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Enable Process Transformation in 6 Easy Steps in 2024

Written by
Hazal Şimşek
Hazal Şimşek
Hazal Şimşek
Hazal is an industry analyst at AIMultiple, focusing on process mining and IT automation.

She has experience as a quantitative market researcher and data analyst in the fintech industry.

Hazal received her master's degree from the University of Carlos III of Madrid and her bachelor's degree from Bilkent University.
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Enable Process Transformation in 6 Easy Steps in 2024Enable Process Transformation in 6 Easy Steps in 2024

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Process transformation can increase customer satisfaction by up to 30% and maximize profit by up to 50%. Recognizing its major impact,

Although the investment in business process transformation increases, less than 30% of such projects could be successful.1 The low success has been associated with the complexity of the implementation by 76% of executives.

Therefore, we will define business process transformation, explain why it matters, the challenges observed and how to tackle them to simplify transformation implementation in 6 steps.  

What is business process transformation?

Process transformation is a type of business transformation and a branch of business process management (BPM), referring to a radical change in business processes. Such changes include implementing new technology, integrating core business systems or simply updating the process to reduce costs and improve operational excellence. 

Businesses can transform their processes to:

  • Adopt a new business model
  • Reduce cost
  • Improve customer experience
  • Implement new technologies
  • Redesign existing processes
  • Embrace sustainability goals
  • Mitigate risk
  • Enhance product or service quality 

Process transformation vs. Digital transformation

Digital transformation is a way to transform business processes, a subset of broad business process transformation projects. However, some academics and vendors use these concepts interchangeably since almost all transformation projects focus on digitizing processes.  

Process transformation vs. business process improvement

Business process improvement can be seen as a part of the business transformation. It has a limited focus on identifying areas to implement changes, such as 

  • Standardizing an existing process, 
  • Changing business process model,
  • Improving their key performance indicators like cost reduction. 

On the other hand, businesses that seek organizational transformation might need a large scale change, as in transformation initiatives to:

  • Produce better business outcomes,
  • Accelerate business growth,
  • Create new processes,
  • Deliver more value for customers,
  • And, improve digital experience. 

Why is process transformation important?

Figure 1 below shows the gradual increase in trends for process transformation over the last 10 years. The reason behind the growing interest is related to benefits business process transformation provides to business processes, such as:

  • Enduring relevant for the business,
  • Meeting business goals and demands,
  • Remaining up-to-date with the latest technology, 
  • Having a good performance.

By doing so, transformation statistics indicate that process transformation can boost business growth by

  • Improving operational efficiency by 40%, 
  • Providing agility in the market by 36%, 
  • Increasing revenue by 56%, 
  • Reducing additional cost by up to 20%. 

What are the process transformation challenges?

Some of the major challenges leading to failures of process transformation involves:

  • Lack of objectives: Process transformation projects fail because organizations might not set a clear goal or identify the process’s objectives.  
  • Lack of continuous improvement:  7% of employees stated that transformation projects optimized their processes but they could not sustain these improvements. One way to sustain these improvements is to continuously monitor and measure the transformation initiative in order to ensure performance improvement and compliance. The lack of such system can lead to high fines, costly mistakes and errors, and failure of the entire transformation project.
  • Lack of model alignment: Business leaders and analysts might understand their business processes through the best practices, legal procedures, business strategy and work instructions. However, the operational processes are often quite different from these ideal models in real life. It can be challenging to identify how to align the ideal and actual processes.
  • Lack of the right tool: Choosing the right tool is difficult for business process transformation given the availability of thousands of competing tools. Selected tool must be
    • capable of pulling data from various systems effectively
    • easy to use
    • cost effective
  • Lack of engagement and culture: A major challenge for organizational transformation is the perception of employees and culture. For instance, in transformation surveys, employees stated that they did not favor such change by 26% and perceived the project as costly by 28%. 

6 Steps to successful business process transformation with process mining 

Phased implementation is the practice of dividing the entire project into smaller phases to implement a core transformation. Figure 2 represents how Deloitte approaches to process transformation in phased manner. Deloitte suggests leveraging process mining, intelligent automation, process orchestration to capture, envision, execute and sustain processes.

In this section, we elaborate on this approach and list 6 business process transformation steps with process mining analysts and business executives must follow for a successful business transformation:

Successful business process transformation in 4 steps with process mining and intelligent automation.
Figure 2: 4 steps to process transformation, Source: Deloitte

1. Understand end-to-end process

The first step is to have a full picture of the current process both in real-life and in models, including work instructions, policies and guidelines. By doing so, analysts can compare them, detect areas that require alignment. 

