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How does Process Mining leverage data?

Cover Livejouney article Process Mining et data

Data: the "black gold" of the century

Google, Facebook and Tencent have recently joined the top 10 global market capitalizations. They all have one thing in common: their business model is essentially based on data!

Data has been described as the “black gold” of the 21st century: it is indeed difficult for companies today to do without this digital “fuel” which is a real growth lever and which has made the fortune of some. Data is nowadays of a great variety, easily accessible and sometimes in real time.

Livejourney article Process Mining et data



Indeed, the evolution of the volume of digital data available is exponential. As shown in the diagram , the growth has been more than 3% in only 10 years! – To better imagine the data in this graph, let’s compare the storage capacity of a smartphone in general between 30 GB and 512 GB to the data generated by connected objects in 2025, the zettabyte corresponding to 1,000 billion GB.

While a smartphone is about 64GB, IoT data will represent 79 Zb in 2025, i.e. 79,000 billion GB (IDC market research).

The challenge for companies is no longer to collect data but to be able to make the most of it, and this is not always easy. A Forrester study from 2021 shows that one out of two companies would be unable to exploit even their own customer data from the CRM. However, and still according to the same study, 8 out of 10 companies declare that they give priority to data-based information to make their decisions. The paradox is obvious: the decision is made difficult or impossible because of the data!

Forbes in a December 2021 article, identifies multiple trends to manage to leverage this data in 2022: two of them are automation and real time.

Process Mining and data

These two key factors of success in data exploitation are omnipresent in Process Mining. Process Mining is a technology that recovers logs from information systems and company applications. It allows to identify and map in real time all the activity and processes of companies. The restitution is visual and dynamic, and gives a precise vision of how the processes are operated on the field.

This allows you to observe inefficiencies, redundancies but also points of optimization and automation at each stage of your organization. Machine Learning and AI complement Process Mining to automate the management and analysis of all collected data.

Let’s take the example of an e-merchant’s supply chain. Thanks to Process Mining, data logs will give a clear vision of what is happening in real time on the ground: from procurement to delivery, including invoicing and preparation of packages. This shows the global performance of the process, to make comparisons according to geographies and/or suppliers, to see where the bottlenecks are but it also allows to know and analyze the path of a particular package.

Another application of Process Mining is the detection of non-compliance to avoid deviations in critical processes. It is an application particularly appreciated in Cybersecurity.

Cybersecurity is defined as a state for an information system that allows it to resist external attacks that could compromise the veracity, availability and confidentiality of the data present in these systems. It is essential and strategic for the company to secure the data and to set up a real time monitoring of the processes that will allow to identify and correct any process deviation.

Process Mining is a technology that relies on data that is increasingly rich and already present in the systems and applications of companies.

It is relevant to drive a good number of business processes and allows to take serenely the right decisions. Thanks to Process Mining, the data is accurate, well-structured and secure.