Advances in technology have helped manufacturers of all sizes become more sophisticated. You know how to use ERP or small business software to manage your business information. It is staggering how far we’ve come compared to managing those processes on paper.
There’s a side-effect to this process: continual data creation. You are constantly creating data at every stage of the manufacturing process. Your ERP software can house a lot of the data about purchases, costs, and customer behavior. This is all business data. If you use automated or network-connected machinery, you also have data on the assembly process.
The problem is, regardless of how sophisticated your technology is, most manufacturers do not have a plan for how they will exploit all of their data to increase their profit margins. There’s a few baby steps you can take right now to do that.
Step 1 Identify What Data Drives Value
There are critical junctures where everyone one of us checks our output. Deep Fork Technology works in custom software development, and we have to create products by deadlines we set with our clients. Before that deadline we check to make sure that the product we are delivering matches the specifications set by the client.
You probably have similar steps where you measure how your process has performed. What is the quality of a specific product off the line? How much raw material did it take to get there? How much was wasted? How efficient was your labor, and how much does that fluctuate?
People have different ways to measure and track performance. But you should at the very least be storing the answers to these questions somewhere so you can track trends over time. Tackle what you want to measure and then you can move to the next step which is how to gather that data.
Step 2 Automate Data Collection
If you haven’t already, building a database often starts with an excel spreadsheet. You can plug in numbers over time and see how your metrics are changing.
Some machines will already be creating data, and that data needs to be stored elsewhere. For the question of line output, you might be able to get some fairly inexpensive sensors set up that can start tracking data on every single product that comes off your line.
Both data from machines and data from sensors are examples of automated data. Automated data is generally cheaper to collect and more accurate than the clipboard method. It also allows you to collect exponentially more data than manual collection.
That means more profitable insights more often.
Step 3 Analyze and Make Decisions
As you collect data you need a place to store it. This is where technology comes into play. You’ll need a solution for a Data Lake as we sometimes refer to it, where all raw data is stored exactly as it came in so that it can be referred to and compared to other sets of data.
The output of this data should be into business analysis software like Power BI or Tableau. From here it’s up to your experts to look at the cold hard reality of your manufacturing data. Ask questions like “Where are you spending too much or too little?” “How do schedule changes impact the bottom-line?” “How close is your plant to maximum efficiency?”
These are the types of questions that can take you from guessing to making informed changes. If you need any help along the way just give us a call.