Ahead of his appearance at this year’s Chief Data & Analytics Officer Africa conference, Michiel van Staden, Data Analytics Lead: Everyday Banking Growth at Absa, shares three things his experiences to date have taught him about data leadership
The value of data analytics rests on communication. It is a multi-disciplinary role, requiring a data analyst that:
Fundamentally understands the relevant subject matter (i.e. the business)
Knows how to efficiently and creatively mine data for relevant insights
Has developed the ability to share those insights effectively
But in practice, data analysts can spend much of their time running the same ‘business as usual’ data processes over and over. It often falls to individual analysts and analytics leadership to showcase and sell what more could be possible.
Given the high levels of ambiguity in this function, work outcomes can vary significantly depending on the individual data analyst involved. So, how do we enable, empower and develop these people to deliver their best?
What They Don’t Teach Data Analysts in School
At school, I excelled in mathematics, subsequently achieving my BSc Honors degree in mathematical statistics. My ability to make sense of numbers and identify patterns makes me suited to a career in analytics.
Having conducted many interviews for a variety of data analytics roles, I have found the primary alternative to statistics recruits come via a computer science-focused education. These candidates generally exhibit the foundational language needed to communicate with computers.
When starting out on a career, what both of these profiles have in common is that they do not know how to make data ‘work’. Yes, dealing with numbers and talking to computers are the ultimate keys. But being an effective data analyst requires at least three things they don’t teach you in school.
1. Guidance from Someone Who’s Been There Before
Data environments are not standard by any stretch of the imagination. Each one of them comes with its own access processes, tool setups and pool of information to work with. Getting the required access and software set up to do your job successfully can potentially take months to resolve.
As a data analyst, if you do not have somebody who has been through it and can closely guide you on which processes to follow and people to speak to, you cannot deliver. In addition to the basics, there are also environment-specific hacks, which only those in the know can tell you about. These can have a dramatic impact on what you are able to produce.
The information at your disposal is also very specific to the environment. Firstly, you need to know what is available before you can have any idea of what is possible. Secondly, you need to be able to find the right data source to go to for a specific piece of information. Thirdly, you need to know exactly what a piece of information means before you can draw any conclusions. For all of the above, you need somebody who ‘knows’.
A business focus on ongoing documentation obviously also helps. But data analytics, MI [management information], data engineering and technology resources are often consumed by other business priorities. So, this does require business appetite for either adjusting delivery timelines to allow for hygiene factors or recruiting additional documentation resources.
2. Direct Exposure to Key Company Stakeholders
The most challenging part of working in data is not technical. It is figuring out how to engage around technical matters with company stakeholders.
Personally, I used to dread these engagements. Hiding behind emails was generally my ‘go to’ mode of communication. What I looked for in a manager was the willingness and ability to shield me from these people.
Thus, as I moved into leadership, I thought doing what is best for my team meant protecting them, too. That is, until I realized that I developed most when forced to directly confront these challenges.
In my experience, the value of data analytics rests on communication. So, to be an effective data analyst, you need communication skills. Training can help provide analysts with guidelines. But you only get better through practice.
We need to expose our people to these very challenging situations for them to grow and develop close relationships with key stakeholders.
3. Enough Space to Deliver the Goods
As data analysts, we add value through what we come to know. But becoming a data leader is about letting go of what we learned on the frontlines.
Leadership is about allowing our teams to take ownership of and improve on the status quo, rather than just keeping business as usual running. Coaching is a brave but proven approach to giving them time to think. This can put staff on the right track through clarifying values, goal setting, identifying plans of action and providing analysts with space to solve business problems.
From us, as data leadership, analysts need a clear data analytics vision and specific business focus areas. Trying to do everything for everyone at once is a sure-fire route to burnout without making any progress.
A data leader who understands what it takes to develop new capabilities is critical for buying data analysts sufficient time and giving them the freedom to make mistakes, while supporting their ongoing training and development.
Given the high levels of ambiguity in data analytics roles, work outcomes can vary significantly depending on the individual data analyst involved. As such, data analysts need their leadership to provide them with the right guidance, exposure and space if they are to deliver their best.