How to build your data team
Peer reviewed by Kat Holmes – Data Director ITV
As businesses recognize the decisive power of data to achieve business goals, most are hoping to put data in the driver's seat of their business and product strategies. This entails putting together a strong data team that can effectively propagate its insights across different areas of the business. Unfortunately, this is no easy task.
To be truly data-driven, companies need to build three capabilities: data strategy, data governance, and data analytics.
Strategy: Data strategy is your organization's roadmap for using data to achieve its goals. It requires a clear understanding of the data needs inherent to the business strategy. Why are you collecting data? Are you trying to make money, save money, manage risk, deliver exceptional customer experience, all the above?
Governance: Data governance is a collection of processes, roles, policies, standards, and metrics that ensure the efficient use of information in enabling your organization to achieve its goals. A well-crafted data governance strategy ensures that data in your company is trusted, accurate and available.
Analytics: The term data analytics refers to the process of analyzing raw data to draw conclusions about the information they contain. Typically, those involved with data analytics in an organization are data engineers, data analysts and data scientists.
Ultimately, your ability to leverage data will depend on these three pillars. If you’re reading this and realizing that your organization possesses none of these, don’t worry. That’s why we’re here. A good place to start is to build a strong analytics team, one that is ****closely tied with the strategic goals of your business. It is the first pillar of your data organization, and the focus of the article.
When building a data analytics team, heads of data typically grapple with the following questions:
They rightly do so; having a strong data team is not a luxury anymore, but essential to the very survival of a company today.
Let's start with the basics though.
Before building a data team, it's important that you realize where you are in your "data journey", because this will directly affect the structure of your team. This part is thus dedicated to a simplified data maturity assessment. Beware, company size, and data maturity are two different things. Your organization can be large but immature on a data level.
Data maturity is the journey towards seeing tangible value from your data assets. We propose a simple framework of data maturity assessment, in which you measure your ability to understand your past, know your present and predict your future. What do I mean by this?