What You Need To Know About Industrial Analytics to Optimize Your ERP
By: Scott Jessup
It seems like only yesterday that enormous software providers such as Oracle or SAP had the resources and sophisticated tools to integrate business intelligence with enterprise resource planning (ERP). Only big, expensive, enterprise-level ERP systems had the data collecting and processing firepower to conduct analysis on any meaningful level – it was just too expensive to run and maintain.
But that’s all changed.
Today, ERP systems are remarkably faster, more flexible, more agile, and more powerful – at a fraction of the cost of those legacy systems. Modern manufacturing now has the tools to gather, monitor, manage, and analyze data faster and more easily than ever, using industrial analytics to turn information into knowledge and knowledge into improved processes and performance.
Today’s ERP systems now enable even small to medium size businesses (SMBs) to gather vast amounts of information from multiple processors across a complex environment. But the trick is how to easily and efficiently extract and analyze that information in a useful manner.
Some people believe that ERP is all about entering information into the system. In reality, it’s more about getting information out of the system and utilizing analytics to create value by identifying weaknesses and bottlenecks that can be fixed so processes can be optimized. After all, inefficiencies are the result of specific behavior (certain tasks are performed a certain way) and the purpose of analytics is to drive behavior.
The challenge, though, of using industrial analytics is the possibility of driving the wrong behavior. For example, if someone gets punished every time there’s a stock-out, the purchasing agent’s going to make sure he or she buys plenty, which can lead to overstocking.
Industrial analytics vs. reporting
Let’s be very clear – reporting is NOT analytics. Reporting is simply the act of providing data and numbers by themselves don’t provide anything. There needs to be a goal or benchmark to which the numbers can be compared. It’s about using measurements for analysis to identify patterns and establish root causes to improve existing operations. Measurement should never be done just for measurement’s sake. The goal should be the collection and interpretation of real-time information.
Reporting is simply a bunch of data. A list of every customer order entered or invoices sent out. Analytics helps you understand what this data means. It can be used to draw an informed conclusion so that behavior can be modified to improve processes, performance, and profitability. Analytics, when aligned with corporate strategy and business goals, can help a company better understand where it is compared to where it wants to be.
So what operational areas are important to focus on for industrial analytics? Here are some basic metrics to consider:
1. Machine utilization
It’s pretty simple. If your machines aren’t running, you’re not making money. However, it’s not quite that simple. Beyond simply ensuring your machines are running, it’s important to determine if they’re running efficiently and effectively. For example, are you making the right products at the right time? Are you making them on time?
2. Inventory turns
Analyzing inventory turns helps you determine if you’ve got the right product mix. If you’re turning inventory on a timely basis, then you’re producing the right product mix.
Analyzing purchasing is popular with many manufacturers. Are you purchasing too much, too little, or just enough? Analyzing inventory and purchasing together can be particularly valuable.
4. Supplier performance
A reliable, efficient supply chain is clearly important, especially if you’re practicing a lean strategy. Supplier performance affects everything, from planning to production to costs and customer satisfaction.
5. On-time receiving
Most companies just look at what was received and when, but that’s not quite enough. Instead, it’s important to also analyze when it was scheduled to be received. Measuring the performance against the plan yields much more valuable information for optimizing your supply chain.
Rework and scrap are direct costs that just suck money out of companies. However, some organizations miss an important component of this metric, and that’s rework and scrap within work-in-process (WIP). It’s easy to measure rework/scrap against products already manufactured and in inventory, but what’s missing is the fuzzier but vital metric of additional raw material and time consumed doing rework before the product is finished.
These six areas of industrial analysis are good places to start if you company is not already analyzing ERP data. However, none of it will matter if your workers are not actively engaged in the analysis. They are the ones most familiar with operational processes and can best drive process improvement. By using industrial analytics to gain valuable knowledge and insights from your ERP data, you and your employees are better positioned to drive positive behavioral changes that can improve overall organizational performance and ultimately profitability.