This Supply Chain Matters commentary continues our market education series to helping readers to differentiate the nuances of traditional vs. operational supply chain business intelligence needs in SAP environments. In our last posting in early September, we pointed out that supply chain business and operational intelligence is not solely about business reporting, but increasingly focused on analysis of ongoing performance, uncovering hidden risk factors and synchronizing performance of the entire supply chain.

Supply chain teams require intelligence capabilities appropriately configured and tuned for analysis of bottlenecks or supply and demand shortfalls. The design principle of this approach is root cause analysis, to tap important data and information existing in specific applications. The premise is to identify bottlenecks and provide early warning to operational process outliers and exceptions.

This Editor recently had the opportunity to interview Every Angle Software executive Richard den Ouden, Managing Director for North America. In our interview, we explored specific examples of how operational intelligence challenges are manifested in typical SAP environments.


Question: Richard- In your travels across North America, what forms of supply chain operational complexity or information challenges do SAP ERP or SAP SCM customers typically describe?


We find that in many SAP environments, users view their system more as a black box. The frustrations they communicate are in the inability to extract needed information in a timely manner and in a user-friendly way. Because of these limitations, often, two routes are taken:

  • Asking IT to build operational or custom reports, which result in added time constraints or miscommunication as to information requirements.
  • Users themselves downloading raw data into Excel spreadsheets for analysis but risking the timeliness and context of that data.

If SAP users do have information, the challenge is often in the context of lots of statistics as to what has happened vs. operational intelligence indicating what needs to change, or where operational bottlenecks will occur. Some users do not take the current situation as acceptance and instead go with the limited information they have been able to gather.

Typically, when we demonstrate the capabilities of a true operational business intelligence application, it is viewed as a breakthrough in effectively mining needed information or being alerted to operational bottlenecks.

We often approach SAP backbone customers with a three day live demo session utilizing that customer’s actual SAP data extract. On day one, we load all of data and demonstrate the capabilities of a true operational intelligence application. On day two, we interactively allow the customer to describe current business process, financial, supply chain or business operational challenges. In day three, we demonstrate the full capabilities of the application with live data, identifying bottlenecks and improvement areas including pending imbalances in supply or demand, inventory mismatches caused by MRP driven order changes, order entry or master data mismatches. That day often results in uncovering data quality or in laughing and crying at the same time.

In one typical operational example, when product demand changes upward, MRP creates a purchase requisition for more material. When demand changes down, MRP creates Exception Notices in MD04, and here is the problem.  Unless users mine MD04, then manually calculate the impact and convert that to a specific action (like reduce the open purchase order), the now unneeded material flows in. An executive would ask, why would a procurement team place orders for materials we do not need? In most cases they would not, unless it was a spot order for a great price, a typically constrained material, or some other special case. 

But in the usual scenario, MRP produces purchase requisitions that Procurement teams then convert to purchase orders among specific suppliers.  MRP created these purchase requisitions as a result of a calculation that considered inventory on hand and due in, and an expected demand profile .Real cash money is spent to pay the supplier, the freight, the receiving dock workers, and locations in the warehouse are taken up.  It is not uncommon to find several million in unneeded procurement.  In Food and Pharma, where many raw materials have a shelf-life, this condition is more acute than in repetitive discrete where the material could eventually be used.

Question: Can you describe a few industry or supply chain specific examples?


Typically we address four specific use cases related to improved operational business intelligence within SAP environments.

  1. Analysis of data quality which is the foundation of any effective business process. Here we help customers with the importance of master data. A proliferation of products and product changes contribute to master data inaccuracies but the transactional data errors are where the money is lost. What makes Every Angle unique here is that we automatically read the master data, like BOM’s, (Bills of Material) and use this in our calculations.  If a BOM changes, as they frequently do, no one has to fix Every Angle.  We automatically read the new BOM each time we load data from SAP. 
  2. Analyze historic performance to uncover operational trends.
  3. Execute open order management processes to uncover mismatches in back orders or delivery commitments.
  4. Identify any mismatches in supply and demand.

Every Angle’s operational business intelligence capabilities are applied to many industry settings.  For instance:

Food and Beverage: What is sales demand vs. what production is making?

High Tech: What is component availability and have purchase orders changed as a result of frequent bill of material changes?

Pharmaceutical: Will the current backlog of batch production releases fulfill the right demand?

Retail: Here, master data is key. Do we have the right planning profile and replenishment data? Does current operational planning data reflect on-time delivery of supplies?

Wholesale Distribution: Do we have the right balance of quantities purchased with sales order demands?


Question: How do you view the key differences between business intelligence vs. supply chain focused operational intelligence?


The key difference relates to what information needs to be delivered to what specific target audience.  In essence, it is targeted intelligence and more informed decision-making.

Business intelligence is essentially an analysis of past performance, for example sales volumes or financial data. This serves the purpose for a great presentation of management information related to business performance.

Supply chain operational intelligence is more focused; Is the supply chain able to effectively and profitably fulfill product demand? Where are the specific gap areas or negative effects on profitability? Operational intelligence is more focused on the predictive aspects of what is about to happen.

Business intelligence provides great statistical information related to historic performance but operational intelligence is where firms uncover data and process mismatches and reduce unnecessary costs.


Question: What role do forms of prescriptive analytics play in these types of challenges?


A typical business intelligence application provides limited predictive capabilities and as noted previously, reflects more on past performance.  To be predictive, information is needed as to what is occurring across business operations and across the supply chain.  Operational intelligence takes into account all existing planning and fulfillment information, for instance, what sales order will not be delivered in two weeks because of an operational constraint.

Planning and smart algorithms designed within Every Angle predict what specific exceptions will occur and when.  For example, there may be huge lot sizes defined in SAP master data that are a mismatch to specific customer needs, resulting in excessive production costs. 


Question: What other observations or wisdoms can you share with our reader audience regarding these capabilities?


There are great technologies available in the market today.  However, firms often forget that operational effectiveness comes down to people and their day-to-day needs in accurate information, easier to use applications that contribute to more informed decision-making. It is about helping people in their daily work routines and getting in-control, trusting systems as opposed to questioning the information provided.

Firms have invested in the basics such as deployment of an SAP ERP backbone or SAP SCM but it is ‘just’ the data and process foundation, which is great. But, this does not provide operational transparency about data quality and process performance to the business users in a fast and flexible, self-service way.  Every Angle provides this, with a native and certified integration with SAP SCC, and it therefore is a “no-brainer” complementary solution for SAP customers.

People instead will invest more time in not trusting the system and instead in trying to gather and assess needed information vs. making timely and better informed decisions related to operations and supply chain.

SAP business users and IT support teams may well be frustrated in understanding the timetable and implications of where SAP is headed in its Integrated Business Planning vision, data and operational intelligence milestones. An SAP implementation of ten years ago cannot keep-up with the today’s more rapid speed of business change and requires that people have tools that can mine more predictive information much quicker, and in operational context.

Take the responsibility to fix and address these needs today.


We would like to thank Richard Den Ouden for his specific observations related to solving operational business intelligence challenges within operational SAP backbone ERP environments.

For further information, readers can visit this Every Angle Software web site.

Bob Ferrari

Disclosure: Every Angle Software is one of other sponsors of the Supply Chain Matters blog.