The Difference Between Production Reporting and Business Intelligence Systems

This is the transcript of a podcast hosted by InetSoft on the topic of "The Difference Between Production Reporting and Business Intelligence Systems." The speaker is Mark Flaherty, CMO at InetSoft.

I find a lot of enterprises struggle with operational reporting and the difference between production reporting and business intelligence systems. You know classic financial production reports are those that run against a single operational system or what we call ERP system.

Typically they’re not capturing a lot of historical data. They’re just looking for information about current activity in those reports. A lot of those reports are inflexible and costly to change because either they came with the ERP package if it was a reporting package the company had purchased to run that ERP system, or it was built by an IT department running directly against the operational system and the schema for those systems is very complex so to build a report against them takes a lot of time and expertise so it’s obviously costly to change.

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What Is Production Reporting?

Production reporting is the process of generating reports on a regular, periodicy frequency that oftentimes delivered by email in paginated PDF format and sometimes made available in Web-based non-paginated format. The purpose is operational, meaning managers and frontline workers, need the information each day, week, or month in order to do their jobs.

Examples of Production Reporting

• Salesperson receiving daily leads to contact
• Customer service manager reviewing exception reports for delayed responses
• Finance VPs gettting cash flow statements
• Marketing getting a list of search engine rankings
• HR staff monitoring employees with excess PTO
• Supply chain manager being alerted to stock outs by store

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What Is a Business Intelligence System?

A business intelligence system is an organizational approach that combines technology and management philosophies to make optimal use of data in decision making. It usually brings together data from disparate systems and makes it available for all types of workers to ask ad hoc queries of the data in order to answer operational or strategic questions. The interface is usually a cloud-based interactive system that dynamically updates advanced data visualizations and permits nearly limitless slicing and dicing of data.

Need to Have an Integrated Reporting View

So displaying current data, being costly to change, being fairly inflexible, these are the attributes of operational reporting and are the result of running reporting against one system and not having an integrated view of the business or multiple processes put together.

This raises a couple of issues. One is operational reporting BI. In other words, it’s an important question because it gets to the root of who should be managing the operational reports. Because they’re running against the operational system, should source system owners create and manage those reports, or should they be run by the BI team because they are reports? A lot of companies take different sides on this issue, and sometimes it’s confusing to the end user.

The second question is, is real time BI operational reporting? Now I made a distinction about BI looking at historical integrated data, but we’re seeing a couple of things happen. Operational systems are becoming more analytical as time goes on. They’re embedding more reports, more analytical capabilities and analytical systems. BI systems are becoming more operational and delivering more real time data to users so they can be more proactive in the moment.

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Boundaries Between Traditional Operational Reporting and Analytical Reporting

So these are interesting issues as these two worlds collide. The boundaries between traditional operational reporting and analytical reporting are blurring and the architectures are blurring as well.

If you think of the business in two respects, one is there is the day to day transactional types of activities that need to occur, whether that’s in the finance space, posting, accounts payable, PO, following up on receivables, doing basic general ledger posting etc, or in more of a customer centric area, whether that’s a call center rep taking a call, being able to look up the person’s name and number and handle the call. So that’s what I’d call more the transactional side of what we call operational.

At the same time you have this historical data warehousing which is more the strategic back office decision making. In the case of marketing that might be the corporate marketing folks doing segmentation, coming up with campaigns, figuring out which offers to send out to customers. In finance that might be finance looking at the profitability of various customers and making pricing decisions etc.

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Operational Workers Need Real-Time Information

But what now we’re beginning to see, in order for those back office, or what we’re calling strategic intelligence, to really be realized, you need to make sure that the frontline operational workers are able to operate with that information in near real time as they’re talking to a customer. So an example might be if you’ve made a pricing decision or you’ve made a marketing decisions, that when the person calls into the call center, you’re still going to have the back office operational system that runs the IVR system, but at the same time you’re using intelligence to change the dialogue with that customer.

I was just with a customer this week in Europe and one of the things they do based on the intelligence they have with the customer and what they’ve done with that customer in the past week, they change the IVR routing. If they’ve sent you a new offer, when you come to the IVR, you may get routed through a number of prompts that have to do with that new offer.

If they’ve detected that you had an operational problem, a service problem with your phone as a mobile provider, then they would route you more directly to creating a ticket to getting your problem solved. So that’s an example where we’re seeing more people want to link the strategic knowledge that people have, the traditional data warehousing workload with the frontline decisions at the frontline.

Data warehousing now is evolving to not just do that top strategic intelligence but to do the tactical intelligence. The last piece is, historically a lot of these have been very stove piped so people might be getting better at linking strategy to execution within sales, but there’s not good linkage across the various stove pipes.

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Example of Value of Frontline Real-Time BI

If there’s a product issue in the engineering process, and you’re starting to see the linkages between a poorly engineered product and warranty and quality issues and the amount of cost that’s occurring because of the extra service for that product, do those organizations communicate and understand this, and are they able to proactively detect what’s happening out at the frontlines as the service rep is out finding all these issues? Does that get routed quickly back to engineering so they can redesign the product for quality purposes? We see some real opportunities to link that strategic decision making and defining where the organization should be headed.