“Transformation for the sake of transformation doesn’t matter unless you get real, significant outcomes,” says Scott Layton, Vice President of Global Finance Transformation for IBM. That’s a salient point given that IDC predicts $6.8 trillion will have been spent on digital transformation investments between 2020 and 2023. Despite this investment, businesses still struggle to realize their digital future and make practical use of multiplying data sources. These struggles result from lack of insight into how interactions happen and where information lives. That’s what process mining paired with execution management can solve.
Process mining reveals actual, actionable workflow data
Organizations have turned to process mining to gain more from their data. What is process mining? It’s a method that applies specialized algorithms to event log data to identify trends, patterns and details of how a process unfolds. That information is then used to discover, validate and optimize workflows.
Enterprises use information systems, such as Enterprise Resource Planning (ERP) or Customer Relationship Management (CRM) software, which create audit trails of work processes that are recorded as log data. Process mining takes that log data and creates models that show an intuitive, explorable visualization of a process from end to end. The map uncovers the details and all the variations that a process can take.
The models can reveal the root causes of deviations from the norm. They help managers see if processes are functioning as intended and, if they aren’t, how that can be fixed. Process mining doesn’t always lead to automation, but it helps show how automation, intelligence and other technology might be used to improve a process and the resulting workflow.
Process mining gets to the heart of workflows
Process mining pinpoints where there are process inefficiencies and silos, as well as untapped value inside workflows. But those revelations alone aren’t enough. That information must then drive execution management—actions—to fix those problems and derive value from unused sources. Execution management is a new category of software, created by IBM ecosystem partner Celonis, that uses process data and intelligence to drive action. It works from within the same platform as process mining but takes it a step further by showing what actions can fix problems, particularly using intelligence and automation. It then allows users to take those actions through APIs, RPAs, or source data changes.
This is analogous to surgeons performing heart surgery. Surgeons learn how hearts work from their education and past experiences. Knowing a patient’s symptoms, they can guess what the problem might be and how to fix it. Yet with advanced medical imaging, they can see a specific patient’s heart in exacting detail. They see actual blood flow and blockages for this particular patient. Those images paired with robotics tools allow them to act on what they see with greater precision. Years of past experience can’t compare to the intelligence gained from seeing that real-world, real-time image or the meticulousness gained by the robotics used.
This is how process mining and execution management software work. You can guess what your processes and workflows are like, but this software taps reams of often overlooked and untouched data. It shows the reality of process flows and, based on that, how problems can then be fixed as well as providing the tools for that fix. Like medical imaging for the heart surgeons, this software creates a picture from actual data to create an up-to-date and real-world view of current workflows and actions to be taken than can then fix and optimize them.
What process mining and execution management look like in practice
How does this work in practice? Layton describes a recent experience with a client using process mining and execution management powered by ecosystem partner, Celonis. “They said, ‘In two weeks you’ve been able to identify something we’ve been trying to figure out for 17 years,’” Layton says. “We looked at millions of transactions through their ordering system. Out of four million transactions, only 7,000 flowed the way they thought they would.” The client guessed there were 30 to 40 ways an order could process. In reality, there were 300,000. “We mapped their entire universe of transaction processes, giving them a full view of how it works today. That allowed us to dramatically reimagine a better way to build a new system for it. That’s just something we haven’t been able to do before with clients to this extent,” says Layton. This greater insight has been powered by the strategic partnership between IBM, Red Hat and Celonis. The result for this client was a shortened development and build-time for the new system, more efficient processes, as well as lower costs.
Jonathan Wright, Global Managing Partner and Service Line Leader, Finance and Supply Chain Transformation for IBM, describes a different scenario with a customer with a high number of invoice disputes. He says, “With process mining, we can understand the processes around that issue and ask the right questions. Who talks to whom? Why are certain steps in a workflow? Why would an invoice discrepancy ever occur?” With this client, the process involved many people trying to manage the dispute without much transparency or insight into what had gone on before. “We put a blockchain solution in place, where the entire chain of action was visible. This connected everybody with hyper-extreme visibility and eliminated back and forth communication trying to figure out the dispute. That transparency allowed open collaboration and intelligent workflows. This type of visibility solved the problem.”
Any industry, any company, any process
Process mining and execution management can create process models from any set of event log data. This is true across sectors and companies of any size. It’s also true of processes of every kind, like order management and invoice disputes, as described above, or even more complex activities, like finding and streamlining overlapping processes and systems in company mergers and acquisitions. These tools help deliver the promise of digital transformation—efficiency, flexibility, transparency and speed—by using real-time data to drive meaningful action.
Celonis process mining is embedded into IBM Garage, working in an agile manner to pinpoint areas for process improvement that can have the greatest impact. Using the Garage methodology, clients can co-create ideas to turn into MVPs to scale across the enterprise and quickly address high impact areas.
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