Initiated: Spring 2021
Expected completion: Fall 2022
Next event: Annual Conference session - Thursday, May 20, 11:15am; Learn more and register
The value of analyzing data from university and industry partnerships allows for the understanding of systematic engagements. When R&D teams are geographically distributed and their university partners are also varied, member companies would be interested in some key analytical metrics. These can include degree of cohesion among the teams, intellectual property sharing, diversity of technical thought brought into the project, maturity (TRL) levels of research artifacts and the yield (measured in transferable technology and research products), talent acquisition into R&D functions within the company.
Information that becomes available to IRI and its members can help set benchmarks for university and industry collaborations and companies can determine areas that need investment of resources.
The current data repositories at IRI may have a lot of textual data that include interviews, opinions, focus group studies and workshop proceedings. In addition to textual data, quantitative data to produce better analytics may be needed.
The methodology for the project will be to utilize both textual data (through natural language processing analytics) and quantitative data (through statistical and multivariate analyses). If quantitative data is lacking, we may develop new questionnaires or surveys and use the techniques of survey analytics to synthesize information. We expect such surveys and questionnaires to be run on an ad hoc basis or during IRI networking events. In many cases, we will run simple surveys the like of which are seen in webinars, which have almost immediate responses. Additionally, we believe that we can use textual data from the case studies available in IRI databases, plus use freely available data from government sources (IPUMS, BLS, Census etc.) Thus, the methodology will utilize data across surveys, case studies, focus groups, and other demographic data.
The end result will include a dashboard that shows key performance metrics from university engagements. Dashboards can present informational insights derived from the data with suitable visualization. This helps in getting the summary information quickly to prospective decision-makers. A summary of best practices in leveraging universities will also be included in an RTM article.
Rhonda Crate, Adjunct Professor, Washington State University and Principal Data Scientist/Associate Technical Fellow, Boeing
- B.A., Anthropology; Eastern Washington University
- M.A., Anthropology; Washington State University
- M.S., Statistics; Washington State University
Rhonda has been a part of The Boeing Company since 2014 and is currently working as a senior data scientist supporting the Analytics and Information Management Services within the Information Technology and Data Analytics organization. In addition to her MA in cultural anthropology and MS in statistics from WSU, she has earned professional certificates in statistical programming with R and big data technologies from the University of Washington, and is currently working on a master’s certificate in geospatial intelligence from Penn State University. Rhonda teaches R programming classes through Boeing’s Ed Wells program and is a relations focal for the WSU College of Arts and Sciences within Boeing. She is currently teaching a class for WSU Global Campus, Data 424, which helps students learn to combine skills they’ve gained from the data analytics program into creating a solution for an Industry based analytics project. Prior to her work at Boeing, she worked at a small marketing company doing work for companies such as Microsoft, GCI Telecom, Treehouse, and Seattle Central Co-Op.
Outside of work, Rhonda enjoys doing sewing craft projects, hiking, gardening, and organizing. She is married to fellow data scientist Andrey Zaikin, has an elementary school-age daughter named Elsie, and one fluffy Russian Siberian cat named Emma.
Saurabh Sircar, Sr. Project Manager, Airspace Operational Efficiency, Boeing Research & Technology
- B.S. Electrical Engineering, Indian Institute of Science, Bangalore
- M.S. Computer Science, Pennsylvania State University
- Certifications in Decision Making & Financial Management, Cornell University
- Executive Certification in Venture Capital, UC Berkeley
Saurabh is currently working as a Program Manager for research projects with FAA in the area of airspace operations. He is also leading effort in technology development, evaluation and proposal writing, business case preparation and customer interactions with government and commercial customers. He is also responsible for contracted R&D strategy and has led as Principal Investigator in several contracted research projects. Prior to his current role, he was Project Manager in Advanced Services group developing synergy opportunities between commercial aviation services and government services. He utilizes his experience with technology sets that include collaborative information systems design including decision-support systems, quantitative techniques including statistical analyses and multivariate analyses, modeling and simulation technologies including discrete event systems and agent-based modeling, information storage, retrieval and knowledge management systems, performance metrics for operations including productivity and risk and systems engineering design and evaluation (quantitative and qualitative analyses).