Data Automation: The Most Underutilized Strategy in Manufacturing

Every leading company in today’s world leverages data to stay ahead of the competition. It helps you decide what to do next, how much production to run, or even how many people you need on staff. All of these have become important in the wake of supply chain issues and labor shortages.  

And yet, thousands of other companies still use clipboards, whiteboards, and spreadsheets to collect that data, which hurts the efficiency, effectiveness, and bottom line.  

That’s why it’s so essential to start automating your data collection, analysis, and processing. Even though data automation can often be seen as an additional cost, it should be seen as an investment. The business insights you gain from it not only help you optimize the business and increase your speed-to-market, but it also helps you mitigate errors. 

In this blog, we will explain how data automation is used in manufacturing and why it could be the missing piece to scaling your operations.

What is data automation?  

Today, a lot of data is collected, recorded by hand, input into a spreadsheet, and then analyzed, but it often ends up riddled with errors and results in hours of lost time. Data automation uses software and hardware to capture all the information available from your processes and then organize it in a way that is easy to understand and use.  

And it does it in a fraction of the time and with minimal errors. Two areas of the manufacturing process that humans simply can’t compete with.  

Data automation is about giving you the opportunity to make better business decisions because you have access to more accurate data as soon as you need it. 

Why data collection isn’t the big issue — bad data is 

Data automation actually makes the most sense in manufacturing where Industry 4.0 has been the trend for the past decade but there is often a huge communication gap between the top floor and the shop floor. Unfortunately, automation is often seen as the enemy in many cases, that it is going to replace jobs. 

What it actually does is free your team to work on higher priorities instead of standing by with clipboard in hand. It’s not there to replace workers, it’s here to elevate their roles.  

The main challenge is actually bad data. Bad data is anything you struggle to access or make sense of. According to Progress.com, the reality is about 85% of data goes unused by organizations and only 15% are able to take advantage of real-time, accurate data.  

Why is this significant? ]Because a meager 1% improvement in productivity across the manufacturing industry can result in $500 million in annual savings. 

Main benefits to data automation 

Now that you know how data automation can be a powerful tool for improving business processes, here are some real-world examples of how it’s being used to add value for manufacturers.  

1. Data collection becomes more efficient and accurate 

While humans can watch a gauge and record what they see at intervals, machines can monitor and record in real-time; things like pressure, temperature, flow, and current draw. This gives you an accurate look at what's going on inside the manufacturing process whenever you need it. And because machines don’t get bored, tired, or need breaks they record everything along the way without using any additional resources. A recent study has shown that human error in data entry can be as high as 4%. When humans are entering hundreds of thousands of entries, this 4% can turn into a significant amount of lost or incorrect data that you would not be present with data automation.  

2. OEE

Data automation can help improve your Overall Equipment Effectiveness (OEE) by using real-time insights into to help you identify and address the root causes of any inefficiencies, downtime, or quality issues. It can even go one step further to help you react quickly if any employees are unavailable, materials aren’t delivered on time because of supply chain issues, or there is a potential disruption with a process further down the production line. By tracking these metrics in real-time, manufacturers can monitor their equipment and processes more closely, make data-driven decisions, and continuously improve their operations over time. 

3. Better production output 

Another benefit of data automation is that when your machines start to monitor their own health, you may find indications of a looming issue before it becomes a crisis. This can help you avoid defective parts and components. The accurate data you collect will also allow you to tweak your manufacturing processes to schedule your downtime and optimize your production, allowing you to increase your bottom line.  

4. Your data becomes easier to use 

The heart of data automation is about taking all of your data streams and formatting them so they all work together. When you want to see something, you select the right report or input the parameters you want and you get charts, graphs, or tables, whichever you like. The great thing is, if someone else needs to see the same thing but prefers a different format, they get the same information presented how they like it.  

5. Streamlines your workforce 

There’s no way around it, manual data collection takes time. Depending on the scope, it may take one employee, or it may take a whole team to spend a portion of their week collecting data, loading data, and reporting on data. Not only can data automation perform these tasks in a fraction of the time, but it also allows that worker or team to get involved in more important business functions. This adds to your organization’s production without additional hiring. 

Why manufacturers are slow to adopt data automation 

Given the obvious benefits to data automation, why are manufacturers slow to adopt it?  

Automation in general has been a touchy subject for manufacturers for some time. The obvious allure is saving time and money but there are many reasons why organizations put this off.  

Implementation costs 

One of the main reasons we don’t see organizations utilizing data automation is the worry about the cost and the disruption it may cause the business when implementing a new process. Installation, training, and downtime are all valid concerns when building a data automation process. The truth is, there will be upfront costs.  

The trade-off is this short-term pain is replaced by a significant long-term ROI. Efficiency will go up, downtime will drop, and you’ll be able to move your workers around to more valuable tasks. Over time, you will see a large payoff.  

Knowing which processes to automate  

Another reason organizations aren’t implementing data automation is that they are very comfortable with their current processes and machinery.  

With a manual process in place, management often feels like they have people who know what data to retrieve, how to collect it, and how to format it. Changing organizational processes takes time and effort, so it’s easy for manufacturers to delay it as long as possible.  

When key processes and data are siloed with just a few people, disruption is inevitable. People get sick, go on vacation, and make mistakes. Data automation reduces your risk by automating the data collection process and providing access to anyone who needs it whenever they need it.  

Replacing or integrating legacy machines 

Many manufacturers use tools that were acquired years ago and are worried about replacing those machines.  

The good news is that even legacy machines can be retrofitted to collect data. Sensors can be added where needed and the hardware they communicate with can be “bolted on.” So instead of replacing the technology that your employees are used to, you can harvest the data from these machines 24/7.  

Even though most new machinery is created with data automation in mind they often offer no visibility to key decision-makers. So it is still important to make sure your new machines are giving you the right information. 

Developing your Data Automation Strategy 

A great way to start developing your data automation strategy is by figuring out what data you have access to already and then making a wish list of what you wish you had. Take a look at your whole company and identify as many processes as you can that generate data that you review and identify gaps in that set of data.  

You can then examine the costs and accuracy of that data collection: 

• How much time and resources are spent on collecting important data before you even see it?  
• How much time is spent writing down information on clipboards and whiteboards, then inputting it into a spreadsheet, and formatting it? 
• Is it accurate or are there opportunities for mistakes that reduce the validity of the data collected?  

Finally, find a partner with experience in data automation. What you know about your data processes is just the starting point. Working with an experienced data automation expert will bring you new insights into what can be collected, measured, and used in planning and decision-making.  

Adopting data automation is as important as ever, if your competitors are receiving insights that you are not, they may just be able to grow quicker and price better as a result. If you want your manufacturing process to run efficiently and realize its maximum ROI, you need to invest in data automation. Changing your processes is always a challenge, but with the right partner, it can be done with a minimum of disruption and stress.