The Emerging Role of the Chief Data Officer
Across all industries, enterprises have access to more data than ever before as insights pour in from machines throughout the company, customer queries, and archived information. These exponentially growing volumes of information have become overwhelming and unusable for enterprises, making it necessary to have designated staff in the organization to lead data strategy and decide how to manage the digitization of the customer experience, determine the stance on data ethics and the use of that data.
Thus, the role of the Chief Data Officer is emerging as companies are looking for ways to properly manage (and potentially monetize) data. In fact, Gartner believes that 90% of large organizations will have a Chief Data Officer (CDO) by 2019. This type of C-level support for Enterprise Information Management (EIM) strengthens the entire organization, getting everyone behind the concept that data is a valuable business asset and is vital to operating a successful company.
C-Suite Drives CDO Title
For many data managers today, their title may not be “CDO,” but the role is on the rise and will continue to be more formalized in the next few years.
As organizations continue to see how data is influencing the overall business model, the need for a data expert to sit in on the c-suite conversations will increase. For now, this person may be billed as a data scientist or IT manager, but as she or he gets pulled into more and more future-shaping conversations, that Chief Data Officer title will soon follow.
The role (whether formally titled CDO or not) includes a multitude of data-related responsibilities:
Data Strategy: This strategy will set the stage for the enterprise’s overall rules and policies that inform how data is treated throughout the organization. The CDO must consider internal and external data partnerships. For example, a customer agreement may promise that data gathered from that relationship does not go to any other parties. All of these contracts and relationships must be reviewed and considered before any decisions are made on how data is handled.
Data Management Processes: Once that strategy is in place, the CDO must build out the tactical aspects of executing on that strategy. To ensure that all lines of business are able to properly contribute to preserving the data’s value and integrity, an enterprise-wide process for managing data properly must be implemented and enforced to guide the way data is submitted: how much, to whom, at what time, in what format, using which tools.
Manage Challenging Data: The classic “old becomes new again” adage comes to mind as I think about the inception of the data warehouse in the 90s, and the realization shortly thereafter that we had to manage and clean it. Today companies have more than tenfold the amount of data than a data warehouse, as real-time information floods in from Hadoop, the cloud, data lakes, IoT, you name it. So, the question is no longer “how do we clean all this data?” but “which data should we clean?” The CDO must pull the data from each of these unique sources, and then determine which data to clean and how to systematically select it time after time.
Data Ethics: With the General Data Protection Regulation (GDPR) taking full effect in May of 2018, more organizations must use extreme caution when handling the external data that is brought in to the overall business process and analytics. Enterprises must have a secure and trackable process for how data is stored and moves through the organization, and ensure to its customers that data is being used responsibly. This has always been important from a customer relationship standpoint; now with GDPR on the horizon, this need is reinforced with legal and financial ramifications.
Monetize vs. Openly Share: The first four responsibilities outlined above help the CDO and the enterprise position the data to be usable and effective, so the final decision is what to do with the data once it’s in pristine condition. Some organizations choose to sell information, using it as another source of revenue for the company, while others package the insights as a value-add to existing customers. This decision-making process demands a deep understanding of the industry and the customer base that will use the data.
As with any industry, data management goes through trends, and the priorities for this role will ebb and flow over time. Over the past five years, the data management world was heavily focused on the topic of big data, and getting the greatest variety of it at the highest velocity possible. Now that we’ve obtained all the information, though, we have to manage it, move it, store it, and organize it in a way that we can trust it enough to base big business decisions on it. Only after the data has been wrangled, prioritized, and then cleaned can it be used to shape business models and enterprise-altering decisions.
There are currently more than 1,400 appointed CDOs in organizations, and with increasing market pressure to build business models from data analytics, I would expect to see even more organizations with a strong leadership role assigned to data transformation over the next few years, if not even a formal Chief Data Officer title.
About the author: Kristin McMahon is a senior director of product marketing for Enterprise Information Management (EIM) solutions at SAP. McMahon is responsible for leading the product marketing cross-activities of the SAP Database and Data Management (DDM) portfolio in addition to leading the product marketing team for SAP Enterprise Information Management (EIM) solutions. McMahon brings over 15 years of broad EIM experience to SAP. Her background in information quality, enterprise software and data governance, and analytics enables her to provide expertise in the database and data management market to global organizations. McMahon holds a Bachelor of Science degree from the University of Wisconsin and a Masters of Business degree from St. Thomas University School of Business.