“People don’t want to buy a quarter-inch drill, they want a quarter-inch hole.” Theodore Levitt. 

It is important to remember Analytics and Data Science is all about investigation and the investigatory enthusiasm needs to be aligned to tangible business/project objectives! This seems obvious; however, it is important not to get caught up in the AI hype. Look for specific skills that align with your project scope. If you are at the beginning of your journey you may need to scope out how Data Analytics & AI can support your organisation so you may need someone with a broader knowledge base.  

Also, there is no such thing as the perfect candidate. You may be sitting in front of someone who is amazing at mathematical problem solving, but no knowledge or familiarity of your business. An option may be to have combined skills in a team rather than looking for the perfect “unicorn” candidate.  

So, let’s put your team together …  

Firstly, leverage existing skills! The hardest thing is to find someone internally who has detailed knowledge of your business goals and objectives, in specific those nuances only obtained by experiences. So, look for someone who is product focused and happy to pick up new skills on the way, but the focus should be business or project.  

Now move on to the second team member. Try to find someone who is methodical in their approach, pedantic about details and has a mind for numbers. 

Thirdly, compliment with an enthusiastic specialist who can bring new ideas to the team and bolster the skill sets from within. An expert in Python, SQL and other similar tools should be your next candidate.  

And your fourth candidate should the artistic visualiser and communicator!  

Lastly, hire or maybe get a consultant to develop pipelines from your data. Typically termed as the Data Engineer but this person could also be your developer who understands cloud and server technologies.  Some people may start with this role but in my opinion get those business/project details laid out then hire the most expensive piece. Makes sense, right?   

But wait, you still need a “Coach” or a person who can Govern the project and make sure policy and legal requirement are met.  

By now you have realised I have 5 team member and a Coach, and I was modelling my numbers on the 2003 Lakers, the number and numberings do not matter as long as you are delivering the right skills at the right time. The 2003 Lakers had:  

  1. They the point guard namely Derick Fisher. He understood all the plays and is a thorough bred Laker. 
  1. Secondly Robert Horry, unknown but he is methodical and pedantic about the perfect 3-point shot.   
  1. Then you have the super star Kobe Bryant (RIP Kobe) who was the centre piece. He had the Jordan Jump shot and understand all the angle of the game.  
  1. Fourth you had Rick Fox. Not the best player but his artistic flair was amazing. Ok I would probably swap him with Dennis Rodman in an ideal world.  
  1. Then there’s the Engineer! Shaq the centre who was bought in as the specialist Centre and often would not stop fighting with Kobe.  
  1. Finally, the Zen Master Phil Jackson who Governed the team to 3 Championships.  

Alternatively, you could hire Lebron James who tries to do it all but falls in the finals!  

I hope this piece sheds some light on how to think about developing data teams, but obviously, each organisation requires different things at different times. If you need any support with your data projects or just want to muse on developing your data projects get in touch today.  

Read more about our Data Analytics Apprenticeships HERE.

Imran Rehmi

A self-confessed Nerd, Rehmi joined the GBS family earlier this year as he loved the values GBS stands for. Rehmi has over 20 years’ experience in the technology and training sectors having worked on many unique projects.  

Combining his customer-focused mindset, technical know-how, and willingness to understand the customer beyond a basic project scope, Rehmi truly goes above and beyond to ensure customer satisfaction. The ability to be adaptive and research is critical in the disruptive age and Rehmi prides himself in attempting to derive commercial value in a continuously changing technological landscape.  

Head of Data Analytics GBS Apprenticeships