Large organizations need to understand their processes much better than they currently do.

Today’s organizations are complex, interconnected global entities. Yet they are often unaware of how the business processes that underlay their daily work are constructed.

Organizations that are committed to improving processes, compliance, and customer outcomes evaluate and monitor process data on an ongoing basis.

However, a great number of organisations don’t measure or monitor process data.

As a result, delivering business outcomes such as improved customer experiences, reducing the cost of operations and improved employee work life balance, are less likely to succeed.

Many organisations run fragmented processes across business units.

Process analysts often must stitch together broken processes or pieces of processes done by individual departments across a fragmented organization via ‘time and motion’ studies that shadow user behaviour.

Identifying ideas to improve processes often meant finding areas where manual effort was high and automating them using a variety of software tools including robotic process automation or business process management software.  

Automation projects have relied on SME interviews to gather current process details and baselining volumetrics associated with the process. As lean practitioners can attest to, this is a very time and sticky notes consuming and subjective process. Yet quite often interviews do not reveal the actual underlying true situation; and if they do the situation changes before their work is complete.

Enter process mining!

Process mining is coming from the need for organizations and businesses to have better knowledge of the processes. These processes, tasks, and standards are needed to understand what their employees are doing and performing each day. Since businesses, analysts, and even a company's PMO - Project Management Offices have had issues capturing and updating these standard processes. The need is still there and almost everyone it seems is looking for a solution for it. Introducing Process Mining! The only issue now is what vendor to go with, how do you implement it, and what’s the TCO - Total Cost Ownership of it.

 

Doug Shannon, Global Intelligent Automation, Manager.

Recently quite a few process mining tools have come to the market. For example, automation companies, such as UiPath and Automation Anywhere are improving their task or process mining capabilities to pinpoint automation opportunities. KYP.AI attempts to go beyond traditional process mining to hardness AI to generate instant insights, prioritised automation recommendations and resolved business cases.

Other companies such as Celonis, which started its journey largely on SAP (ERP), have a broad vision to improve business operations efficiency, performance, and sustainability through disciplined process execution management at every level of an organisation.  

The use of technology in order to understand work, is well over due. The historical way of trying to capture both data & knowledge from our people alone is full of bias and gaps, Process, Task and even Communications mining, are not just nice to haves but a business imperative through the next decade .

Wayne Butterfield, Global Lead Intelligent Automation Solutions, ISG Automation

 But what is Process Mining?

 Process mining stitches together individual business processes to create a holistic end to end view of an organisations business processes in visual format. 

The visualizations allow us to ‘see’ process variations by volume and allows a drill down into specific process flow scenarios.

Process analysts can then visually identify delays and process bottlenecks.

What is Task Mining?

Task mining tracks discovers the tasks that complete the individual steps of that business process. This view provides insight into the human action steps in a process. Given the rise of citizen developer programs, task mining is often utilized to identify and develop pipeline for the citizen development community inside an organization or team.

While Process Mining leverages system data to visualize the process, task mining on the other hand captures individual user (desktop) data to visualize the steps individuals take to get work done. While Process Mining is more holistic in its approach, task mining is a great tool build one’s automation pipeline. Particularly, when a company chose to go down the citizen developer path and enable SMEs to automate their work, within the governance framework of the company of course, task mining is a great tool to help teams capture user data create awareness how work gets done within a team and then automate it.

Martin Jahn, Customer Success Leader & Process Expert

Together:

Together, task mining and process mining can present a complete picture of a business’s processes and can help identify opportunities to improve upon e.g., a customer service, finance, HR or supply chain process.

How does Process Mining work?

Employees carry out a series of steps to complete a process. Every time an update is made, an entry into IT systems such as ERP is created, leaving behind a ‘footprint’ in the IT system. Process Mining tools use these ‘footprints’ to create a virtual, visual copy of the process flow. Over a period of time this allows a reliable version of the process flow to emerge.

1.     Selecting a business process to measure. Identify a business process to study, identify process KPIs and identify each application that is used in the process. Task mining software tools may need to be installed onto a user machine to track user actions. Applications that are of interest need to be labelled so that all actions are tracked to the right software application.

