Building an effective Data Analytics team for your business

Data Analytics is an enterprise capability that requires the right combination of skills and the right governance model. Our experienced team brings together the deep data science, change management and coaching/ mentoring skills to build the right Data Analytics team, build the right Governance model for Data & Analytics team and ensure change lasts.

It takes more than statistical/advanced maths mastery for a data analytics team to have the right decisive impact on the organising they are serving with actionable insights.

Business Understanding 

Data & Analytics should be focused on solving a business problem as best expressed by Line of Business stakeholders. This requires curiosity around business issues, questioning skills, communication skills and negotiation skills (balancing the importance of the business question, available budget, available supporting data etc…)

Change Management

Data & Analytics is about actionable insight. In other words, success is about action enabled by data insights, basically, change in the way an organisation does its business and makes decisions even at a very small scale. Change needs to be anticipated and prepared for to cover both hard and soft components (emotion, resistance to change etc).

Data Science related skills

Data Engineering / Data Transformation / Data Modelling. Of course, a Data Analytics team need to provide core Data Science capability be it in the engineering, preparation of data (effectively being able to bring together all different data sources together and address data related issues linked to these sources) and the right data modelling capabilities in both Business Intelligence and Advanced Analytics.

The right governance model, be it informal, is needed between the expert Data & Analytics – the supplier of Insights – and “Line of Business” people – those demanding insights:



The right lines of communication need to be put in place so that those in need of insights (Line of Business People) know whom to turn to. Too many times, in our experience, it is the other way around! Members of the Data Analytics team try and demonstrate their value by providing insights to business people that never really asked for it. This usually is a symptom of a lack of sponsoring from the top of the organisation.


Simple and effective prioritisation processes should be implemented with regards to the nature of analytics work and the right type of investment in enabling capabilities (Data Infrastructure, Software, People and Skills etc). This requires an overall roadmap and vision against which decision can be made.

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