How to choose manufacturing software for business intelligence
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Ever get the nagging feeling you should be paying more attention to the fast-moving manufacturing business intelligence (BI) software market? After all, manufacturers are increasingly relying on BI and analytics software to help them reduce costs, improve quality, optimize the supply chain and boost customer service. If it has been a while since you last checked out what your ERP vendor has to offer in the way of BI, it might be time to schedule a chat with the account rep.
However, although many manufacturers do stick with BI offerings from their ERP vendors, users shouldn't stop there. Today, there are still independent solutions on the market that can drive real benefits for manufacturers, experts say. Whether it's a large, established ERP company or a specific BI software vendor, vendors are offering capabilities and features of particular interest to manufacturers.
Dashboards, scorecards and other visual key performance indicators, or KPIs, are easier to understand at a glance, said Marty Carney, CEO and president of Dallas-based WCI Consulting, a firm that specializes in BI.
"What's really changed is how you visualize data. The dashboards now make more sense. They're easier to look at," Carney said. Executives in particular love their eye candy, he added. But next-generation dashboards are critical in keeping workers focused on the right metrics -- often in real time so they can make adjustments quickly if things start to go south.
Useful new manufacturing BI dashboard capabilities include in-memory processing, advanced search functionality, the ability for users to combine data from multiple sources, mobile capabilities and the ability to link insight to action, according to Carney.
Performance management key part of manufacturing business intelligence
Many developments have taken place recently in BI tools that relate to performance management as opposed to operations, said Ashwin Patil, analytics and information management leader at Deloitte's Consumer and Industrial Products group in Dallas. For example, many tools do a better job of integrating real-time data from production and fulfillment to give a day-to-day synopsis of how the team is doing toward meeting goals, he said.
BGF Industries, a Greensboro, N.C.-based industrial fabrics manufacturer, recently implemented a dedicated BI suite to create an early warning system for potential problems before they hit the market. Previously, BGF was unaware of quality issues until it was notified by a customer.
"We would get that dreaded phone call from the customer," said Bobby Hull, corporate quality assurance manager at BGF. "Your customer should never know about an issue before you do."
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BGF implemented the BI system to obtain daily trend analysis. "We wanted to see if the properties of our products were shifting over time," Hull said. The investment will repay itself immediately if the company can avoid even one major field claim, he said, acknowledging that it is difficult to prove a negative.
"The system refreshes the data, and we plow through it every night and see everything that is showing a trend as of yesterday," Hull said. The system will be critical to a new initiative that is about to kick off. "We are trying to eliminate the acceptable level of defective product. We are going to zero. That is a huge difference in mind-set. That has forced us to look at process numbers, labor numbers, waste numbers," he said, all of which feed into the system and get spit back out as dashboards, and users can take those and drill down for more insight.
Using predictive analytics with manufacturing business intelligence
Beyond the advances in performance-management-related BI, predictive analytics is a hot new area, according to Deloitte's Patil. "This has become really interesting. Predictive analytics is focused on business scenarios and decision making," he said. "Manufacturing executives buy these tools because there are burning questions they need to answer. What keeps the managers up at night -- that's what predictive analytics will dig into."
Patil suggests that manufacturers use predictive analytics to get answers to such make-or-break questions as, "When will my production line go down unexpectedly in the next six months?" Users can correlate variables -- data collected from controls equipment, for example -- to a milestone or event, and predict when next that milestone will occur, he said. If you know the drill bit will break when the temperature goes to X and the vibration goes to Y, maintenance can be done before those conditions are met so the production line doesn't go down.
"All of the major vendors are investing in predictive analytics," Patil said.
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