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Estimated read time: 10 minutes
How is the manufacturing industry just like a shark?
Simple: We have to keep moving forward.
We don’t have time to look over our shoulders or agonize over “the old ways.” Instead, we must keep up with constantly growing demands from consumers and other players in the supply chain — which means our operational history probably isn’t that important or beneficial.
Actually, predictive analytics tools tell us that the answer is a resounding no. With these data science solutions in your arsenal, it’s possible to go beyond your shark-like inclinations. You’ll always be moving forward — but with predictive analytics, there are chances to glance backward and learn from the past, too.
Here’s everything you need to know about predictive analytics: what these tools look like, what the benefits are, when you should use them and when other solutions might be more effective.
What does "predictive analytics" really mean?
Before we get into the good stuff like manufacturing analytics benefits and strategies, let’s take a step back and appreciate what we’re dealing with here.
According to Gartner, predictive analytics is a type of data mining that has four key elements:
It emphasizes prediction rather than description (but you probably guessed that from the name).
It’s capable of measurement in days or hours rather than months (which is your only option with certain traditional data mining techniques).
It focuses on the business relevance of all the data it provides (rather than just dumping insights on your desk and leaving you to sort through the chaos).
It’s easy to use (so everyone on the plant floor can actually use it).
Simply put, predictive analysis allows you to break big data into bite-sized chunks, suggesting future outcomes and pointing out what you can learn from past events like machine breakdowns. It does this by using artificial intelligence to explore historical data, identify patterns and answer the question, “What’s going to happen next?”
It’s like giving a shark a rear-view mirror so it can glance backward without having to pause that relentless forward motion.
Here’s what predictive analytics techniques look like:
Data capture: The first step in any data analytics strategy is to actually capture the data. This can come from machines, sensors or even workers on the plant floor.
Data conversion: Once the data has been captured from all these sources, it must be unified into a single source of the truth. That means converting units of measurement, combining automated info with user-entered data, translating insights from multiple manufacturing systems and more.
Advanced analytics: Next, your predictive analytics software works its magic. Utilizing artificial intelligence and machine learning, it creates a “story” about issues on the plant floor, complete with a beginning (what happened before the event), a middle (what the event looked like) and an end (what solution was chosen at the time and how effective it was).
Translated insights: At this point, you have a lot of data about the past. That’s why the final step in the predictive analytics process is to translate this data into actionable insights about the future — essentially, using those previous stories to help you write a better sequel.
Before you start daydreaming about robot butlers, remember that artificial intelligence and predictive modeling are not capable of replacing human workers. Every manufacturer still needs people to capture data, decide when and where to use these insights, run the predictive analytics software, ensure production quality and more. It’s not about replacing humans; it’s about enhancing their skills through data analysis to create benefits they couldn’t reach on their own.
The benefits of predictive analytics tools
Speaking of benefits, what do those look like when it comes to predictive analytics? Let’s find out:
Supporting your teams
You know your teams are good at what they do. Predictive insights help make them even better.
That’s because predictive models help prepare workers to effectively navigate the challenges inherent to any manufacturing process. It also simplifies and reduces their workload, helps them make progress on their tasks, gives them the opportunity to learn from past mistakes and more. When leveraged appropriately and used in the right places, predictive analytics can act as a sixth sense for your teams.
Identifying and solving problems
It’s difficult to solve problems if you don’t know what they are. A predictive analytics solution can help you identify weak points in your processes, issues with your solutions and more — all by taking a hard look at your history.
Once you’ve recognized patterns and created expectations for the future, you can respond more quickly. Those responses will also be analyzed by your predictive analytics software, and you’ll get to learn from them, too. It’s a constant cycle of improvement, and it helps make your forward motion more intentional.
When you’re going full shark and charging forward without looking over your shoulder, you’re essentially just making guesses about whatever comes next. That leads to wasted resources as you choose the wrong solutions, miss significant problems or make plans you’ll never have to utilize. Predictive analytics gives you the insights necessary to move forward with confidence, applying resources based on identified patterns on the plant floor.
Take, for example, predictive maintenance. If you were to just stare at a machine and decide it’s looking a little slow today, you might waste resources on unnecessary maintenance. Use predictive analytics software along with machine sensors, however, and you’ll have solid predictions about when maintenance is necessary.
In manufacturing, there are two broad ways to handle issues that disrupt production: proactively and reactively.
When you’re operating reactively, things go wrong and you scramble to fix them. Your main goal is to keep your plant on track, so you choose solutions that may be temporary or ineffective, like smacking a bandage on a gaping wound just to get you by.
