(US and Canada) Joshua Peterson, Interim Director of Health Plan Business Intelligence at Kaiser Permanente, talks to Robert Lutton, Vice President of Sandhill Consultants, about his nontraditional journey toward data and analytics. While most data and analytics leaders come from computer science backgrounds, he was an economics and finance major.

Reflecting on his first job, Peterson says he was trading $9 billion in FED funds for a large regional bank in Ohio, and he tried to build out and apply statistical models during that time. During his MBA program, he learned how to predict price movements for FED funds and euros.

Peterson, fascinated with the power of prediction in mathematics, soon began to use these quantitative methods to predict market movements. For the most part, however, using such methods was a bit fringy in his organization, especially in the late 1990s and early 2000s.

Although he was not initially inclined to start pivoting into data and analytics in 2014, he soon recognized it was on the horizon. So, he started with the base of the data and analytics pyramid. He did some information mapping, information management, and governance work for a large financial services organization. He believed it would be imperative to understand data, infrastructure, systems and how important it would be to have strong governance around your data assets. He says it was something he would have been exposed to earlier if he had chosen a more traditional route. 

He eventually started digging into advanced data analytics, machine learning, and artificial intelligence. First, he self-learned R Python and the sequel, and then learned  data visualization platforms like Tableau.

Peterson joined Kaiser Permanente in 2019 and took care of front-end data via analytics. He initially joined the organization as a senior data analyst and worked on several reports in areas like outside medical space and the care continuum space.

Operational reports and dashboards for internal customers are essential for business and functional leaders, he says, and he has been pitching more toward predictive models and analytical insights rather than reporting counts. Reporting counts are significant, but it is essential to be proactive instead of reactive, he emphasizes. He has started moving forward with his insights and preaching the power of advanced analytics and approaches like machine learning. Kaiser is currently working on projects like voluntary membership termination, looking at things like the characteristics of readmission.

While being data-driven is imperative, he thinks that CDOs and other data leaders need to have a strong foundation in infrastructure and systems, information management, governance, and front-end analytics. It is crucial to have that rounded experience, especially as older and not necessarily natively digital companies, look to restructure their IT, talent, and processes to better take advantage of their organizations’ massive amounts of data. He emphasizes that it’s also paramount for leaders to understand the businesses they support.