacturing analytics fills a gap created by other “solutions” promising to deliver insight into the efficiency of the factory floor. 
  2. Manufacturers are also now starting to realize that data without context or in isolation is not useful. Sure, asset condition monitoring is important; knowing temperature, vibration, or flow rate can be beneficial, but only with context. Trying to predict where a problem is or will occur is impossible without context. What line was the manufacturer running that day? What was happening in the plant that could potentially cause a problem? The data on its own doesn’t actually give the manufacturer that information. Contextualized data is key.
  3. Data storage in the cloud is more popular than ever. 65% of global and 93% of U.S. companies use cloud storage services. Manufacturers are becoming more comfortable with connecting machines to external networks to gather data. Developing solutions that use the cloud is now easier than ever because of the lack of security concerns in storing data in the cloud.
  4. Manufacturing analytics is a relatively small investment in comparison to the significant return manufacturers gain. We understand that an ERP system is the plumping and manufacturers have to have it, but if a change in software or upgrade is needed, a return on investment may or may not happen.Implementing manufacturing analytics and getting visibility into a process where there was otherwise no visibility not only increases efficiency but also reduces waste and the costs of people doing manual reporting. (Oh, and by the way, manufacturing analytics integrates with most ERP systems.)  Considering the ROI, manufacturing analytics is worth the investment.
  5. The start small, grow big vision has grown to define the manufacturing analytics industry. Manufacturers are now planning to roll out manufacturing analytics to a few key machines or lines, and as efficiency and productivity improve, roll out analytics to the entire floor or to multiple plants. The concept gives manufacturers the power to grow over time. 

Does Manufacturing Analytics Give Manufacturers a Competitive Advantage?  

Absolutely. Think about it, if you have two competitive manufacturers who make the same thing, for the same customers, and one of those manufacturers is able to eliminate all weekend overtime, produce more, increase growth, and reduce costs because of manufacturing analytics, who is the clear winner in the end? There’s no question as to which manufacturer would dominate the competition. 

Why is Context More Important than Regular ‘Ole Data?  

Collecting data aimlessly won’t do you, or your employees, any good. Instead, it will only bog you down with endless amounts of data with virtually no context. What good does that do you? You don’t know why things are happening on the floor which is literally, the whole point of manufacturing analytics – provide visibility and context into the factory floor so you know why a machine has gone down, for example.

We’ve said it before and we’ll say it again – context is everything. Without context, data is meaningless.  

Think in terms of “The 5 Why’s”.  

  • If vibration on a motor is trending towards critical – Why?  
  • You go look, but initial glance doesn’t suggest anything abnormal. Why?  

But, after those first two “Why’s?”, you’ve reached a barrier – there isn’t contextualized data to ask any other questions to figure out the root problem. 

If you had data to review, you’d find that a particular vibration pattern is normal when running a certain product on a certain line and that by asking “The 5 Why’s?”, the data would lead you directly to that conclusion. 

With contextualized data, you know why something is happening. With uncontextualized data, you’re getting false positives, but with context, you have an understanding that a particular vibration pattern is normal, but just not something that occurs very often.

How will Contextualized Data Play More of a Role in Strategy Improvement? 

As we’ve come to realize, most manufacturers want to start using manufacturing analytics to understand utilization. That’s it. It’s really simple – are the machines running or not? It’s a single data point that answers if a machine is down for a portion of a shift.

Then, as manufacturers see a machine is down, the natural next step would be to ask why the machine is down? Is the reason planned downtime that was otherwise miscategorized? Or a changeover that wasn’t scheduled. Why?  

This is where manufacturers naturally progress to expanding the data solution to include contextualized data. The lack of context prevents manufacturers from obtaining the supporting information to go through that “5 Why’s” process to really determine the root cause of a machine going down.  

(While this still can be done manually, it’s nowhere near as efficient as if the data was collected and contextualized, automatically, for you.) 

How Do You Get Started with Manufacturing Analytics? 

The best advice we can give for someone that wanted to implement manufacturing analytics – start small and start smaller than you think you would need to. Start with one data point or a couple (maybe 3, but that depends on the machine you’re wanting to monitor). 

The reason for this is to focus your efforts. Instead of collecting all different data points to understand what you’re doing and why you’re focusing on critical factors or numbers for your particular business. Focus and improve on critical efforts, first. This strategy is overall less expensive and time-consuming and easier to add additional data points throughout time. A win, win. 

You will ensure your success with the reiterative process, rather than trying to do it all once, because if you try to do it all, you’ll inevitably bury yourself in data with no end in sight.

Embrace Manufacturing Analytics

In the scheme of things, manufacturing analytics is a newcomer to the manufacturing industry, but it’s proven time and time again, the benefits provided to manufacturers. The concept of analyzing data to improve processes isn’t new, but the companies that have been created to help users efficiently analyze data is new. As those companies have entered the market, there has been, as with any company, trial and error. A few do very well while others don’t. It’s the natural course of business.