Process mining and task mining can facilitate this first step in the business process transformation  project by capturing existing processes and user interactions. 

Process mining vendors offer automated process discovery and visualization to analyze, model and map the extracted data. These models include resources, people involved and activities, which are crucial information for transformation initiatives.  

Analysts can leverage these process maps to expand their knowledge on their operations, and identify areas, such as manual processes or routine tasks requiring improvement and automation.  

2. Define transformation goals

Many organizations mention the lack of objectives as a major challenge to a successful business process transformation. To overcome such an issue, analysts must define their goals by asking specific questions like: 

  • If the business aims to incorporate new technologies,
  • If the existing systems will be upgraded or replaced, 
  • If the business will embrace a new organizational structure, 
  • If there is any reason to create a new process. 

Some of these questions are easy to respond to, while the second and fourth questions may be slightly difficult to figure out without the help of any process intelligence tool

Process mining can help analysts locate areas in the process workflow that might require any change. Analysts can also leverage customized dashboards provided by process mining to measure process performance KPIs and metrics, such as delivery time, compliance level or cost. 

Based on these insights, analysts can set their exact goal and objectives for their business process transformation initiative.  

3. Focus on customer-centric processes 

Companies with annual earnings of  $1 billion are estimated to gain an additional  $700 million as they invest in improving customer experience. This is why business process transformation teams must focus on transforming customer-centric processes to deliver the best customer experience possible.

Process mining can streamline the business process transformation of customer-centric processes because it can map customer journeys and evaluate feedback collected from customers

Moreover, the software can be integrated into CRM and SAP, to gather, analyze and map any operation that deals with customers in the first place. 

4. Connect the strategy with model

As stated above, business transformation teams struggle because their process models and real life processes are not aligned. Therefore, analysts must create an ideal model reflecting transformation,including all tasks, activities and parties involved in the workflow. 

Then, business process transformation teams must connect and compare the operating model against the designed one. This way they can decide whether they must develop a new business strategy and new business goals or implement change in the current processes. 

Many process mining tools facilitate doing such comparisons by running conformance checks. Analysts can either create these models on process mining or upload it to process mining from another tool to assess the level of compliance between two. 

Estimating the compliance between two enables analysts to understand where they are and how much they need to transform and eventually develop their business process transformation strategy.   

5. Measure the ROI and performance 

Organization culture and resistance from employees represent a great obstacle for transformation in any industry. One way to overcome such backlash is to provide data-driven insights to the team to make them understand how essential the change is and increase their engagement in this. 

However, it may not be so straightforward to find a way to do that. Analysts must collect data to measure the expected ROI of the change first and then develop baseline metrics for tracking the impact of the change. Yet, 29% of businesses complain that it is hard to find data to prove ROI. 

Process mining tackles this problem seamlessly since it collects data from any IT systems of your organization and generates useful metrics measuring the performance. These could be beneficial to measure the impact of the transformation at each step. 

Moreover, some process mining vendors allow users to generate digital twins of an organization, a virtual model of the business processes and services. These models contain all these KPIs along with the process analysis, goals and models. DTOs can help measure the expected ROI before the change is implemented and run different transformation simulations to identify the best scenario.  

6. Monitor the transformation project

Final step in a well-designed process transformation methodology is to closely monitor the changes implemented and estimate the success in business change. Such continuous monitoring can allow analysts to build an optimization cycle where they predict potential issues in the project or realize an error to intervene in time. 

Analysts can utilize process mining for continuous monitoring because the software offers features like automated root-cause analysis and real-time data extraction. As a result, analysts do not need to manually update process maps and re-analyze the new processes after

This way, business transformation teams can pinpoint and improve any inefficiencies in the strategy or business models. Specifically, analysts can easily discover the triggering factors behind these issues 

Further reading

Explore how process mining facilitates digital transformation and automation:

If you believe your business can benefit from process mining tools, compare the tools with our data-driven and comprehensive vendor list.

Leverage process management tools and technologies to transform your processes, by checking out our objective and constantly updated lists:

We have prepared this checklist in Google sheets with recommended weights per criteria so you can have a transparent methodology to assess different vendors. Feel free to get it on your business email:

Get Process Mining Vendor Selection Guide

And, if you still have questions, let us help you:

Find the Right Vendors
Hazal Şimşek
Hazal is an industry analyst at AIMultiple, focusing on process mining and IT automation. She has experience as a quantitative market researcher and data analyst in the fintech industry. Hazal received her master's degree from the University of Carlos III of Madrid and her bachelor's degree from Bilkent University.

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