Over the past decade, Pfizer Inc.’s (NYSE:PFE) data science senior director Chris Kakkanatt has been transforming the company into a collaborative and integrated intelligence entity. This idea has made headlines for years, and with the proliferation of advances and data in machine learning, the objective has become necessary for most organizations.
Kakkanatt shared the transformation the company has had in the last 170 years with Dataiku’s COO Kurt Muehmel during the Transform 2020. He explained how Pfizer turned years of technical debt into combined intelligence in the company. The approach entailed breaking the objectives into three main areas.
How Pfizer transformed into AI organization
According to Kakkanatt, the first area of focus was emphasizing empowering colleagues globally on the mastering of data sets. Because of the wide range of technologies available and different skills, the company sought to empower them regardless of whether they are coders or clickers. Therefore, it is important to enable all functions of a company by removing all barriers to allow users access data.
He explained that the creation of interactive visualizations helps people interact with models. For instance, the Plug and Play method has been a game-changer for moving people from their silos to explore other areas.
The second move was to do away with silos by transforming the way business colleagues in various sectors engage. The need to have all people in the room has been removed. Colleagues can look at what others are doing and understand what they are doing. Interestingly a data analyst can dig into the data and understand the process.
Pfizer leveraging AI
Another even big area is leveraging machine learning and AI to accelerate the rate of decision making. Kakkanatt indicated that Pfizer started by being selective on the projects where to use machine learning. They employed a range of business questions and functions to understand how to apply the tech collaboratively across the organization. Pfizer stated testing machine learning on different lighthouse projects to determine the right fit for the initiatives.