CIO OPINION to achieve performance and compliance targets such as “ Which changes can I apply to meet my loan applications time-to-yes SLA ?”, or “ What changes can I implement to deliver a 20 % uplift in cycle time without compromising controls ?”. To recommend changes that address these questions , the GenAI generates dozens of possible configurations and tests each of them thorough simulation , considering the operational constraints and business goals of the organization .
GenAI accelerates the identification of optimal configurations , saving time and resources , and reducing the time-to-market for new initiatives . However , to avoid hallucination issues GenAI techniques suffer from , GenAI should be used only for generating new simulation scenarios to be tested . The actual testing should be performed by simulation engines to ensure statistical reliability .
From Tactical Analysis to Operational Support
The previously discussed applications focus on tactical analysis for mid-to-long term improvement . GenAI can also be used to recommend on-the-fly interventions and understand their impact on ongoing processes . This enables answering questions like " Today , which loan applications are at risk of breaching our time-toyes SLA and what can I do to avoid it ?" These on-the-fly recommendations from GenAI should be tested , to rule out hallucination . This can be done using causal machine learning techniques , which are effective at determining which treatments have the highest causal effect on a desired process outcome ( like lifting cycle time by 20 %) but do require a set of possible treatments to be provided first . That ’ s precisely where GenAI helps .
Conclusion would be the impact on our time-to-yes Service Level Agreement ( SLA ) if we received 20 % more loan applications a day ?”. The GenAI builds and tests the simulation scenarios required to answer these questions and presents the results in an easy-toconsume form such as a dashboard .
3 . Process Optimization
The first two applications make process mining more accessible and accelerate time-to-value , while the third focuses on prescriptive optimization . Here , the objective is to prescribe the most effective changes
The integration of GenAI into process mining offers significant opportunities to accelerate initiatives related to operational excellence , Digital Transformation and compliance monitoring , especially at scale . GenAI can dramatically shorten time-to-value , particularly for non-technical users . The real game changer is GenAI ’ s ability to explain findings and patterns that are not easily seen and to generate interventions , both at tactical and operational levels , that are not easily thought of . However , GenAI is still in its infancy and requires guardrails to avoid pitfalls .
As GenAI continues to evolve , it will likely provide further applications in process mining . Staying on top of these developments will enable organizations to unlock new opportunities , remain agile , gain competitive advantage and fuel growth . p
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