Although 87% of business leaders believe digital is disrupting their industry, only 44% are ready to transform their organization to face such disruption as digital transformation stats indicate.
Process mining can ensure that organizations are prepared for digital disruption by allowing analysts and leaders to:
- Understand their processes,
- Assess digital maturity level,
- Discover automation opportunities,
- Measure the initiative ROI,
- Monitor the project,
- And mitigate the risk.
In this article, we will expand on these six steps to explore how process mining can enable digital transformation.
1. Understand as-is processes
Digital transformation and RPA stats show that 70% of digital transformation and 63% of RPA implementation initiatives fail to meet the time, cost and benefit expectations. One major reason for such failures is the choice of process. Companies might lack knowledge of their operations and consequently choose a process that
- Has insignificant impact
- Contain errors or designed mistakenly
- Changes frequently
- Complex with various sub-processes
- Involve high-level cognitive tasks.
Process mining discovers processes and visualizes the entire workflow with all steps, activities and tasks included by employing algorithms. By diving into the workflow, users can identify unnecessary steps, errors, mistaken designs and actions that could be more beneficial for the customers.
Execution of complex processes might vary according to the organization’s cases, employees, teams or region. Such differences in practices can be identified with the help of process mining and task mining.
For instance, multi-level process mining shows the impact of one change in a sub-process over the entire process flow, disentangling complex processes. Task mining captures the user interactions to help analysts detect mistakenly executed cognitive tasks and facilitate algorithms to replicate some of these tasks for automation.
2. Assess digital maturity level
Every business must assess its digital maturity level before they start its transformation journey since the level of maturity determines the efforts and benefits the firm can gain from the transformation.
To measure digital maturity level, analysts investigate the former transformation projects, interview with teams to see if they are ready to change the processes and measure the impact of the projects and strategies. However, such detailed research can prolong the transformation project, reducing the competitive advantage of the firm.
Process mining can reduce the time and efforts dedicated to the assessment phase. With process mining, analysts can skip demanding interviews and long analysis to assess the maturity level while generating data-driven decisions.
Process mining allows users to see their digital maturity level and measure the impact by setting certain KPIs. Also, the analysts can run conformance checks against pre-defined KPIs to understand the rank the company achieved after the transformation project. By understanding how digitized their processes are, business leaders can invest in accurate processes and technologies.
3. Discover automation opportunities
The main goal of digital transformation is to reduce manual work to ensure the smooth and efficient execution of processes through digital technologies. To do that, businesses must look for areas to automate. However, discovering places to automate and employ RPA can take time and effort.
For instance, businesses that adopted automation mentioned that they achieved automation up to 80%. However, while the automation level increases, they experience diminishing returns. Finding and automating the remaining 20% of a process requires more effort and budget.
Process mining can facilitate the discovery of automation opportunities by seamlessly pinpointing manual tasks and activities that can be automated. Indeed, 78% of business leaders and decision-makers consider process mining as a key that facilitates automation.
With process mining, business leaders and analysts can measure the level of automation their organization achieved, areas that are potential candidates and the benefits business can leverage by automating specific activities and steps in the operational workflow.
For instance, Credem Bank from Italy leveraged process mining to enable their digital transformation. The bank simulated their back office (BO) activities for the next 8 months if the bank automates of 90% of BO processes by using RPA. The bank could implement the project since expected return on investment was verified. After the automation, the bank managed to save BO costs up to 85%.
4. Measure expected ROI
One of the major challenges for digital transformation is the high expenses. For instance, Axa insurance’s digital transformation project costs reached up to $ 95 million in 2 years. 1 Therefore, companies are recommended to calculate their ROI before implementing any solution.
Some process mining tools can generate a digital twin of an organization (DTO) to measure the ROI before implementing any change in the project. By leveraging such software, process analysts can experiment with any measures they want to adopt. They can deploy RPA and set different levels of automation to assess the scenario that returns the highest ROI and most plausible.
5. Develop data-driven strategy
A common myth about digital transformation is that all organizations should follow the same formula. However, every business must develop its unique digital transformation strategy and project according to its necessities, environment and business goals. However, such efforts can be demanding for analysts who still need to clarify the relevant factors for the strategy.
One way to develop such transformation strategies is to leverage business data. Process mining can extract business process data, and task mining can record employee activities to understand the process that the business wants to transform.
Moreover, leading process mining tools employ machine learning to offer low-code platforms with drag-and-drop features. As the digital transformation stats have shown, almost half of the businesses that implemented digital transformation acknowledge that they need more relevant skills in data science and cybersecurity. By deploying process mining, these business leaders and analysts can transform their processes with less data-science investment.
6. Monitor transformation projects
Only 16% of employees believe digital transformation initiatives could improve performance. The reason behind such a low success rate is related to how transformation projects are carried out.
These projects might include inefficiencies or process gaps, leading to longer and unsatisfying results. 37% of business leaders complained that they experienced such problems in their digital transformation initiative. Thus, such inefficiencies are not easy to identify if the analysts are not closely watching the entire project.
Process mining can be useful for monitoring the project continuously and evaluating the results by displaying the level of transformation for the given process. This way, analysts can pinpoint current mistakes and predict inefficiencies to correct them in time.
With process mining, business leaders and analysts can experience a smooth digital transformation initiative and obtain the results they intend to grasp from the project.
Explore how process mining can enable RPA and intelligent automation by:
- 3 Steps to Implement RPA with Robotic Process Mining
- 4-Step Guide to Facilitate RPA Deployment with Process Mining
- 3 Ways Intelligent Process Mining Enables Automation
If you know enough of process mining but are not familiar with vendors, check out our data-driven comprehensive process mining vendor comparison list.
Check out comprehensive and constantly updated list of process mining case studies to explore process mining digital transformation real-life examples.
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