Blog post by Michiel van Staden Data Strategy, Solutions & Analytics Lead, Absa Group

In data, there are often so many technical aspects to get your head around.  One can spend many years just focusing on the practice of interacting with computers or the skills and understanding required to process large amounts of information.

Personally I have found that much of the learning regarding how to practically leverage these extensive abilities in the workplace, only starts on the job.

Once a data team has been put together, or data specialists have been embedded into a cross functional environment, truly getting value out of what they can offer, is largely going to depend on interpersonal skills.

Better answers requires better questions

Workflow and prioritization needs to be managed.  Only having neat questions flowing one way, and quickfire data answers coming back, is however not going to shift any dials.

You need data individuals who are comfortable in asking the questions needed for them to understand the nuts and bolts of the organization better.  When they do not, their responses are not going to fully address the requests, and they are definitely also not going to spot related opportunities.

What becomes even more powerful, is if they can start employing their data insight and analytical thinking, to challenge the asks being made of them, driving their stakeholders towards critically assessing the core of fundamental matters at hand.  Ultimately getting your data specialists to focus their efforts where they can make the biggest impact.

Nothing gets built by any one

Most of the time, it is not practically possible for data functions to build anything meaningful in an organization by themselves.  The rest of the time, even when it is possible, it is not advisable.

Sitting in front of your screen, firing off orders with your code and watching the data points entertain your demands, can be quite addictive.  Working with other people, that have their own thoughts and ideas, can be much more challenging.

Becoming comfortable with standing on the shoulders of the giants in the organisation that have already done similar work before, can however get the piece of work much further, much quicker.  Similarly, involving end users and subject matter experts in the development process, stops you from reinventing the wheel, or building a perfect square for a star shaped environment.

When studying, success largely depends on individual performance, and having the right answers.  In the workplace, it is all about alignment with others.  Data individuals need to be able to align.

Your idea versus mine

In practice, there is very rarely anything like one right or best answer to a challenge.  Given all of the variables involved, including varied life experiences, a broad range of expertise and most often very unique circumstances, you’re at best going to get a handful of well informed opinions.

Data work, especially in a theoretical sense, does sometimes present the illusion of clear cut rights and wrongs.  The real world does not work that way.  People have got a range of experiences (data points if you may) that are not neatly captured in rows and columns.

Yes, data work can definitely help in compiling, processing and summarising large sets of related information, in a way that humans can not.  Thinking that this is the be all and end all of decision making, will however not serve data specialists well inside of an organization.

The majority of stakeholders do not have the specialised education or time to make sense of the technicalities inherent in data work.  Whilst staying on top of these technicalities, towards quality inputs, data specialists thus need to refine the ability to effectively sell all they have done, focusing on that which is absolutely relevant to their audience.  This is hard.

Even the best I’s, do not make TEAM

Technical skills are needed, and can be immensely valuable.  Without developing interpersonal skills, they will not be.

Towards building teams that deliver, you are going to need to develop data individuals, that:

  1. Are adept at asking the difficult questions needed
  2. Compliments what they have around them
  3. Can relate and debate their findings next to many others

This doesn’t happen overnight.  If you want to build effective data teams, or effectively embed data in diverse teams, you are going to need to cater for a space where they can safely unpack their way of thinking about day to day interactions, have their assumptions challenged and discover their own personal best way forward.

Generic advice in itself won’t do the trick.  Telling individuals exactly what to do is rarely effective.  When presented without attachment, and with permission, respecting that it is only an opinion, guidance can however additionally also help individuals get a sense of the bigger picture.

In the end, fundamental mind shifts in data individuals are key towards getting them to gel in a team, and data to work.

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