CoreNet Global Summit, Boston 2018
Boston | Oct 14 - 17, 2018 | John B. Hynes Veterans Memorial Conv. Ctr
Don't miss the largest gathering of corporate real estate professionals.

Machine Learning & Data Science make CRE Smarter - Lessons Learned from the Field

October 16, 2018 | 11:45 - 12:30

Machine Learning & Data Science make CRE Smarter - Lessons Learned from the Field

Corporate real estate could take a page or two from the silicon valley playbook to innovate using data science and  AI/Machine Learning. This session will showcase a real CRE Machine Learning pilot and the lessons learnt, in addition to highlighting some cutting edge use cases & demos that leverage data science & machine learning to make this innovation journey quite interesting. Innovating in the corporate real estate world brings with it many challenges that require patience, empathy, relationship building and an endless persistence in driving to a meaningful result.

The pilot project focused on leveraging machine learning to simplify and ease the work order request burden employees face, while automating some of the validation, ticket creating, and routing hurdles inherent in some of the legacy work order systems. The project leveraged Natural Language Processing (NLP), using just a phrase, word or sentence entered by the employee to create a real work order. The project was an innovation journey, facing both technical and cultural hurdles in creating a solution that was unknown, in a manner that was outside the norm of the typical CRE technology approach. Understanding what machine learning models are available, the process of data set gathering, and the data science viewpoints on interpreting the results are all aspects that will be valuable to anyone interested in leveraging a project like this.

Key Takeaways:

  • Apply machine learning use cases to improve the experiential and operational aspects of today’s workplace.
  • Understand the fundamental value of data and need to identify where your critical data resides today.
  • Consolidate and organize the data so it’s available for further analysis, and review the quality of that data.
  • Understand the benefits of engaging enough stakeholders from all parts of the organization to avoid hurdles.