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Back-end of Kairos: A Prescriptive Process Monitoring Tool
(Tartu Ülikool, 2023) Qu, Zhaosi; Milani, Fredrik, juhendaja; Shoush, Mahmoud, juhendaja; Kubrak, Kateryna, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
Prescriptive process monitoring is an approach that aims to predict potential failures and provide recommendations to optimize business processes. It seeks to improve efficiency and productivity by aiding enterprises in making informed decisions during process execution. For example, it can be applied to optimize a company’s supply chain management by predicting delays and suggesting actions based on historical data. The primary problem that this thesis address is the absence of a comprehensive tool capable of analyzing data from different sources and offering various types of prescriptive recommendations. Consequently, the objective of this study is to propose and implement a software solution that enables the integration of diverse algorithms and plugins in a seamless manner. The proposed approach includes back-end software that provides APIs to implement prescriptive process monitoring features. Users can upload event logs to the tool and receive various prescriptions for ongoing cases, encompassing predictions of the next activities, scoring the likelihood of adverse outcomes, providing treatment effects, and allocating resources based on treatment gains. Moreover, the modular design enhances adaptability and flexibility across various business domains. To evaluate the effectiveness of the proposed solution, a combination of requirements fulfillment evaluation and performance evaluation is conducted using datasets from the Business Process Intelligence Challenge (BPIC). As a result, this thesis contributes to the field by providing a prescriptive process monitoring tool that can provide multiple types of prescriptive recommendations.
Digital innovation for business process redesign
(Tartu Ülikool, 2022) Nava, Juuli; Milani, Fredrik, juhendaja; Kubrak, Kateryna, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
The focus of this thesis is the adoption of emerging digital technologies in the context of business process management. To better understand the ways in which technology can impact business process redesign, this thesis explores the capabilities of these technolo-gies. This research presents a systematic literature review (SLR) with 26 academic articles (from 2017 to 2021) that describe case studies in which business process redesign is done with the introduction of new technologies. As a result of the SLR, six capabilities of digi-tal technologies were derived and positioned beside 14 identified redesign heuristics. The main contribution of this research is a framework that can support practitioners and re-searchers in establishing how business processes can be redesigned through the capabili-ties of digital technologies.
Visualising Prescriptive Process Monitoring Output
(Tartu Ülikool, 2023) Botchorishvili, Lana; Milani, Fredrik Payman, juhendaja; Nolte, Alexander Udo, juhendaja; Kubrak, Kateryna, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
The emergence of process mining in business process management has given way to developing algorithms that predict future processes based on historical event logs to improve operational efficiency. Further improvements have followed in the form of real-time prescriptive process monitoring tools, which identify volatile process instances and suggest interventions for upcoming activities to prevent risky execution. One of the main challenges of this practice is communicating interventions to end users in a clear and concise manner. This research was conducted to develop a real-time application that visualises available interventions and their impact on a process instance. The tool helps support process analysts in identifying activities that improve a KPI or circumvent a sub-optimal outcome in a process. A resulting artefact is a form of an operational dashboard - Kairos - that visualises prescriptive process monitoring output.