Peter Serenita recalls a time when to work with data was considered a solitary pursuit that was shunted off to the backroom. This was long before the notion that working with data was considered the “sexiest job of the 21st Century”. Serenita holds the distinction of being one of the very first executives appointed as a Chief Data Officer – a position that he was named to as Chief Data Officer, Worldwide Securities Services at JP Morgan in 2006. By the time that Tom Davenport and D.J. Patil heralded the era of the data superstar, Serenita had learned many valuable lessons which have continued to stand him in good stead as we move toward the era of the Chief Data Officer 4.0.
Serenita is now U.S. Chief Data Officer for Scotiabank, the 3rd largest bank in Canada, serving over 25 million customers. I caught up with Serenita at the recent 2018 Chief Data Officer Summit, organized by Evanta/Gartner Group, and held on November 26-27 in New York. This summit is one of a series of industry events that now confirm the prominence of the Chief Data Officer (CDO) as a senior executive decision-maker. This year’s CDO Summit comprised over 150 data executives and CDO’s, featuring a range of presentations and panel discussions on the state of data and the evolution of the CDO role within leading companies. One of the keynote presentations was delivered by Serenita on the history of data management and the march to managing data at scale. This was a history lesson that few have experienced as directly, and from its infancy, as has Serenita.
Organizations are at very different stages of maturity in their adoption of data management. This is something that Serenita understands well. While some organizations have yet to reach the stage where they have appointed a Chief Data Officer, the most ambitious organizations are moving to the stage of Chief Data Officer 4.0, characterized by using data as a source of innovation and for purposes of business monetization. Most organizations sit somewhere along this continuum. For data-native businesses like an Amazon or Google, the notion of appointing a Chief Data Officer seems inherently redundant – every business leader should have data in their DNA. The role of the Chief Data Officer is most needed for mainstream, legacy companies who are undertaking a vast business transformation that leads to becoming data-driven organizations.
Serenita describes the evolution of the Chief Data Officer role over the past dozen years, as each organization has embarked on its own individual implementation of the data management journey. He reflects on the early days of data management, where data was largely an Information Technology (IT) function. He notes that the early wave of CDO’s (CDO 1.0) was focused on establishing data governance policies and practices relating to data quality, data lineage, remediation, and data ownership roles and responsibilities. Then came the 2008-2009 financial crisis, and with it the emergence of regulatory demands, standard data management practices in the form of the Data Management Capability Assessment Model (known as DCAM), and an emerging focus on the use of analytics (CDO 2.0). Serenita also notes that, “The data profession is very collaborative. Organizations can learn from one another. Data executives can benefit from the experiences of others who have been in the data trenches. But the 4.0 data executive also brings a new way of thinking that will further advance the data practice”.
In recent years, Serenita has seen a growing movement to integrate data and analytics responsibilities and functions. Whereas firms had appointed Chief Data Officers (CDO) and Chief Analytics Officers (CAO) with often parallel responsibilities, there has been a sharp movement toward the establishment of the updated role of the Chief Data and Analytics Officer (CDAO). This is CDO 3.0, which is characterized by a combined focus on data governance and analytics, coupled with a growing adoption of AI and machine learning practices, along with advanced analytics techniques.
The progressive adoption of Big Data technology solutions is enabling businesses to process and analyze whole data sets in their raw form, rather than relying upon individual data domains and tables. Data does not have to be refined in advance either. Machine learning capabilities can be employed to understand and transform data into its most usable state. Subject experts can teach the data or algorithmic model initially, and then rely on the machine to learn along the way. Serenita remarks, “We have gone from the Stone Age to space travel in the course of a decade”.
So what lies ahead? Serenita envisions a future where data is now understood to be a business enabler and a revenue generator, and where the CDO reports to the head of business strategy (CDO 4.0). This is a far cry from the days when data was relegated to the back room. Yet, Serenita is cautious as well as realistic based on his many years of experience. In the data business, you need to be. “One size does not fit all”, notes Serenita. “Factors such as stage of maturity, capability, organization, centralized versus federated management, risk, and business enablement must all be taken into consideration”.
Serenita believes that to be successful a CDO must bring together within a single executive a diverse set of skills. He describes the CDO function as being a “multi-disciplinary approach” where CDO’s should refocus on the “art of the possible”. Serenita sums up, “data has become mainstream”. He advises that organizations need to move rapidly to adopt agile data processes that enable the business to move quicker and be more responsive to internal and external customers, and notes that organizations need to leverage technology through AI and machine learning techniques. “Let the machine be the heavy lifters; let the data analyst guide the machine”, Serenita concludes.
