Building High Performance Data & Analytics Teams

When we work together with our partners, we often assist them in building a data team. Numerous screenings and interviews all demonstrate one thing: finding the right candidate for the job is hard. It is extremely difficult to find someone with the right skills, who also aligns with the company.

To help you out, we have listed our steps for building high performance data & analytics teams in this blog. Although there is no silver bullet or a blueprint for guaranteed success, these steps enabled us to build multiple high performance data teams, including the one we have at The Data Story, often labeled as a “high expertise team” or the “Special Forces of Analytics”. This blog will elaborate on the chain data teams go through and explain what firefighters can teach us about building a team the right way.

Building Functional Chains

Data teams function as a line of firefighters who pass a bucket of water. At each handover, a data product is passed on to the next step. Hence, it is counterintuitive to appoint a single person to handle data, in contrast with what many companies believe. Even appointing one person, only “for now”, will probably not work out, since all the steps in the chain need to be completed diligently. For that reason, we build teams based on a fully functioning chain.

Whether it be a completely self-sufficient team or one that gets external help at points where they lack experience or capacity: we build teams with a fully functioning line of capabilities and capacities. Now that we have introduced the chain, let us dive deeper into its specifics.

The data chain consists of seven steps, as shown above. When looking at the chain, it becomes clear that many different disciplines are involved. The chain starts off more technically and progresses to more business-oriented tasks. The final steps of the chain are about translating data into decisions and strategies – what actions to take. With so many different fields involved, it is slightly different from the chain in our firefighter analogy. It does become apparent though, even more so, that a single person is not sufficient to handle the entire chain on his own.

When seeing all these distinct steps, companies might be tempted to focus on only one part of the chain. This way, they need less people and can still handle some of their data. However, if another part of the chain is neglected as a result, less value can be delivered. To illustrate: when firefighters carefully hand over the water bucket at the beginning but neglect the final steps, less water reaches the end. Likewise, when firefighters neglect the initial steps they will have less water to carry at the end of the chain.

Finding Firefighters

Now that we understand why we should appoint several firefighters, we will share some tips for finding the best firefighters. Evidently, the interactions across the chain are very important. Not only is the successful execution of each task essential, the connections between them also require great care. Chains that lack these strong connections will have firefighters losing water along the way. Thus, communication is key.

Apart from communicatively strong firefighters, we also prefer those who have knowledge and understanding of connected steps. This way, data is handed over with the next step in mind, making the next step easier to execute. Moreover, mindset and the ability to cooperate are crucial in a team of firefighters. As such, we would always favour someone with thorough experience and the best mindset over someone with perfect experience who does not fit the team well.

Lastly, do not get caught up on finding someone with experience in certain tools and languages. If one knows one or two data tools or languages, he is capable of handling them all. As long as a firefighter is able to extinguish a fire, any fire is manageable.

Performance Data & Analytics Teams

Data Team Success

Now that we know why and how to build high performance data & analytics teams, we also know where things might go wrong. When efforts are wasted and results are not as expected, companies might feel like their data team is failing. Likely, the data team is not to blame but instead its setup. Holding a single firefighter accountable for executing the entire chain does not make sense. Likewise, only focussing on one part of the chain and neglecting other parts means less value can be delivered in the end. Moreover, by hiring the right communicative people with knowledge and understanding of related fields, one can make sure that connections within the chain are strong. This way, there is greater certainty that value will be delivered. It provides confidence that fires will structurally be extinguished.

Building high performance data & analytics teams requires understanding what is needed, and acting accordingly. Do you have any questions or need someone to look over your shoulder? Feel free to reach out, we are more than happy to help!

Follow The Data Story on LinkedIn to stay up to date on our blogs and more!

Need some help?

2022-03-10MRF (1055)

Jeroen Bakker

“Data speaks volumes and is the foundation and input for the issues at play in a company. By making data visual, it becomes recognisable for everyone.”

More Data stories

BLOG_afbw2
Data stories

Analytics for a Better World

For the second year in a row, our team-member Sophie Caro attended the Analytics for a Better World conference on May 14th. Nowadays, analytics play an important role in increasing...
BLOGquality (1)
Data stories

Building High Performance Data & Analytics Teams

When we work together with our partners, we often assist them in building a data team. Numerous screenings and interviews all demonstrate one thing: finding the right candidate for the...
Data quality
Data stories

Data Quality is not difficult - how automation simplifies

When companies start collecting more data, data quality eventually becomes a topic of discussion. With more plants in your garden, maintenance is a larger responsibility. It is good to be...
clean ai
Data stories

AI needs clean, high-quality data - here’s why

With AI becoming more and more popular, its usage as a technology as well as a buzzword is growing ever so quickly. Even so, the title of this blog contains...
Product Owner
Data stories

Unlocking Data Potential: Role of a Product Owner in Data Teams

In the ever-evolving landscape of data science and analytics, organisations are recognising the need for a holistic and strategic approach to manage their data and turn it into value. One...
BLOGuit
Data stories

What is Server-side tagging in Google Tag Manager?

You’ve probably heard about Server-side tagging and might be wondering “What is it exactly?” and “How is it any different than the current Google Tag Manager setup?”. This blog will...
en_USEnglish