The rise of the ‘data czar’

Back in 2004 Yahoo! appointed Dr Usama Fayyad as it’s chief data officer (CDO) – an unprecedented move within business but one that highlighted the burgeoning area of data management. Indeed, the work surrounding data was a business function that was becoming increasingly crucial and visible – a trend that didn’t go unnoticed in the financial services sector. In 2006, Citi’s Markets and Banking took the bold step of making John Bottega its CDO – a first within the industry. In order to find our more FST caught up with the man himself for an exclusive interview.

FST. Can you give an overview of your role as CDO at Citi and what the job entails?
JB. As the CDO at Citi my responsibility is to drive the data management strategy, policy and function. At Citi the CDO does not report into technology, as has been the norm in the industry. The model has changed here. Data management, by design, needs to be driven by the business, enabled by technology, and supported by operations.

As CDO, my responsibilities span the breadth of data, from financial instrument repositories, to customer and account data, corporate actions, pricing, positions and transactions. The CDO is a facilitator; my job includes establishing a data governance structure, defining data ownership and stewardship, coordinating technology and organizing operations. Best practices dictate that core enterprise data be managed in a federated manner, leveraging off the firm’s best subject matter experts across the various business units to create the golden copy and make it available throughout the firm via standard distribution services.

Data is recognized as an important component of a firm’s effective and efficient operation. As CDO, it is my job to ensure that data is managed and recognized as a key asset to the firm, focusing resources on achieving short-term benefits while building the long-term solutions according to a well-defined and well-communicated strategic roadmap.

FST. How did it feel to be the first person within the financial sector to be appointed a CDO?
JB. I am honored to hold this position at Citi. As someone who has worked in the data management space for many years, this is an exciting career milestone for me. I am grateful to Citi’s senior management, who, recognizing the importance of the data management discipline, took the innovative step to create this position.

FST. With it being such a unique position, has it added extra pressure on your shoulders?
JB. Certainly. While it is exciting to be the first person to hold this position, it remains an every-day challenge to define this role – and with it, to manage expectations. The CDO is a change agent. Proper data management is a culture change and these are not easy things to implement. By the very nature of its ‘newness’, the role will continue to evolve. Since my appointment, several other firms have appointed their own CDOs. It will be interesting to see how the roles & responsibilities of the CDO evolve across the finance industry.

FST. What can a so-called ‘data czar’ offer and why have more institutions not appointed a CDO, do you think?
JB. If there is one element that defines what the CDO, or data czar, can do, it would be to assume the ‘ownership’ of the data management challenge. I have heard this repeatedly asked in firms across the finance industry – ‘who owns the data problem’. Either there are too many people trying independently to solve a data problem, creating unconnected solutions, or there is no one, allowing problems to linger. The CDO role brings attention and focus to the data management challenge.

Realizing what this role can provide to a firm is becoming better understood. When speaking about implementing a data management program, firms are realizing it is not a matter of why it should be done – it is a matter of what will happen if it doesn’t get done. Regulatory requirements, financial exposure, and reputation risk are all critical aspects to a firm and all tightly linked to an efficient data management strategy.

FST. What are the primary challenges that Citi faces today when it comes to handling data?
JB. Citi is no different than any other firm when it comes to the challenges of data management: duplicate repositories exist throughout the firm due to the existence of legacy systems, internal changes, external acquisitions, etc. Like every other firm on the street, lack of attention over the years and the street’s ability to ‘patch’ solutions has created a complicated network of data creation, data maintenance and data movement.

Lack of industry standards, or in many cases, too many standards, has created a very big ‘entity symbology’ challenge – we as an industry don’t do a very good job of ‘bar-coding’ our products, customers, business entities, etc., which has led to the creation of a disjointed pockets of information that is very difficult to holistically view.

FST. How do you strive to overcome these problems?
JB. The data challenge requires both immediate solutions as well as the implementation of strategic solutions for the long term. Therefore, the approach we are taking at Citi is a combination of tactical fixes coupled with a strategic roadmap.

The plan breaks down into four pillars: remediation, rationalization, automation and governance. First and foremost, we need to correct and/or cleanse our critical data repositories so we are best positioned to both address the many regulatory requirements (Basel; MiFID, etc.), while providing flexibility to the business to pursue new markets and new opportunities. Parallel to this effort, we are rationalizing all of our existing stores of data and data operations. We need to tap into the ‘best of our best’, while, at the same time, identifying and filling the gaps of missing or incorrect data.

Next, we need to document and identify our business and maintenance processes in order to reengineer and automate whenever possible. And finally, Data Management requires a strong governance model, to drive and support the overall data program.
And I'm happy to say that in my first year at Citi, we are seeing progress in all aspects of our data program.

FST. What are the primary mistakes that business make when storing data? Is having complicated and/or disjointed databases a common problem?
JB. I don’t believe you can say mistakes were made in ‘storing’ data. More correctly stated, mistakes have been made over the years in the ‘process’ of storing data. The technology of data repositories continues to get better and better – more information can be stored from more sources, accessible to more users, faster and cheaper than ever before. But, if the data management processes that surround data are broken, the best database on the market will not make it better.

Disjointed databases are not the root cause of the problem, but a ‘result’ of the problem. Proper data management comes down to proper business process and process flow. How is the information is obtained, stored, maintained, and distributed has to be understood end-to-end. You cannot do one without the other and hope to achieve a complete data management solution.

FST. Looking ahead, how do you foresee your role and department expanding over the next few years and how will technology impact on managing data at Citigroup?
JB. One of the key foundational elements of the data management strategy at Citi was the creation of the Office of Data Management (ODM). ODM is now taking on the data management challenges, engaging the key stakeholders, and driving new solutions for the business and the bank at large. But how the role of the CDO expands over time will largely depend on the success of the data management program itself. Success will drive scope and responsibility. Establishing credibility with its stakeholders will expand ODM responsibilities. A strong alliance with the business will empower the ODM to establish important data policy and enforce compliance.

And without question, technology is critical to the success of the ODM. As the business assumes the driving force of the data solutions, technology can focus on implementation and technology best practices. Better technology implementations lead to more efficient operations. You can start to see the snowball effect because clear definition of responsibility of data management will lead to more strategic technology spending, lowering costs while focusing on key deliverables. Business process improved, technology responds, data quality improves and operations becomes more streamlined. But it all starts with data – managed as the critical asset.