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5 Ways to Harness the Power of Process Mining Digital twins [2024]

The digital twin market is expected to grow to ~36 billion dollars by 2025 at a CAGR of 38%. One major reason behind the growth is that digital twin technology can be simultaneously employed with other software and platforms such as IoT and process mining. By pairing these platforms with a digital twin, leaders make model-driven decisions and run cost-effective simulations in  various sectors like consumer goods, manufacturing, retail, and energy. Although business leaders know these possibilities, the numbers of business leaders who are utilizing digital twins (13%) remain smaller than the ones that are willing to apply (62%). The challenge arise because it is not clear for business leaders how these two technologies are applied together or how they can be paired together to achieve better business outcomes 

In this research, we give 5 different examples where business leaders can pair digital twins and process mining to harness their full power.

How do process mining and digital twins complement one another? 

Process mining is the practice of collecting and analyzing business log and event data in order to obtain an understanding of the company’s processes. For more, feel free to read our guide on process mining.

Digital twins were initially used to create replicas of physical assets like machinery and planes. These digital replicas were used to run simulations and identify opportunities like predictive maintenance. Same technology can be used on business data to create virtual model simulations, also called digital twin of an organization (DTO).

Process mining and digital twins complement one another in process assessment and improvement:

1. Provide better quality data

Process mining can be used to prepare data for a DTO. Process mining (PM) can be the first step for data preparation and cleaning to provide better quality data to digital twin and DTO models since PM pulls the process steps by utilizing the data directly from operational systems. 

2. Predict future outcomes via simulations

A DTO can be used to run predictions and complex simulations which are usually outside of the scope of process mining.

Process mining concentrates on the past data to understand how the entire process has been executed with its challenges, benefits, and cost. Digital twins provide predictions using such historical data by considering certain conditions and desensitizing parameters. When these two fields are combined, they provide more comprehensive business insights.

For example, Credem Bank employed process mining to generate digital twins of their processes for their digital transformation projects.1  The bank simulated their back office (BO) activities for the next 8 months if the bank automates 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%.

3. Have visibility into end-to-end processes

Digital twin models capture different steps in product and manufacturing processes, and visually represent these steps. By combining digital twins with process mining, companies gain a centralized understanding of end-to-end processes and build their strategies upon these insights. 

For example, manufacturing companies can optimize the processes that include interactions between human and robotic workers by delivering improved process visibility, layout, and an overall increase in efficiency and speeds.

4. Identify risks via scenario analysis

Just like process mining can be used by itself in process optimization, it can be complemented with DTO as well. DTO technology, with its scenario analysis capabilities, can identify outliers, evaluate every single scenario to ensure that the optimized process is robust and will perform well under a variety of conditions. As a result, companies that generate several scenarios with DTO models can respond  to market changes in a fast manner and improve end-to-end processes with minimal risk.

One example is Lufthansa CityLine who implemented digital twin of organizations (DTO), an application of DT technology combined with PM to analyze their boarding process. They detected seconds that could be trimmed off to use the time in other aspects of their businesses. With DTO, they increased their punctuality and efficiency. 

Another example is from a global retail bank that faced a challenge while testing video-enabled customer service in-branch because of disparate and dynamic data structures. DTO came over the challenge by providing an integrated business model which illustrates that video technology achieved higher conversion rates for the personal loan processes. 

5. Build efficient processes via automation

A common type of optimization involves automation using automation tools such as RPA or workload automation. As in optimizing resources, process mining and digital twins can be used in parallel to build robust, efficient processes.

Further reading

To dive into digital twin studies or learn more on other capabilities of process mining, check out our in-depth articles:

If you believe your business can benefit from pairing digital twins with process mining, you can start checking vendors from our data-driven lists for process mining and digital twins.

And, if you need guidance, let us help you to find the right vendor:

Find the Right Vendors
Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Hazal Şimşek
Hazal is an industry analyst in AIMultiple. She is experienced in market research, quantitative research and data analytics. She received her master’s degree in Social Sciences from the University of Carlos III of Madrid and her bachelor’s degree in International Relations from Bilkent University.

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