Hub & Spoken.

What's in this podcast?

In this episode Jason talks to Allison Sagraves, who until recently was the Chief Data Officer at M&T Bank. Now a Portfolio Chief Data Officer, Board Advisor and continuing as Adjunct Faculty on the Chief Data Officer Program at Carnegie Mellon University.  Together they discuss Allison’s move into becoming a Portfolio CDO, why you need to learn how to prioritise value as a data leader, winning ugly and her take on how data culture is different to business culture. 

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One big message

There is a big push for the democratisation of data in big corporations to foster a healthy data culture but are activities like this always necessary? Resources are not limitless so it is good to get into a habit of checking your activities and taking focused action in order to get the best results.  

[00:45] Why Allison left her job at a Big 4 Bank to take on a portfolio

[04:08] Providing value with data and ways the value can be reflected within the company

[11:30] Why success criteria needs to be aligned with business objectives

[18:50] How to strategically create reasonable expectation

[21:26] Prioritisation in data

[27:10] Creating a well-rounded data team

[32:15] Delivering value at scale

[37:50] Why you need to understand the ‘why’ behind a strategy before running off to implement

Focusing efforts to drive competitive value

Pinning down the main business goals and objectives is only one part of a much larger picture when it comes to becoming more focused. Data leaders need to sit down and consider where a lot of time and energy is already spent and weigh up whether or not the current activities of the data team are producing fruitful results for the organisation. According to recent research, only a minimal amount of revenue on average is directly attributed to data. This is not to say that data has a huge impact on things which may not directly impact revenue, but it is a good wake up call for data leaders to realise that there is still so much knowledge and expertise that can be leveraged if they concentrate on the correct things. 

Competitive value is all about really drilling down on what the data team can do to push the needle forward in a business amongst their competitors. Sometimes we spend so much time focusing on things such as trying to teach everyone in the company about data, or creating several unscalable data products that it can become easy to lose sight of what is important for a data team to work on. 

Strategically prioritising data

There is no doubt that data can help with any part of a business. However, it is ultimately up to the data leader within the organisation to sit down and strategically prioritise what needs to be done in order. For example, if an organisation wishes to collect data on customer traffic during a promotion that will take priority but there are other things such as examining operations and systems or other projects that can be put on the backburner if necessary. Not everything needs to be full systems all at once and as much as the term ‘transformational change’ is used, sometimes the best transformations are often done in smaller chunks, relieving pressure off your data team so they can remain focused on the task at hand. 

Balancing soft skills within a data team

Data teams are often composed of scientists – the ‘doers’ who put together data products and analyse the outputs. But there is an argument to be made to include people in the team who are good at strategy and leadership too. Every team needs encouragement and support which is often lacking in data teams who are usually focused solely on numbers. Having that extra bit gives data teams a greater sense of direction. 

Separating business culture from data culture

Data culture and business culture are two very different things. Business culture is about facilitating change and achieving results, while data culture is all about the data itself. Data leaders often fall into the trap of assuming that business needs are the same as data needs, but this is not the case. Business needs are constantly changing, whereas data needs are relatively static. As a result, it is important for the data leader to separate the two cultures and to understand the nuances between them. Only by doing so can they truly understand the data and its role within the organisation.

Conclusion

Data leaders are faced with a huge task of taking on a role that is still yet to be fully defined by the industry. It is up to them as leaders to take stock of what is happening within an organisation, come up with a focused strategy and knuckle down on things that can help propel a business forward.