As correctly stated by Dr William Edward Deming; “In God we trust, everybody else must bring Data”, these words stand true to the core in today’s world where we find ourselves surrounded by petabytes and Zettabytes of Data. It is needless to emphasise that Data is the new Oil, as Data has shown us time on time that, without it, businesses cannot run now. We need to embrace not just the importance but sheer need of Data these days.
Every business runs the onset of processes designed and defined to make everything function smoothly, which is achieved through – Business Processes Management. Each Business Process has three main pillars – Business Steps, Goals and Stakeholders, where series of Steps are performed by certain Stakeholders to achieve a concrete goal. And, as we move into the future where the entire businesses are driven by Data Value Chain which supports the Decision Systems, we cannot ignore the usefulness of Data Science combined with Business Process Management. And this new stream of data science is called Process Mining.
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As quoted by Celonis, a world-leading Process Mining Platform provider, that; “Process mining is an analytical discipline for discovering, monitoring, and improving processes as they actually are (not as you think they might be), by extracting knowledge from event logs readily available in today’s information systems.
Process mining offers objective, fact-based insights, derived from actual data, that help you audit, analyze, and improve your existing business processes by answering both compliance-related and performance-related questions.”
Below we talk about Why do we need process mining and how it helps Businesses in decreasing costs, increasing profits and above all, improving Customer + Employee satisfaction.
- Bring in Transparency – the business process mining tools and platforms bring in the capability to absorb tons of data elements and provide it in a consumable format at the nth level of details enable business owners to see all the steps and uncover inefficiencies along with identification of venues of improvement
- Reduce multi-Hops steps – Machine Learning powered root cause analysis enable identification of un-needed steps thus reducing blocks causing slowdowns and increasing efficiencies through the processes
- Create a shift-left ecosystem – enable the stakeholders to identify problems earlier and being able to solve the problems at the initial stages reduce efforts and increase employee + customer satisfaction.
- Reduce cost – by uncovering hidden bottlenecks, identifying in-efficiencies and discovering venues of automation result in increased bottom line profits and reduces costs.
Now, let’s cover the four major techniques which make process mining effective and make businesses achieve their goals:
- Data Extraction and Management – To be able to get a 360-degree view of the processes you need to get complete data extracted. The most important part is that there should be a standard quality of data with a proper definition of data types for seamless information integration.
- Data Preparation – Once the required data is identified, extracted and standardized, you need to prepare the data for consumption by Business Users, Data Scientists and Decision Makers to be able to consume it through properly defined KPIs and Variables.
- The Visual analysis – The data points are then used to visually interpret the process flows, identify multiple steps, find out bottlenecks and uncover the overlaps or repeated steps that slow the processes. This is very key to understand the as-is processes against the benchmarks.
- Optimization of Processes – Once you have the detailed internal and external dependency view along with the bottlenecks, these data points will provide the foundation for deriving the optimization measures and then prioritize the areas to improve the processes across.
Below we talk about some of the broader use cases covering Process Automation, Risk management and Operational Process Improvements which will enable Businesses to transform Digitally along with helping Businesses become more stable, scalable and future-ready:
- Business Process Improvements – using the process mining lifecycle where continuous monitoring and optimization of the process takes place in iterative fashion results in the identification of avenues of improvement like which steps can be simplified, removed or merged with another process.
- Auditing and Compliance – keeping track of the data logs help in maintaining a proper set of records which can provide insights into the audit trails and lineage along with the implementation of best practices and regulations.
- IT operations optimization – Using the insights of process mining the optimal resource allocations within the IT operations can be identified and a proper capability sharing model can be achieved by leveraging Advanced Analytics and Insights.
- Process Automation – The results generated by Process Mining implementations can also shed insights into the gaps resulting from poor data governance and data quality in place and will help remove manual processes causing such issues thus setting the platform for end to end Automation implementation.
- Digital Transformation – All of the above points when combined together will set the platform for the complete digital transformation of the Businesses by providing a strong data foundation with a flexible yet effective lifecycle to manage the digitization of processes.
As by now you know about Process Mining, its Use Cases and the Value it brings to the table from both, Business and technology perspective. Now let’s focus on one of the most important aspects of making Process Mining more effective and efficient through Process Mining as a Service or PMaaS.
What is PMaaS? – The idea behind enabling Process Mining in the form of a Service offers a one-stop-shop market place that provides services like, Process Analysis, Identifying Gaps, Building and Implementing Processes and Monitoring services. All this can be achieved with low initial expenditure to the customer, zero to minimum Licensing cost and no Capital Expenditure.
How does it work? – PMaaS provides access to any Process Mining tool of client’s choice and enables service wrapping around it covering Environment Provisioning on Cloud, User Access set up, Data Model Build-Up, Analysis of Business Process Areas, Generates Gap analysis and Recommendation report along with Run & Maintenance service. With these services, it removed the hurdles of infrastructure set up, user training and reduce the time to market for the clients.
What value does it bring? – PMaaS enables a lot of flexibility and can operate in various mode of operations like Distributed Model, Hub & Spoke Model or Centralized COE Model. This helps in Cost Reduction, Process Efficiency Increase and Removal in Redundancy of Processes thus increasing both the top-line and Bottom-line growth of the client.
So in a nutshell, having data alone is not the solution to the problem but having proper tools and platforms to churn and present the data in the right format is very much needed to bring out value our of data. And the new stream of Data Science in this area that is bringing this clarity is called Process Mining.
About the Author(s):
Rudraksh (Rudy) Bhawalkar is an Analytics practitioner by core and currently works as Senior Principal within Accenture Applied Intelligence as part of the Solution Design team. He is also leading the Responsible AI capability in Austria, Switzerland, Germany and Russia across all industries. He has more than 14+ years of experience in the field of Data, Analytics and Artificial Intelligence covering Delivery, Sales, Pre-Sales and Solution Architecture. He is also a publisher of more than 36 articles on the topic of Artificial Intelligence, Analytics, IOT, Big Data, Digital Transformation along with being a Public Speaker at various CXO conferences in Europe, Americas, Africas and India.
Jack Ramsay is the head of Accenture Applied Intelligence and Data & AI business groups for Austria, Switzerland, Germany and Russia. He has been active in the world of Technology, Data, Analytics and AI for around ~35 years and represents Accenture across all Industry verticals in all continents. Most recently he supervised the growth of the Accenture Industry X unit as the Global Delivery Lead and previous to that he leads Accenture Digital as the Global Delivery Head where he foresaw the juncture of Business and Data in 720-degree mode to drive Data lead growth.