Business Process Improvement - Digital Payments Transformation:

Lessons from the Field

Abstract:

The aim of this experience report is to highlight the challenges and benefits of applying a wide-range of process improvement techniques in a complex service environment, contrasting the benefit of continuous process improvement with the frequently over-hyped transformational improvement program.

Payment processing is a highly regulated, high-value, time-critical, and high-risk function. The Run Team responsible for this function at the bank comprised c 1,500 FTEs over 32 countries, but was predominantly based in 4 major processing centres. The operating environment was complex with over 8,000 process variants and fragments. The processes were run on poorly integrated, legacy technology, with many manual steps and workarounds. Performance at the start of the journey was poor. Multiple regulatory breaches, poor quality, unstable processes, productivity and automation rates significantly below global competitors and low levels of staff engagement.

The talk will highlight the business process improvement approach the author took to rise to the challenge. It will cover deploying a standard process improvement path with an array of techniques drawn from a broad operational excellence toolkit from simple lean/six-sigma tools to short-interval control, RPA, AI/ML and developing digital twins. The outcome was successful to the extent that the results were published in the bank's annual reports and half yearly updates for 5 successive halves - rare publicity for a back-office, operational function. The productivity benefits outlined in the transformation business case were delivered within three years - by the Run function. Despite the overall success of the program, many aspects did not go to plan and some did not complete. The lessons learned touch on a wide-variety of the topics across all of the categories outlined in the BPMDS program overview. These range from working across time-zones and cultures, leadership and politics, governance and control, the role of process models, opportunity identification and prioritisation with limited data, reference models and classifications, privacy and ethics, dealing with significant variation, the downside of RPA, AI/ML and blockchain.