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| Data Management Series |
The Chief Data Officer (CDO) or the “Head of the Data Team” is one of the most challenging jobs because is more of a "political" than a technical role. It requires the ideal candidate to be able to throw and catch curved balls almost all the time, and one must be able to play ball with all the parties having an interest in data (aka stakeholders). It’s a full-time job that requires the combination of management and technical skillsets, and both are important. The focus will change occasionally in one direction more than in the other, with considerable fluctuations.
Moreover, even if one masters the technical and managerial aspects, the combination of the two gives birth to situations that require further expertise – applied systems thinking being probably the most important. This, also because there are so many points of failure that it's challenging to address all the important causes. Therefore, it’s critical to be a system thinker, to have an experienced team and make use adequately of its experience!
In a complex word, in which even the smallest constraint or opportunity can have an important impact especially when it’s involved in the early stages of the processes taking place in organizations. It relies on the manager’s and team’s skillset, their inspiration, the way the business reacts to the tasks involved and probably many other aspects that make things work. It takes considerable effort until the whole mechanism works, and even more time to make things work efficiently. The best metaphor is probably the one of a small combat team in which everybody has their place and skillset in the mechanism, independently if one talks about strategy, tactics or operations.
Unfortunately, building such teams takes time, and the more people are involved, the more complex this endeavor becomes. The manager and the team must meet somewhere in the middle in what concerns the philosophy, the execution of the various endeavors, the way of working together to achieve the same goals. There are multiple forces pulling in all directions and it takes time until one can align the goals, respectively the effort.
The most challenging forces are the ones between the business and the data team, respectively the business and data requirements, forces that don’t necessarily converge. Working in small organizations, the two parties have in theory more challenges to overcome the challenges and a team’s experience can weight a lot in the process, though as soon the scale changes, the number of challenges to be overcome changes exponentially (there are however different exponential functions in which the basis and exponent make the growth rapid).
In big organizations can appear other parties that have the same force to pull the weight in one direction or another. Thus, the political aspects become more complex to the degree that the technologies must follow the political decisions, with all the positive and negative implications deriving from this. As comparison, think about the challenges from moving from two to three or more moving bodies orbiting each other, resulting in a chaotic dynamical system for most initial conditions.
Of course, a business’ context doesn’t have to create such complexity, though when things are unchecked, when delays in decision-making as well as other typical events occur, when there’s no structure, strategy, coordinated effort, or any other important components, the chances for chaotic behavior are quite high with the pass of time. This is just a model to explain real life situations that seem similar on the surface but prove to be quite complex when diving deeper. That’s probably why a CDO’s role as tamer of complexity is important and challenging!
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