Chief data officers (CDOs) are responsible for overseeing an organization's data strategy, granting them a unique opportunity to make a lasting impact on their organizations. In the first 90 days (about 3 months) on the job, a CDO must become familiar with the organization's data architecture and governance framework, as well as assess the organization's current data use and identify opportunities for improvement. Most importantly, the CDO must develop an unclouded vision for how data can be used to drive business value. To achieve these objectives, the CDO must work closely with other members of the senior leadership team. By taking the time to understand the organization's data landscape and developing an unclouded vision for its future, CDOs can set their organizations up for success.
Data is a Business Strategy
In the business world, data has become one of the most important assets that companies possess. That is because data can offer insights that can be used to make strategic decisions that can improve business performance. For example, data can be used to identify trends and patterns, assess customer needs and preferences, and optimize marketing campaigns. In addition, data can also help businesses to better understand their competitors and make more informed decisions about pricing, product development, and other business strategies. As a result, data has become a critical part of business strategy. By leveraging data assets, companies can gain a competitive edge and drive business value.
The strategy for using data to drive business value may be known and discussed broadly in the organization. The CDO will need to partner with other members of the senior leadership team to ensure that everyone is on board with the strategy and understands how data can be used to improve business performance. By working collaboratively with other members of the team, the CDO can help to ensure that data is used effectively to achieve the organization's goals.
If a refresh is needed, or the current the strategy is too tactical or technical, a pivot and focus on the tangible business value may be in order.
Data Outcomes are Business Outcomes
Chief Data Officers (CDOs) are responsible for deriving value from data through data-driven insights. To do this, they need to be able to attribute value to the right things. Chief Marketing Officers (CMOs), on the other hand, are focused on delivering customer value and, as such, often attribute value to the things that create the most direct customer impact. This can lead to a disconnect between the two groups, with CDOs feeling that their efforts are being overlooked, and CMOs feeling that CDOs are fixated on indirect attribution. The reality is that both direct and indirect attribution are important. CDOs should focus on delivering value through data-driven insights, while CMOs should focus on delivering customer value. However, both groups need to be aware of the importance of both direct and indirect attribution, and work together to ensure that the right attributions are being made. Otherwise, they risk missing the benefits that each can bring.
This is not an exercise about "who", it is all about the "what" that gives a CDO an understanding of how mature the organization is when it comes to leveraging data assets to drive business value. Once the roadmap is in place, it is important to monitor progress and revise the plan as needed. By taking these steps, CDOs can ensure that their data projects are delivering real value to the business.
Data as a Process
If your process begins with an "onboarding" form of sorts...stop!
Behind every form is a long and overly complicated process that ensures standards, prioritization, and so on. You might get lucky and have a PMO, and a PMO-of-PMOs that reviews architecture implications. Then if you are really lucky, 90 days later you have ingested that "CSV file" with its 4 columns of data and "n" of rows, and by that time the project is dead.
The role of the Chief Data Officer is to know what data you have and is it fit-for-use. FULL STOP. What the business is looking for is: will this "data" work for the purpose they intended, completely and accurately?
In our experience, it's hard to answer questions about how accurate and complete the data is, and even the smartest clients don't always ask them. Your team's thinking is based on a pattern, not on working with the business to figure out what data is needed and then working with the technical teams to make sure the data is clean and ready to use.
In the cases where your team is doing an okay job working with the business, they often accede to the impulse to do something quickly and will not follow any common design standard, which leads to "franken-data".
Your team should start with a standard path where the data acquisition, cleansing, and integration are part of a light-weight pattern without forming a special "project team" or require "project funding." The goal is to make sure that the data is ready for use when needed and that it can be accessed quickly and easily. Some of our clients refer to this as the "time to value", a quantifiable metric that data teams can track.
The right answer would be that we can ingest, learn, catalog, and have sense of the scope of the data today.
This statement highlights the importance of having accurate and complete data. CDOs need to be careful not to focus too much on just acquiring data and not enough on ensuring that it is accurate and complete. This can be a challenge, but it is important to make sure that the data is ready for use before embarking on any projects.
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