Proactive operations are far more effective in most cases. With predictive analytics, you’ll have advance notice regarding potential issues, necessary repairs, possible downtime and more. Sometimes you can even solve problems before they become significant — like stopping that gaping wound when it’s still just a paper cut.
Perhaps the most important benefit of any predictive analytics tool is its ability to improve efficiency across your manufacturing plant. The idea is to help you learn from your past to create a better future, and that means perfecting your approaches, identifying strengths and weaknesses, optimizing your workflows and making better use of your time.
Making the most of predictive analytics
So, now you know what predictive analytics tools are capable of and why you might want to leverage them in your manufacturing plant. You’re all ready to get started, right?
There are two questions you need to answer before you can make the most of predictive analytics: the how and the when.
Connected workforce platforms are the foundation for predictive analytics software. Why? Well, these platforms do a few key things:
Enables data capture: Without data, predictive analytics would never get off the ground. Luckily, a connected workforce platform makes it easy to capture this data from anywhere through an arsenal of user-friendly tools. Machine info, user-generated data, data from other systems such as CMMS, EAM, or ERP — you name it, a connected workforce platform can house, combine, and help analyze it.
Manages big data: All that data could quickly become difficult to manage, but a connected workforce platform simplifies and streamlines the process. Remember all the conversions we talked about earlier? Your platform makes it easy to ensure your big data is “speaking the same language” (and that it’s useful, relevant and accurate no matter where it comes from).
Makes predictions accessible: To fully utilize any predictive analytics software, you need to make it accessible. A connected workforce platform essentially creates a shared digital workspace for workers at all levels, improving visibility and keeping everyone on the same page.
Provides necessary tools: Once you have predictive analytics at your fingertips, then you need to act on those predictions. A connected workforce platform gives you the tools necessary to make fast decisions, track results and refine your advanced analytics technique. Plus, once you’ve identified a solution that works, your platform allows you to share it across the plant and even the entire organization.
Guides your choices: Believe it or not, these platforms can also act as your advisors. It’s all about prescriptive analytics, which can predict problems and help to suggest or reveal the best options for a solution. Human workers are still necessary to take the recommended actions and feed data into the system to create such prescriptions, but this utilization of artificial intelligence makes employees’ lives that much easier.
Essentially, a connected workforce platform shapes, informs and empowers predictive analytics tools for manufacturing. It also gives you the information you need to confidently — and correctly — answer the next question: When is predictive analytics actually necessary?
Once your connected workforce platform is ready to go, you might be tempted to dive head-first into predictive analytics. However, the truth is that predictive analytics — like all manufacturing technology — should only be utilized when the return on investment is clear. That means you shouldn’t just grab tech for tech’s sake; instead, you need to know which processes can benefit from predictive analytics and where to take advantage of those opportunities.
The good news is that your connected workforce platform can help make that possible. By providing visibility, illuminating pain points and enabling data analytics processes that provide a single view of the truth, you’ll be able to see where a predictive analytics tool could be a game-changer.
For example, say you have a recurring breakdown of a particular machine on your factory floor, and you want to get better at understanding when it’s going to break down in the future so you can stop that from happening. You may think that predictive analytics needs to step in to help give you that insight. In many cases, however, the cost of getting the right sensors in place to set up predictive analytics isn’t justified. With a connected workforce platform, you’re able to unify machine and user data, helping you see what’s happening with your machines and allowing you to react quickly to issues and keep downtime to a minimum for a lower cost.
Once you’ve put the right solutions in the right places, you’ll have the support and investment you need to scale your solutions even further. In the meantime, you’ll be using data analytics in target situations to make tangible improvements, simplify life for your workers, leverage artificial intelligence in effective ways and generally make your plant stronger than ever before.
Predictive analytics tools in your back pocket
We know the manufacturing industry is like a shark because we both need to keep moving forward. Luckily, you’re not a shark. The difference is that you can have the clarity necessary to decide when you should look over your shoulder and what to look for when you do. That’s what predictive analytics is all about.
Of course, this isn’t supposed to make you agonize over past mistakes. Predictive analytics helps you approach your history constructively and move forward feeling informed, enlightened and empowered with actionable insights. These tools also help you build a brighter, more streamlined future for your employees and organization. The only thing you have to do is know when to pull the trigger.
To do that, you need to put predictive analytics in your back pocket with a connected workforce platform.
There’s always more to know about connected manufacturing, predictive and prescriptive analytics, artificial intelligence and the other keywords that probably circle your brain and show up in your dreams. That’s why we’re leaving you with one big takeaway:
You don’t need to have all the answers — you just need to know how to get them.
If you’re ready to put big data to work for you and find out when to leverage solutions like predictive analytics, book a platform demo today.