That natural variation in success can leave manufacturers feeling burned, or worse, unwilling to try again with manufacturing analytics if they spent millions on software that provided nothing in return. It’s no surprise – failure, with lots of money spent in the process, is difficult to rebound from. But you should. Here’s why.

At a time when analytics is more important than ever, don’t shy away because of a previously failed implementation. Instead, jump on board. Embrace the previous failure and use that as a guide in finding a manufacturing analytics software that works for you and will prove to make your floor more efficient and productive. Don’t be hesitant to try again – embrace manufacturing analytics.

“Will Manufacturing Analytics Work For Me?”

If it makes a difference, we do understand your hesitation. It’s likely that when you tried manufacturing analytics the first time, it seemed like the solution to all of your problems and it would be an instant success, but it wasn’t. We aren’t really surprised. It’s taken time to determine how to make manufacturing analytics work for manufacturers. Not all solutions worked. Not all strategies worked.

But, today, manufacturing analytics is an effective solution. What didn’t work 5 years ago, works now. Check out this blog we recently wrote: It dives into the big reasons manufacturing analytics is a win for manufacturers now.

Success is Based on a ‘Start Small, Think Big’ Road Map

That start small, think big, move fast idea that other people promised and failed to execute is now effective. (In reality, the other company probably had the right idea about where to go, but no methodology or road map to get there.) That road map is now a reality because of three things:

1. Manufacturing analytics doesn’t have to be overly complex – you can start out with a single data point on a small set of machines to prove it works and understand how to integrate analytics with the culture, which is where all of the success comes from.

(It’s also important to address one thing: manufacturing analytics implementations are not like other manufacturing software implementations. It’s not like an SAP implementation where it’s everything at once or nothing.)

2. Then, when you’ve mastered that, repeat the process throughout the rest of the plant. As we said, it’s not like other implementations. Over time, you continue to revisit and add more data as you mature as an organization.

Manufacturing analytics isn’t the type of thing you implement and forget about – it grows as your company grows. That is why it’s a whole new territory for manufacturers – it’s not what was done before.

3. The key in all of this, to be successful, to mitigate risk, to really implement a solution that works for you, is to partner with someone with a proven track record. Not only that but partner with someone who genuinely wants to see you succeed and helps you get visibility with your best interests in mind.

“So, I Decide I Need Manufacturing Analytics. How Do I Achieve Success?”

Overall, there are important steps manufacturers can take to guarantee success:
Mitigate risk and ensure the use of manufacturing analytics is successful in the long term by appointing a person or small group of people to own and run the project. Don’t just expect it to work without any direction. Then, when manufacturing analytics is taking shape on your floor, do the following four things:

Display data to everyone in the plant. This includes operators on the floor to supervisors to the C-suite at the top of the ladder.

Inform everyone (see above) what the data means and how it will be used to improve the floor.

Distribute that data through manufacturing insights emails. These emails keep people informed about what’s going on the floor– Is production on target or off? How much product was made yesterday? Did any unplanned downtime occur? Why?

Integrate data gathered into the daily routine. An example would be reviewing the previous day’s data in a daily production meeting.

While every manufacturer is different, taking the initiative to ensure each step is taken will undoubtedly establish success.

Keep Moving Forward with Manufacturing Analytics

Risks are a natural part of business. While too risky decisions are never wise, a small amount of risk is necessary. If you’ve been burned in the past, use that experience as a learning experience. Don’t shy away from continuing to improve your factory floor.


  • Find a company with a proven record that will help you improve.
  • Take the leap into manufacturing analytics – you’ll see improvements.
  • Manufacturing analytics isn’t going anywhere; it’s changing the manufacturing industry for the better, providing visibility and accountability on the factory floor.
  • Without it, you’ll be left in the dark about how your floor is running.
  • Analytics provides a clear competitive advantage, unmatched by other manufacturing software.

Don’t let the fear of striking out keep you from playing the game. (Yes, we’re getting cheesy here with a quote – bonus points if you know who said that!) But, the point is, the manufacturing industry is changing quickly. Manufacturing analytics provides the opportunity to embrace the change and achieve success, but only if you’re willing to look past your previous experience and keep moving forward.

Picture of Bryan Sapot
Bryan Sapot
Bryan Sapot is a lifelong entrepreneur, speaker, CEO, and founder of Mingo. With more than 24 years of experience in manufacturing technology, Bryan is known for his deep manufacturing industry insights. Throughout his career, he’s built products and started companies that leveraged technology to solve problems to make the lives of manufacturers easier. Follow Bryan on LinkedIn here.