Building a High-Functioning Analytics Team


Cory Everington

Date Published:
March 16, 2018

This is the third in a series of blogs where Data Scientists Cory Everington and Anna Godwin discuss five Analytics Best Practices that are key to building a data-driven culture and delivering value from analytics. In this installment Cory discusses the benefits of team building and its impact on successful data science projects.

Now that you have built an effective data science team Building an Effective Data Science Team complete with a variety of skills, it’s important to ask the following question:

How does a group of individuals transform into a high-functioning team?

Realizing that each person brings value to the team and taking action on that knowledge sets teams up for success. In this blog post, we will explore two concepts that nurture team growth and deliver higher performance:

  • Identifying and leveraging different work styles
  • Understanding the team development process

The Four Work Styles

Just as important as understanding the technical skill set of your team, is understanding how each personality type drives performance and behavior. Understanding why team members may react differently to a given situation is important to managing the team’s success. An article in the Harvard Business Review details the following four work styles described in Deloitte’s Business Chemistry system:

  1. Pioneers are innovators. They don’t mind taking risks and are excited by the idea of trying out a new, untested technique or technology.
  2. Guardians are detail oriented and methodical. They want to know the facts and are risk averse.
  3. Integrators help bring a team together. They care about people and the relationships within a group and prefer to make decisions by consensus.
  4. Drivers are workhorses. They value getting the job done and seeing results.

What Does This Mean For Data Science Teams?

Most team members will identify with one or two of the work styles above. It is essential to note that there is no one right work style for a data science project. The characteristics of each could be a positive or negative, depending on the situation. Individuals with any work style can come together to create a winning solution, but people with different styles often take different approaches or have different insights to solving the same problem.

Having access to different points of view can lead to more productive team collaboration. For example, an integrator may be particularly sensitive to how the group works together while a driver is focused on their individual work. By teaming these two work styles, the integrator can ensure the driver’s work is included in the final product, while the driver’s habits may motivate the integrator to provide innovative individual contributions to the solution. Everyone wins!

However, a team with different work styles can also create conflict. To work together most effectively, team members need to understand (and respect) the work styles of their colleagues. While it is often easiest to work with people of like style, you’d be isolating the team from the advantages of diversity.

Conflict arises when team members do not adapt their styles to benefit their team or fail to recognize what everyone brings to the table. For example, a guardian might stress that the new technology proposed by the pioneer is too risky. Whereas a pioneer may believe their ideas are being dismissed when the guardian highlights potential problems that might arise. Without understanding the benefits of differing points of view, both parties could come away feeling unsatisfied. One potential solution to this example would be for the guardian to propose boundaries around the time spent investigating the new technology. This prevents the pioneer from going too far down a rabbit hole while still allowing an opportunity for the exploration to bring valuable new insights to the team.

As another example, you may have experienced (or been) a driver acting as a singular force on the team essentially attempting to do all the work. Such projects rarely turn out as great as they could. The lack of respect and trust in the team shown by trying to shoulder all the work deteriorates relationships, prevent others on the team from contributing as much and learning new skills, and blocks everyone from bringing their full knowledge to the table. The act of one person trying to be the “hero” hurts the immediate project but also has a lasting negative impact on the team’s overall growth and professional development – which is a big loss for the company. However, this situation can be fixed if everyone comes to respect what is being brought by the different work styles of each member, and prioritizes working together. In this situation, an integrator sensitive to how the group interacts could help counteract the driver focused on their individual work. By teaming these two, the integrator could help facilitate opportunities for the driver to work with other team members to share knowledge as well as ensure the contributions of the rest of the team are not overlooked. These actions can enable trust to grow amongst the group. Everyone would win!

The first step in applying the knowledge of work styles is to have each team member reflect on which style(s) applies to them. Then schedule a team meeting to share which work style each member most closely identifies with. This is especially important when working together for the first time. This dialog about work styles enables members to understand how to make each member feel valued and how complimentary styles, when brought to light and planned for, can enhance team performance.

Bringing the Team Together

Once a team understands these work style dynamics, they must embrace style diversity on each project to deliver the best business outcomes for their stakeholders. Tuckman’s stages of group development is one way to conceptualize team dynamics and performance. Tuckman proposes that groups undergo the following phases as they eventually grow into a high-functioning team:


Forming occurs when the group first comes together to work on a project. The group is becoming familiar with the project itself as well as one another. It is a key objective for the group to form a common understanding of the project goals. Individual tasks are assigned and group members act independently. The team is really just a set of individuals during this stage. To progress to the next stage, each member must embrace the possibility of conflict.


The team likely experiences conflict due to differing opinions on how to approach a particular problem. In addition, natural power dynamics can easily result in another layer of conflict. Storming can occur during in a single period of time or on a reoccurring basis when new challenges arise. During this phase disagreements can potentially make individuals stronger, more versatile, and able to work more effectively as a team. To move to the next phase, it is important that the team learns what each member brings to the table in terms of work styles and skills and begins to establish trust.


Norming takes advantage of the trust built during storming. Norming encompasses both conflict resolution and the development of a team mentality—putting the goals of the team and the project before any one individual’s pursuits. Group norms are established as individuals learn to understand other team member’s tendencies and abilities. The biggest risk during this stage is that members become so averse to conflict that they suppress controversial opinions or ideas that could benefit the project.


Performing teams are highly functional and collaborate to achieve their goals. Any differences of opinion are handled in a non-storming fashion, allowing the group to quickly and effectively develop solutions. Performing groups are beyond the phase of understanding their teammates; these groups use their inherent knowledge of work styles and team dynamics to assign tasks, make decisions, and complete projects successfully together.

Teamwork Makes the Dream Work

Teams can be so much more than the sum of their parts. Take the time to get to know your teammates, pay attention to their work styles, and recognize their strengths. Keep in mind that becoming a team is a process. Every team will move through challenging times on the way to becoming a cohesive unit that effectively delivers successful solutions. It takes both time and awareness for the group to become a high-functioning team. Applying these concepts as you collaborate on your data science projects will make for a strong team that successfully navigates the demands of project work together.

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