2.     Collect and connect process data. Process Mining largely relies on application logs. Most ERP systems have standard log files that form the basis of this data. Once log data is gathered, AI algorithms work through the data to create a process flow. Similarly, for task mining, user action is classified into process steps. AI helps classify steps into process actions and connect data across a process. Interpretation of the process is important, and analysts may need to be involved so that steps are classified correctly.

3.     Check the story emerging from the process.  Data will start to tell a story. Process flows need to be reviewed by drilling down into each business process scenario. Each process story needs to be mapped to actual SME experience.   For example, in accounts payable processing, high value invoices may be subject to additional scrutiny for legal and regulatory reasons. As a result, they may take longer to process. It may not necessarily mean that there is a process bottleneck. It is critical to bring SMEs with business process knowledge and process mining skill sets together when determining what is currently happening within a process flow.

4.     Identify the right process opportunities to improve upon. Process mining tools make it possible to track the effectiveness of improvement initiatives and ‘slices of time’ can show how outcomes and KPIs are impacted. They can help to baseline, measure and drive process improvements while also helping to drive intelligent automation efforts. Now that process specialists can measure processes based on real data and spot bottlenecks, they can drill down into root causes of delays, non-conformance, or experience issues. Once these are identified, appropriate strategies can be put in place to address them. In addition, impactful visualizations are ideal for mapping process pain points so improvement can be made, seen, tracked, and measured over time.

Pros of process mining

1.  Process owners can get a virtual process blueprint with KPIs based on their actual data without a lot of manual effort
2. Process leaders can track and quantify outcomes from improvements on a continuing basis
3. Task mining surfaces usage and training issues. These can improve both the employee and customer experience.
4. Improved operational efficiency i.e., process simplification, standardisation and automation.
5. Faster continual improvement efforts.

As departments grow bigger in relation to company growth, they start to lose the knowledge of what happens when they hand something off to another department and how changes in their processes could affect the receiving department.

For example, changing one small step to save 1hr per day in Department A could mean increasing process time by 1hr per day in Department B.

With the utilization of a process mining tool, leaders can take those blueprints and not only improve their processes but connect their processes to other departments processes opening a whole new level of process improvement opportunities.

Breaking down those walls and silos between departments could not be more important.

Ryan Wakefield, Senior Software Engineer

 

Cons of process mining

1.  Process mining relies on IT systems and logs to stitch together data. Legacy systems may not have such logs or may be limited in the insights they can generate.
2. Process data is only as accurate as the quality of data available.
3. Process Analysts may need to spend effort to stitch the story together.
4. A formal organization structure to use process mining and drive improvements is a necessary investment e.g., a Process Centre of Expertise of Business Process Optimisation team.

Productivity mining can help to rapidly address most of these issues by providing insights on the trifecta of people, processes and technology.

It increases visibility at scale to show what could be improved, integrated and digitally transformed.

It highlights the causes of productivity problems to help the teams achieve their goals and subsequently improve their job satisfaction, e.g. how prescribed process steps work in practice, where to automate or transform in order to generate hyper productivity combined with work-life balance for employees.

Adam Bujak, CEO, KYP.ai

Conclusion

Large organizations with a commitment to continuous process improvement will benefit from process mining or process intelligence platforms. Process Mining can help baseline current process performance, identify areas to improve and then track results over time. This can support in fostering a data driven decision making culture and continual monitoring can also surface ideas for ongoing intelligent automation and digitization.

Process Mining technologies offer organizations the ability to fully observe, understand and fix the end-to-end business process or value chains enabling them to provide more value to both customers and employees. Given the new realities in the workplace, particularly increased remote working practices, there is a need for automated process discovery solutions which shorten the review cycle and accelerates time to value.

Process & task mining journey is a continuous cycle, like Deming’s plan-do-check-act or the DMAIC cycle. The more iterations occur, the higher the confidence and return on investment.

Like an automation program deployment, process mining requires strong executive-level sponsorship and support and a commitment to operational and process excellence.

That said, if you already have a lean, continuous improvement, or operational excellence capability in your organization, process mining is the perfect complementary solution in their toolbox to drive a step change in your company’s performance, and a good product owner for the technology.

Whether the journey begins by exploring a process improvement area, validating a compliance check, or identifying maintenance issues, process mining will provide the transparency and justification to apply process re-engineering or intelligent automation solutions.

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