Business Intelligence software is a tool that transforms unstructured data into structured knowledge and insight. Primarily, BI software is used to collect, manage, and analyze the data generated by multiple systems within a business. With this tool, companies can centralize their data collection and make the most of the information they receive.
BI software is a broad term that is used all over the landscape of modern business. With so many uses from retail, to manufacturing, it can be hard to pin down any one definition. However, all BI applications have 2 things in common.
All BI software achieves these two actions but between the software provider, the particular industry, and the exact needs of the company, there can be a lot of differences. For this definition, we will look at BI software and its application for a manufacturing setting
From a user perspective, BI software functions similarly to a computer’s operating system such as Windows, macOS, or Linux. Without an operating system, your computer’s user interface would be limited to a sequence of 1s and 0s. These numbers would be hard to understand, let alone extrapolate any workable knowledge from them.
Similarly, BI software takes the immense amounts of data generated by the shop floor and presents it visually so that almost anyone can understand it. Through spreadsheets, graphs, filtered tables, and charts, BI software takes the immense amount of data you generate and turns it into workable knowledge.
For example, imagine your company produces a very popular brand of spatulas. Your employees use work instruction software to monitor and maintain the production line while your ERP tracks inventory usage, machine downtime, finance metrics, and workforce hours.
You’ve noticed that workforce hours are higher this year than last but sales have remained steady. You need to find the root cause of this increase quickly. Luckily, you have two systems that collect the data but you’ll need to cross-reference them.
Using BI software, you take the unstructured data and create a structured timeline and spreadsheet. With this new visualized information, you find the root cause of the issue and quickly adjust certain elements of production to safeguard from higher than normal workforce hours.
Companies use BI software in situations like these and many others to track performance across their departments and see trends develop over time. However, BI software needs intelligent programs to feed data. And the smarter the software, the stronger your business intelligence actions become.
Have you heard the expression: “Garbage in, garbage out”?
When it comes to collecting data, nothing is more true. If companies receive inaccurate data from their systems, then they have no foundation to make smart and informed decisions. Likewise, BI software will misrepresent the facts if it does not receive accurate data from a reliable source.
But if companies collect accurate data, they can take this information and turn it into effective actions. Systems like digital work instructions gather data from every action that is taken by your employees on the shop floor. This worker-centric MES collects performance data, completion times, quality control/assurance information, and data from any action performed by an employee. This level of data collection makes it one of the most effective data generation tools in the industry.
Once companies have a reliable source of data, they can funnel all the information to their BI software.
To understand how data is gathered and then transformed by BI software, there are 3 linear steps.
Since BI software is an expansive application with various purposes and directives, the software can often come in many different shapes and sizes with a wide variety of tools for manufacturers to use. Let’s explore the common yet powerful tools of BI software.
What’s great for manufacturers is that you don’t have to settle on 4 different systems to experience the benefits of these tools. Modern BI software now supports these various uses and is built specifically for companies to gain the best knowledge and insight from their data.