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,  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.
Getting to a Good Decision Takes Good Process
Data can offer a bitter truth that people don’t want to hear, Patil noted. In the case of California, the data showed that the government needed to shut down an economy that would be the fifth largest in the world if it were a country. To help make a case, Patil advises writing memos rather than relying on charts of data. Then, hold an informational meeting. Only once people have been informed should you hold a separate meeting focused on decision making.
When you do present the data, you need to answer three things: What do we want people to take away from this graph? What action do we want people to take? And, how do we want people to feel? Excited? Worried? Scared? When you’re in very tense situations, such as the situation room in the White House, you don’t have time to walk through caveats. You need to have precision to be able to answer these questions.
What Worries You the Most as a CDO?
After DJ Patil’s session, Susan Wilson, Informatica VP Data Governance and Privacy Leader, kicked off an interesting discussion by asking our board, “What worries you the most as a CDO?” Without mentioning names, I’ll summarize some of the concerns we heard:
- When building a data organization, some stakeholders think you can just dump data on the group and the problem will go away. But data management is everyone’s business, and you need to take care of the basics first (e.g., stop ingesting bad data into an AI algorithm).
- One of the biggest challenges is acquiring and holding on to the best people and inspiring those people every day.
- Executives and stakeholders are sometimes challenging because of the “shining light syndrome” and the fear of missing out on the next big thing. The stuff that needs to happen requires conviction and sometimes that conviction is missing. How much conviction do we have in our strategy?
- Another CDO expressed concern that as a data community, they felt they’re far behind and could do much more to make the situation better. When going into a new project, the CDO tells the team that “from this day forward, we need to do it right instead of cleaning up the mess from before.”
- There is concern about the data culture and working with the business, getting them to understand the potential of AI/ML, data governance, and having reliable data. Data literacy and building data as a second or third language to help remove barriers between organizations are critically important.
- One CDO focuses every day on driving the adoption and implementation of strategy, with an emphasis on the teams working on the ground and the health of the data.
- Shift your attention to create excitement and inspiration with data, another CDO advised. Everyone’s job is data, so data needs to be secure by design and super accessible. The potential for data to impact lives is exciting.
Focus on What’s Important, Not Just What’s Urgent
To close, I’ll share a few last pieces of advice from the discussion between Patil and the board. First, in the words of Winston Churchill, never let a good crisis go to waste. Now that everyone has become an armchair epidemiologist, we need to do more with our data. We need to challenge organizations to use disparate data sets and question the paradigm of traditional decision making.
And finally, be sure to focus on what’s important, not just what’s urgent. It’s a little like third-grade soccer, where everybody is focused on chasing the ball. Instead, we need to spread out and distribute tasks across teams. Rather than focusing on cleaning up messes, we should set up a structure that will help us succeed for the long term.
I look forward to sharing insights from our next gathering of the CDO Executive Advisory Board when we meet again in July.
 IDC Survey InfoBrief, sponsored by Informatica, “The Priorities, Challenges, and KPIs of Today’s CDOs,” IDC Doc. #US46695720, August 2020.