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.
Does Manufacturing Analytics Give Manufacturers a Competitive Advantage?
Why is Context More Important than Regular ‘Ole Data?
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 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?
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 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.