Building a Community of Chief Data Officers
Data is more strategic than ever before, and data leaders are also increasingly critical to the success of their organizations. Those leaders are now taking on broader and more business-oriented roles , [1] expanding from acting as governance gurus to assuming the mantle of digital innovator, operational optimizer, or analytics champion.
With this transformation in mind, I’m pleased to announce that Informatica has formed a Chief Data Officer (CDO) Executive Advisory Board (EAB), created to bring together a diverse community of CDOs and data strategy executives from industry-leading companies and public agencies around the world. As a global leadership forum, the EAB strives to transform business and reimagine our world through data-driven innovation by sharing insights, exploring ideas, solving challenges, and testing strategies.
At our inaugural (virtual) gathering in March, CDOs and executive data leaders from Bank of Montreal, Janus Henderson, Westpac, and other organizations shared how they’re working to shape data culture, acquire and keep top talent, and build a foundation of data literacy in their organizations. A common thread echoed by all was that data is now central to the success of their organization, whether they work in the public sector, financial services, healthcare, or telecommunications.
An Inside View of Rapid Data Transformation
We were joined at our gathering by a special guest, DJ Patil, former Chief Data Scientist for the Obama administration. Patil had us on the edge of our seats with his tale of helping the State of California coordinate its response to the COVID-19 pandemic, sparking an animated discussion between Patil and the board members.
Initially Patil’s team had very little data to work with—mostly just some stats from cruise ship passengers. Working with a group of engineers and a team from Johns Hopkins University, Patil and the team sent out a survey to gather data from hospitals and built predictive models to help determine what was happening and what action the state should take. Patil came away from this experience with six key lessons that highlight what organizations need to focus on.
It’s not the sexy stuff that moves the needle. You need to focus on the basics. Predictive models don’t do any good if the data is poor. Early in the crisis, the team spent five hours a day cleaning data from different places, eliminating duplicates and dealing with different levels of reliability.
Building a data dictionary is a vital exercise. The team had a great repository, but it was where data went to die. People spent hundreds of hours doing analysis on poor data. To move forward, they needed to track how to access the data and determine how to make it easy and digestible.
Put foundations in place to answer the hard questions. First master the basics and put in place a foundation to rapidly manage and update datasets so that you can handle more complex questions, such as determining how socioeconomic status relates to infection rates.
Get a little better every day. The team used daily intelligence briefings, a practice DJ carried over from his work for the Obama administration. Initially their analysis was weak but it compounded every day, yielding rich results four weeks later.
Use disparate data. The team derived some of their most powerful insights by looking at anonymized data from the restaurant booking app Open Table. Restaurant receipt data in the Bay Area dropped precipitously two weeks prior to dropping in Los Angeles, which helped explain higher transmission rates in Southern California than Northern California.
Make the best use of your talent. Data professionals get frustrated when they’re not challenged. Often, they’re tasked with fighting fires and don’t get to shift into deep thinking mode until after they’re exhausted.
