Dinesh Das is the Data Science manager in Microsoft’s Core Services Engineering and Operations organization. He sees process mining as a silver bullet to achieve this and he shared his learnings and experiences based on the proof of concept on the global trade process.
The third speaker at Process Mining Camp 2018 was Dinesh Das from Microsoft. Dinesh Das is the Data Science manager in Microsoft’s Core Services Engineering and Operations organization.
Machine learning and cognitive solutions give opportunities to reimagine digital processes every day. This goes beyond translating the process mining insights into improvements and into controlling the processes in real-time and being able to act on this with advanced analytics on future scenarios.
Dinesh sees process mining as a silver bullet to achieve this and he shared his learnings and experiences based on the proof of concept on the global trade process. This process from order to delivery is a collaboration between Microsoft and the distribution partners in the supply chain. Data of each transaction was captured and process mining was applied to understand the process and capture the business rules (for example setting the benchmark for the service level agreement). These business rules can then be operationalized as continuous measure fulfillment and create triggers to act using machine learning and AI.
Using the process mining insight, the main variants are translated into Visio process maps for monitoring. The tracking of the performance of this process happens in real-time to see when cases become too late. The next step is to predict in what situations cases are too late and to find alternative routes.
As an example, Dinesh showed how machine learning could be used in this scenario. A TradeChatBot was developed based on machine learning to answer questions about the process. Dinesh showed a demo of the bot that was able to answer questions about the process by chat interactions. For example: “Which cases need to be handled today or require special care as they are expected to be too late?”. In addition to the insights from the monitoring business rules, the bot was also able to answer questions about the expected sequences of particular cases. In order for the bot to answer these questions, the result of the process mining analysis was used as a basis for machine learning.
Fran Batchelor is a Nursing Informatics Specialist who supports the surgical services at three of UW Health’s hospitals. She used process mining to analyze the flow of urgent and emergent surgical cases added to the schedule.
Niyi started with process mining on a cold winter morning in January 2017, when he received an email from a colleague telling him about process mining. In his talk, he shared his process mining journey and the five lessons they have learned so far.
Wim is a program manager responsible for improving and controlling the financial function at the City of Amsterdam. He shared the five-step approach they used for introducing process mining.
As a data analyst at the internal audit department of Euroclear, Olga helped Daniel, an IT Manager, to make his life at the end of the year a bit easier by using process mining to identify key risks.
As a Sunday afternoon project, Marc collected data from Jira, a project management software for (agile) software development, to see how process mining could be applied to help the teams learn from each other.
After tackling the inevitable complexity of any healthcare process through a combination of simplification strategies, the team at HULA were able to reveal bottlenecks that, once removed, can lead to a faster cancer diagnosis.
The final speaker at Process Mining Camp 2018 was Wil van der Aalst, the founding father of process mining. In his closing keynote, Wil talked about the updated skill set that process and data scientists need today.
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