Fabrice Baranski has been CEO of Logpickr since 2017. Co-founder of this process mining software company, he draws on five years of experience in R & D within the Orange group. In terms of process mining, Logpickr is the only French player. Their innovation lies in the implementation of AI in this software. Their goal is to become a reference player in process mining in France but also internationally. Logpickr is listed by Gartner as a Representative Vendor in the process mining field. The software is available in English and French versions.
Fabrice Baranski: Logpickr is a young company created in 2017. It is a pioneer in process mining in France. We create and edit software solutions in process mining that innovate in relation to the market. Our software combines process mining with Artificial Intelligence: this is what differentiates us. We rely on more than 7 years of R & D (5 years in the Orange group). Logpickr is already listed as a Representative Vendor in Process Mining field by Gartner.
F. Baranski: By making an analogy with medicine: companies pilot their activities, operations, in the manner of what a doctor does by controlling the temperature, with a thermometer. Process mining then plays the role of scanner in the sense that it will allow to understand in detail how operations and processes are actually performed and not supposedly. The process mining will go into detail to understand precisely the processes. This is a big gap compared to what already exists in the process analysis, where audits are done manually. The advantage of this technology is that the audit is done very quickly, simply by analysing the existing data in the information systems (IS) of companies.
F. Baranski: We have built a whole series of interfaces to recover the data where it is, as it is. Research at Orange was based on an evolving IS with existing applications and new applications. With third-party and internal tools, we are able to recover the data in ERP, in databases, in files, to retrieve information that we need to understand the processes. Regarding this we need "event log" or data on processes in the form of computer traces. I take an example: a bank and its bank credits. The computer traces are found in different applications. This information should contain three characteristics: What activity was done? When? For which folder? With these three pieces of information that can come from several data sources, the software will be able to identify the processes. The difference from Logpickr is that the software will add all the business data related to the process. These data are the amount of the title credit, which intervened, which customer, etc. There is no limit to the data that can be processed. This enriches the analysis.
F. Baranski: As part of continuous improvement, process improvement or lean management. There are several application frameworks: the first, when one wishes to optimize the processes of a society. There is a saying that we can improve only what we know well. To know each other well, it requires an automatic audit using our software. The great interest is that our audit is done very quickly and that it is very easy to identify where the needs for improvement are. The second category is the automation of processes or RPA. These dynamics require an audit beforehand to identify how to better automate, and how to optimize this automation. The third interest is the customer experience. From our point of view, the customer experience is a process like any other. With Logpickr, we are able to understand the customer experience to get a real view of the situation in real time. The last point is anticipation and prediction, to anticipate the failures on the processes. Thanks to AI, Logpickr can create prediction models and alert in case of failure such as non-compliance with deadlines on current files or other criteria that can be defined.
F. Baranski: Process mining is a way of having new variables, new data, which will be used to feed prediction models. As Logpickr has built an innovative process mining, we achieve more powerful results in terms of prediction. We will use this material to build predictive models and explain the root causes of process variation and failure. Our niche is to combine our innovative process mining with AI, around prediction features but also features to facilitate analysis. We want to make sure that everyone can become a process miner. Software and AI are at the service of human to facilitate analysis.
F. Baranski: What works particularly well is what is called in our field the "process discovery": the automatic discovery of what is actually happening in the field. In this way it will be possible to detect more or less effective variants, the way you run your business. With our innovative process mining we have the ability to reflect a reality that is much closer to the field. We also bring innovation through new models of prediction on the field, which compared to the benchmark are far superior to other models of prediction, even in the academic world.
F. Baranski: We work a lot with academic personalities of the domain. We are always looking for ease of use and automatic optimization recommendations. The blocking points that may exist in the process are automatically corrected by AI, thus we accelerate process automation and optimization.
F. Baranski: The industrial company using process mining will see and permanently identify what is working well and less well. Thus, to gain precious time in the analysis of the problems, or in the optimization of the use of its resources compared to its objectives, the customer satisfaction, or the legality of the product for example. Process mining, in relation to data mining, looks at behavior: how a process has been developed in order to achieve a service. We are in a constant improvement of the performance because the analysis is permanently available. We try to reach the optimum of the industrial performance.
F. Baranski: There are two aspects. AI has brought interesting innovations in the process intelligence to facilitate its use. The other point is that Logpickr revolutionizes process mining with a new way of seeing it especially on areas that are not well treated at present, such as in complex processes. The complex processes inherent in big companies are not well treated with the current tools. Logpickr combined with AI gives increased performance. AI will bring benefits in ease of use, ease of analysis so that the human really focuses on its innovation, its ability to have new ideas, its organization, its processes, its management customers and more, to understand what is more effective.
I still do not believe in an AI capable of proposing changes of organization. From the outset at Orange we had to deal with complex cases or very bulky ones. It was noticed that it did not work well with the available tools and other current OpenSource tools. AI enriches us through the invention of new ways to achieve better results.
F. Baranski: We have an atypical profile in the AI landscape. We are the only process mining company in France. We invent new ways to use AI in the fact that we introduce the results of process mining in AI. Existing algorithms are used in another way with strong innovation at this level. We look at what is done in other areas to see if we can apply it in the case of Logpickr, and how that will bring gains.
F. Baranski: Process Mining makes it possible to increase efficiency and productivity, where current solutions (lean management, six sigma, process automation) reach their limits. Applying in a systemic and recurring way, you gain in transparency on your organization, but also in operational quality and therefore in customer satisfaction. It is a tool that has no limits as to its scope of application and is essential and unavoidable to manage and optimize all the processes and operations of your company.