"Relatively few organisations are process driven - that will change radically." 
Truly understanding process performance is a starting point for most organisations’ digital transformation programmes. Process discovery to understand the current state can be costly, time consuming and open to human error. It is labour intensive and does not provide real time results. However, it is a critical step in identifying and driving transformation within your organisation, without this level of analysis digital transformation programmes cannot deliver the expected outcomes, or sustained benefits.
"Only 16 percent of respondents say their organisations' digital transformations have successfully improved performance and also equipped them to sustain changes in the long term." 
Process mining offers a new approach to process analysis and transformation by enabling rapid data collection and offering real time insights. It allows organisations to rapidly analyse their data through a process-oriented lens and provide a platform for predictive decision-making. It uses AI and machine learning to extract existing data from an organisation’s IT system and visually reconstruct how processes actually perform.
"Process mining aims to discover, monitor and improve real processes by extracting knowledge from event logs readily available in today's information systems. Process mining includes process discovery, conformance checking, social network/organisational mining, automated construction of simulation models, model extension, model repair, case protection and history-based recommendations." 
Process mining supports all processes along the value chain and works independently of type/number of supporting IT systems. It supports the identification of savings potential and its realisation can be tracked with the process mining tool.
We consider the prevalence and importance of process mining to be huge and Gartner agrees. In Gartner’s Market Guide for Process Mining 2018 it was predicted that the process mining market is to grow exponentially over the next five years.
"The global process analytics market size is expected to grow from USD 185.3 million in 2018 to USD 1,421.7 million by 2023". 
Process mining retrieves existing data from event logs and transforms data into an actionable insight. An event log is the system record of a discrete activity that was executed during the process. Multiple activities are linked together in a process instance or case and ordered by their timestamp to provide a sequence.
The three data requirements for process mining are Case ID, Activity and Timestamp. They can can come from any data source.
|A case identifier, also called process instance, is necessary to distinguish different executions of the same process. What precisely the case ID is, depends on the domain of the process. For example, in a call centre, the case ID would be a service request number. In a hospital, this would be the patient ID.
|There should be names for different process steps or status changes that were performed in the process.
|At least one timestamp is needed to bring the events in the right order. Of course you also need timestamps to identify delays between activities and identify bottlenecks in your process.
By implementing a process mining approach, it enables organisations to conduct rapid process data analysis, uncover hidden inefficiencies, identify optimal process sequences, assess variants and make processes measurable. The first step when undertaking digital transformation is to break “silo mentality" and ensure implementation of digitisation approaches in end-to-end processes.
With the combination of software expertise and industry-specific know-how, Celonis and BearingPoint are uniquely positioned to help organisations deliver value from their digital transformation.
Celonis is the New York and Munich based leader in business transformation software, turning process insights into action with the process mining technology it pioneered. Companies around the world including Siemens, GM, 3M, Airbus and Vodafone rely on Celonis technology to guide action and drive change to business processes, resulting in millions of dollars saved and an improved experience for their customers.
BearingPoint supports its clients with the strategic and operation execution through integration operational improvement programmes combining customer-centricity, business process design, robotic process automation and continuous improvement to unlock value and reduce costs.
BearingPoint and Celonis have partnered to help organisations uncover hidden inefficiencies and identify opportunities for improvement. BearingPoint helped transform the Procure to Pay and Accounts Payable process for a German consumer goods company. The 150 strong function suffered from low levels of automation, inconsistent work practices and a lack of process standardisation.
BearingPoint carried out the data analysis, process validation and technical integration to implement Celonis process mining tool. The project provided higher transparency through “real-time” process monitoring providing a greater understanding of process cost and quicker identification of inefficiencies and elimination. A huge benefit provided by Celonis is the ability to quantify and track potential savings and corresponding implementation measures, in particular process automation initiatives. This allows organisations to better manage their transformation programmes and ensure lower process costs, faster turnaround times, better transparency and compliance.
 Forrester.com. (2019). The Process-Driven Business Of 2020. [online]: https://www.forrester.com/report/The+ProcessDriven+Business+Of+2020/-/E-RES71621 [Accessed 13 Nov. 2019].
 McKinsey & Company. (2019). Unlocking success in digital transformations. [online]: https://www.mckinsey.com/business-functions/organization/our-insights/unlocking-success-in-digital-transformations [Accessed 13 Nov. 2019].
 Icpmconference.org. (2019). IEEE Task Force on Process Mining – Process Mining Conference 2019. [online]: https://icpmconference.org/2019/ieee-task-force-on-process-mining/ [Accessed 13 Nov. 2019].
 ltd, R. (2019). Process Analytics Market by Process Mining Type (Process Discovery, Process Conformance & Process Enhancement), Deployment Type, Organization Size, Application (Business Process, It Process, & Customer Interaction) & Region - Global Forecast to 2023. [online]: https://www.researchandmarkets.com/reports/4576970/process-analytics-market-by-process-mining-type [Accessed 13 Nov. 2019].