Case Study – Automated Process Modelling

Posted by Dario Hudon-Verrelli in APM, Automated Process Modeling, Case Study | 0 comments

This case study was conducted at a prominent oil and gas firm in Canada


A prominent global oil & gas corporation was investing in a large capital project and wanted to implement SAP as a footprint extension. As the project proceeded, the SAP team grew and the organization wanted to determine if the SAP footprint extension would have the desired impact on the business processes.

There were two operating units in the mix:

  1. 1)  Capital projects team
  2. 2)  Operations team (operating the new facility)

The operations team was working with the project SAP team to implement new SAP design elements in the current operating facilities, prior to the new facility being built.

The SAP project manager wanted to show the new changes were going to have a positive effect on the business. In particular, he wanted to model the existing processes and changes. In parallel to the SAP project, the operations team was improving business processes and enhancing master data to improve the efficacy of the operational processes in SAP. All of this work was to come together in the existing facility and be ready for the new facility.

The organization wanted a fact-based approach to process modeling that was not subject to interpretation, was rigorous and sustainable. They wanted to do the analysis now, and then again in the future. Repeatability was key.

The oil and gas firm was shown the Automated Process Modeling (APM) tool from Code Expert. They ultimately selected the tool for the analysis process. APM is an advanced operations research based analytics tool that performs off-production analysis of existing business processes. Providing visualizations of typical flows, repetitions, and loopbacks, APM identified process inefficiencies and bottlenecks where they exist, and highlights the right processes for improvement and optimization


Pilot Project

After selecting APM from Code Expert, the oil and gas firm began the project. The project focused on the Enterprise Asset Management and Procure to Pay processes. Key processes were identified and the business looked for answers to the following types of questions:

EAM (Enterprise Asset Management)

  • How long between status changes on work orders
  • Show notification business processes by notification


  • How often do we change field data: functional location, cause code, work center, cost schedule date, etc
  • How often do we reverse work order complete status to process invoices
  • What data is missing on work orders: maintenance item, symptom, cause code, priority, breakdown indicator, etc

P2P (Procure to Pay)

  • How many times after a PO is created do we change it  How long do users take to complete a requisition from the time they start it
  • How long does it take to assign vendors to PO’s
  • How many PO’s have been created automatically from a requisition
  • How much time does it take to chase down a GR for a blocked invoice
  • How does cross business unit efficiency compare for supply chain processes?

APM showed that for each notification created in the period, there were an equal number of notifications from previous periods that were being changed. This resulted in over 100,000 changes to notifications in one year. Of those the SAP system automated completed, 12% of those were changes. 88% of the changes were completed manually.

The evaluation also showed when work orders were completed in SAP, the KPI for work order closure was driving user behavior to close work orders quickly. Cascading down the process line from the work order closure , APM showed evidence that invoice payment was blocked and work order closures were being reversed. APM also showed that downstream processing of invoices were delayed up to 25 days. The culprit appeared to be a combination of work order closures and delayed goods receipts.

APM also revealed that when buyers were involved in the assignment of vendors to a purchase order from a requisition, the process of creating a purchase order took 3 to 6 days longer than when the SAP vendor selection was automated. The analytics were key in identifying potential training needs and to help refine process emphasis.


Expanding APM’s Role

The pilot project took 7 weeks to complete. Subsequent to the results of the initial process, modeling, the oil and gas firm engaged Code Expert for 300 additional days to complete the follow up work and expand the use of APM. Once the follow up analysis was completed, the oil and gas firm purchased a software license and uses APM’s dashboard to continuously monitor this process.


What’s Next?

As part of the overall project, Code Expert demonstrated the ability of the Automated Process Modeling tool to provide a scientific basis for process improvement. The process models created in APM can be locked down and utilized in a production version of the software complete with alerts, charts, dashboards and ongoing automated process monitoring that results in a visual representation of business process that can be acted upon. APM provides a standards-based modeling environment and tools for refining existing processes.

Code Expert is working on modeling EAM, P2P, contracts management, material master quality and process management, along with transaction quality monitoring. Discussions are underway with the oil and gas firm for extension of the models to include additional facilities and plants throughout North America.

As part of the ongoing discussions, the oil and gas firm is considering APM for master data quality management and profiling, real-time transactional quality management and monitoring and business process flow monitoring with alerts and charts.


About Code Expert

Code Expert Canada offers a suite of process mining and business process management software. Combining the disciplines of data mining, correlation analysis and process modeling, our process mining technique extracts data stored in systems to reveal event patterns. Using Code Expert’s models, business can diagnose problems based on facts rather than theories. For more information, please visit

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