Demonstrating value as a Chief Data Officer


The year has started with the proverbial bang. But even though the pace has been furious, there are many constants in which we can find comfort. One of these is how critical data is to every organisation regardless of industry vertical.

In my reading travels, I have come across this article published on Upside in June last year. In it, the author Hannah Smalltree examines how Chief Data Officers can help accelerate success at an organisation.

One of the things I like about it, is that she positions the article from the point of view of how an impact can be made by achieving quick wins. This is especially the case when you are new in the CDO, CDAO, or CAO role. We all know that it is much easier to achieve success in an established role or when you transition from a CIO position when you already have credibility in that position. But when you are new, or the role is new, this credibility must still be established. What makes this even more difficult is that you need to prove yourself against a backdrop of scepticism as well.

Embrace the cloud to shave months off modernisation

This is an interesting point. Using a modernised stack in the cloud for analytics, if done correctly, can be a massive time and cost saver. But as a new CDO, and especially a new CDAO/CAO, would this really fall under your remit? Would you have a say on infrastructure and systems from day one? In some larger organisations, this responsibility could fall under IT, the CIO, or a technology manager. In such a scenario, you can still request the services, illustrate the cost savings, and deliver results quicker, but it may just not be directly under your control.

Get the right people

I am a big advocate of this. Yes, you need the right people especially when it comes to the roles, skills, and cultural fit required in the organisation. However, you do not need to have a large (and costly) team in place. It is possible to get meaningful results faster and more cost-effectively by using a small, agile, and appropriately skilled team. Essential is the ability to communicate with the business; understand its requirements; understand, analyse, and move the data; and develop and productionise the analytical insights your team produces. Fortunately, this can be done with as few as three people if you jump in and get your hands dirty as well.

Introduce self-service analytics and data democratisation

Long-time readers of my blog will know that I have my reservations about self-service anything. It makes sense to empower data scientists and analytical modellers. But they should be in your team! My concern is about enabling business users to do their reporting and their own analytics especially if the insights are not validated and governed.

Deliver more use cases, faster

This is key to establishing your role and credibility quickly. But you must balance between delivering successfully versus taking on too many projects to manage at the same time. It is therefore important to align with the company’s crucial business priorities and ensure that the insights align with the needs of those initiatives.

An amazing (in terms of analytical wow-ness) but ‘useless’ (in terms of business benefit and value realisation) analytical insight is not going to do much to establish your credibility. Even more so when it is in the initial stages. It is therefore imperative you align with the business priorities of the organisation.

Demonstrate value quickly

For any analytics initiative, it is especially important to always analyse and report the value realisation. Analytical projects often get questioned about cost-effectiveness, money well spent, and so on. Demonstrating the realisation of value pro-actively not only eliminates those questions, but it also establishes your credibility.

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