Today, I like to share key insights into one of the hottest trends in Intelligent Automation - Process Mining/Discovery.
Over the last few years, I have interviewed many experts on Process Mining/Discovery on our Bot Nirvana podcast, We have brainstormed about it in our Bot Nirvana Club. I have also spoken to many clients, vendors, and experts. Based on those, here is what I have understood about the current state of the market, the significant challenges we face, the best practices people are putting in place, and a way to choose the "best" tools for you.
📢 Before we dive in, here is a quick announcement:
We are getting to ready to launch our next cohort of the Digital Automation Club. We are offering an early bird discount if you apply within the next 48 hours!
The process mining market is taking off. It is still an emerging area though and is most effective for certain types of processes. Here is what we are seeing right now:
The number of organizations embracing the technology is on the rise: E.g. ABB, ADP, CISCO, Mars, Uber, Lufthansa, Dell, etc. As per Deloitte, 63% have already started and about 87% of the surveyed plan to use Process mining.
Company valuations in this space are rising. Celonis recently raised 1 B at a $13B valuation. We also see many acquisitions especially big-tech adding the technology. E.g. Microsoft(minit), SAP(Signavio), IBM(My Invenio), & more.
The Terms wars are also heating up as vendors jostle for space. We have multiple terms like Task mining, Process Discovery and Process Intelligence that vendors have added. The analyst coverage is also increasing in the space.
The market is maturing fast as there is a definite need for business processes to be mapped out, analyzed, and improved or automated. Automation is a key driver right now but the big opportunity is plugging revenue leakage due to inefficient processes which are as high as 30% as per an IDC study.
All of this does not mean you should dive in. It is prudent to understand the benefits, challenges, and best practices to see how it addresses your unique needs.
Benefits and challenges
Using the power of Data and AI, Process Mining/Discovery enables you to discover, monitor, and improve business processes. Here are a few key benefits that early adopters are seeing:
You get an objective view of your processes & variations compared to what's in people's heads.
This improves the overall visibility and transparency of process flows.
Organizations are using the insights gained to reduce average process cycle times. This can be through Optimization, Standardization, and/or Automation.
Unfortunately, I am starting to hear client dissatisfaction as hype increases and promises are not kept. Some key challenges I have heard of are:
Data issues: Finding and ingesting the right data required for mining is the biggest challenge especially when you have large and legacy systems.
Wrong purpose: Many are failing at Process mining/discovery for automation as they are using it for the wrong processes - those that were clearly not amenable to automation.
People coordination: There are many stakeholders to handle. You need to involve not only business teams who understand their process but you also need experts from ERP systems who can do data validations and data modeling, and also include IT, security experts
So ensure you have the right data, work with all stakeholders and ensure that the technology can meet your goals. There are some best practices people are discovering as they learn by failing.
Best Practices
Here are some key best practices as you start out with process mining/discovery:
1. Focus on the speed to results that matter. Have a specific objective for your initiatives e.g. reducing days sales outstanding (DSO) by certain days, then drill down into specific KPIs and identify inefficiencies.
2. Ensure good optimization/automation prioritization, governance, security, value validations, and an operating model
3. Chose the right partners and tools for your implementation.
As the market expands, we are seeing more choices in terms of tools.
Current Tool Landscape
We have close to 40 vendors in the space right now and they come at it from different directions and objectives. Here are the key categories we have found:
Standalone platforms: E.g. Celonis, Software AG, Skan
Automation Platforms: E.g. UiPath, Automation Anywhere, Nintex
Big Tech: E.g. IBM, Microsoft, SAP
So, how do you select the right tool for your needs?
How to choose your "Best" Tool(s)
You should ideally have criteria and a checklist to choose the "best" tool for your needs. Here are some key pointers to look for.
End-to-end visibility and transparency of process flows
Range of prebuilt/templated process analyses
Easy Conformance/Compliance checking (with a UI)
Ability to identify process activities that can be automated
Can identify the KPI impact of process variations and outcomes
Embedded AI / Intelligence, ML-based root cause analysis
You can find more suggested tool evaluation criteria here.
