In their pursuit of lean manufacturing and demand-driven strategies, manufacturers are increasingly interested not just in improving their real-time view of manufacturing data -- such as job status, work in process, shop floor inventory, quality data and capacity utilization -- but also putting it in context with business data such as customer orders, product specifications and cost information.

Call it business intelligence, manufacturing intelligence or supply chain intelligence; it all boils down to a need to answer strategic business questions that require the juxtaposition of data from enterprise resource planning (ERP) systems with plant floor and manufacturing execution systems (MES).

"Manufacturers need to use a lot of real-time data but in a broader business context, such as relating plant performance to schedule adherence or quality data to production orders," notes Colin Masson, an analyst at AMR Research in Boston.

And whereas typical business intelligence systems pull data from a transactional system into a data warehouse to analyze historical trends, manufacturers need to view data as the event is occurring and respond before it is too late.

"If you're trying to use manufacturing data while you can still correct the quality problem or adjust the length of the production run, you have to look at that data in something closer to real-time," Masson explains. "The emphasis in manufacturing intelligence is to detect and correct things before you end up disappointing the customer."

With that in mind, here are some issues that manufacturers face in their efforts to build better intelligence into their processes (click here for additional online resources).

Don't Get Caught up in Semantics

The software products that help gather and analyze the required data for manufacturing intelligence don't fit neatly into a single category. Traditional business intelligence systems hail from the likes of Oracle Corp. with Application Server 10g, SAP America with xMII, SAS Institute Inc. with SAS Enterprise BI Server and Cognos Inc. with Cognos 8. But what manufacturers need is a layer of software that pulls data from ERP systems with data from MES and plant floor systems and gives it meaningful context, says Ken Brant, research director for manufacturing at Gartner.

That layer can come from the ERP vendor, the MES vendor or from a pure-play manufacturing intelligence provider, he explains. Examples of the latter include Activplant Corp., Informance International, and Incuity Software Inc., all of which enable multi-site performance analysis.

But manufacturers shouldn't waste time trying to get a handle on software categorizations and terminologies, Brant advises. Instead, they should spend time developing a clear strategic objective. "Don't pay attention to terms [the vendors are] using," he says. "Think about the kind of intelligence you want to act on and the kind of presentation of data you need and then decide which company has the right approach for your objectives."