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Leaders discussion: Mental models of an effective analytics team

Team dynamics have a big impact on the effectiveness of the analytics function. Selecting the right candidates and understanding existing practitioners can be a worthwhile exercise for an analytics leader. This article looks at three psychological models that have gained traction in this discipline.

There are many challenges around recruiting and building an analytics, not least of which is the constrained supply of appropriate candidates. Applying an additional filter might seem counter-intuitive when you have open roles. But hiring in the right talent, rather than any talent can see the productivity of the team increase in such a way that missing resource becomes manageable.

This is where psychological profiling at selection stage has an important part to play (and can equally be applied to existing practitioners in order to understand the nature of your incumbents). Profiling is a relatively mature dimension of human resources and operations management, but has seen relatively limited adoption by the analytics function until now. In part, this reflects the fact that long-standing psychological profiling tools, such as Myers-Briggs tests, are focused on individuals self-assessing for their personal characteristics.

In the context of a group of individuals who are required to operate as a team, building supportive and mutually beneficial relationships, and capable of close engagement with external stakeholders, a new body of models is emerging which may prove to have value for DataIQ Leaders members. Here are three of the most relevant examples.

Belbin Team Roles

Developed by Meredith Belbin in 1981, following nine years of study, these have become one of the most accessible and widely used tools to support team building. Belbin’s psychological models have been developed specifically around workplace behaviours and have begun to be adopted by companies who recognise that talent needs to operate together. There are nine Belbin Team Roles.




Resource investigator

Outgoing, explorative

Over-optimism, short-term focus


Co-operative, non-confrontational



Confident, clear thinking



Creative, complex problem-solver


Monitor evaluator

Strategic, good judgement

Critical, lacking drive


Self-starter, skilled

Narrow focus


Dynamic, courageous



Reliable, organised


Completer finisher

Conscientious, quality oriented


Profiling candidates and teams requires a trained practitioner and each organisation will have a balance of types that is specific to its culture. Analytics teams can typically be heavy on thinking roles and lacking around people orientation, which is where understanding through Belbin profiles can play a valuable part in enhancing team effectiveness (see figure 1). The downside is that this can be an expensive process, especially for a large analytics function.

Belbin team roles

Deloitte Business Chemistry

Recognising that academic personality tests did not take the workplace into account, Deloitte consulted with a biological anthropologist, Helen Fisher, who helped it to develop a list of observable personality traits and preferences that are relevant to business. This was then built out into a survey which was tested on three independent samples. The results were analysed using statistical genetic population models developed by molecular biologist, Lee Silver. This generated the four work styles in this profiling system.




Outgoing, focused on big picture, spontaneous, risk-taker, adaptable, imaginative


Diplomatic, empathetic, traditional, relationship-oriented, self-starter, non-confrontational


Quantitative, logical, focused, competitive, experimental, inquisitive


Methodical, reserved, detail-oriented, practical, structured, loyal


Pioneers, drivers, integrators and guardians,” Suzanne M. Johnson Vickberg and Kim Christfort, Harvard Business Review, March-April 2017

Within an analytics team, effectiveness can result from the correct pairing of styles, such as having an integrator working to ensure that a driver’s work gets deployed. Conflicts can arise from the wrong mix, however, such as a pioneer proposing a solution which a guardian deems as too high-risk. If the work styles can be understood, then it enables the analytics leader to apply the most appropriate management techniques, from incentives to conciliation, to keep a project on track and the team dynamic healthy.

Google Team Effectiveness

As might be expected from the digital technology giant, optimising the performance of its analysts is a key concern. It employed re:Work to conduct interviews with Googlers which identified 250 attributes within its teams. What emerged is a set of five key dynamics which typify successful teams and which are monitored through ongoing testing and improvement.



Psychological safety

Confidence in taking risks, willing to be vulnerable


Meet deadlines, maintain standards of excellence

Structure and clarity

Clarity of roles, plans and goals


Work has personal meaning for team members


Work is thought to matter and leads to change

The most powerful of these dynamics emerged as psychological safety and members displaying high levels of this have longer job tenure and are more likely to develop innovative solutions. Notably, executives rate them as effective twice as often as others. For analytics teams in organisations with less scale than Google, this model may be hard to adopt directly, but its outputs an be used to inform recruitment choices with a little effort.

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