Summary
In the age of Digitalization of process – event based process management is here to stay as stakeholders (suppliers/ providers/ channel partners/ customers/ end users) all want to know the status of an order/ service request as it happens. Event based service management requires a holistic approach to transaction event data capture, measurement and categorization into decision enabling insights (vs data visualization alone).
Context
Admit it – you like to see a notification/ text from Amazon when your order is confirmed, shipped and delivered. Consumer order/ shipping oriented apps like Amazon, UPS and FedEx are driving to real time visibility for fulfillment to end users. This in turn provides an element of perceived control and building trust/ loyalty through each event for the end user.
Welcome to the world of event based process management. Workflow based process management automation has been popular since the mid 90’s and led to the popularity of Business Process Management (BPM) solutions. BPM enabled the connection of various business events – towards end to end visibility of process status across various functional owners and transaction systems. The move to cloud computing enabled the rise of cross enterprise systems of engagement – which provided an overlay across data and processes embedded across discrete/ independent core platforms (systems of record) – and across enterprises.
As the world has moved into the post Digital era – increasingly processes are getting more automated end to end across processes – leading to the availability of a ‘Digital Twin’ environment based on transaction data and stakeholder interactions. The advent of IOT and the access to discrete event data at a very large scale is poised to make the world of Digital Twin footprints even richer (e.g., volume, frequency, variety).
Issues to consider
Unfortunately, this is easier said than done – few business processes still have a common source for an end to end digital footprint (e.g., step of activity/ task, data and time, person executing the step, status whether new/ updated/ re-opened).
Further as data sources and volumes have grown exponentially – the ability to manage track process events in a hybrid/ manual manner has become too expensive / not scale-able.
This leads to sub-optimal manual solutions to measure performance of events across a process. This takes a lot of time and is subject to a lot of assumptions while trying to extrapolate the impact across the entire universe of transactions.
Another impact – decision making around deploying intelligent automation solutions (e.g., Robotic Process Automation, smart workflows) is less than perfect based on multiple assumptions – leading to less than expected impact from automation programs.
How to tailor the solutions to your needs
A range of event based process analysis/ mining companies have emerged over the last couple of years, including open source variants. There has been a rush of partnerships and acquisitions by the RPA solution providers as well to provide a continuous improvement cycle of ‘diagnose > redesign > deploy > measure/ re-diagnose’
However simply the ability to automate creation of a digital twin of a process from granular transaction data is not enough – it is akin to generating an x-ray or blood test panel for a human – without a hypothesis of markers to assess.
For real value, you need to start by developing a hypothesis or range of potential levers for the process that would indicate whether the performance is good/ bad (e.g., efficiency, effectiveness, productivity, compliance).
Event based process analysis is already beginning to feed smart and continuously learning forecasting solutions. For example, an organization using process mining combined with advanced analytics (for root cause analysis) – can continuously update a machine learning model to improve product fulfillment forecasting models.
Conclusion
Event based process management is here to stay – organizations need to incorporate this approach to next generation order/ service fulfillment management as part of their Digital and Analytics portfolio.
In terms of solution elements – process mining with an advanced analytics element would be a no regret move in my opinion.
Shared Services Imagineers 