Business Tips | Data Strategy

For many people, the term “data scientist” is easy to associate with phrases like “charts,” “graphs,” and “crunching the numbers.” While a big part of data science involves just that, some aspects of the job are anything but scientific – including teamwork. According to studies, even perceived collaboration can increase the performance of a team. This is true in virtually any professional environment, but especially those involving data.

The reason for this is twofold. For starters, data is important. It connects organizations with their goals and serves as a compass to help individuals, teams, and companies reach those objectives. Subsequently, the data needs to be accurate. It needs to be clean and consistent. Without teamwork, consistency is difficult to achieve. With proper communication, though, data scientists and their teams can work together seamlessly to create a single source of truth for their organizations.

What does a data science team look like?

Data Science Team

Regardless of how your company is structured, the first step toward collaboration on your team is well-defined roles. Every organization is different, but some of the most common data-defined roles include:

  • Data Scientists
  • Data Engineers
  • Analysts
  • Business Intelligence Experts
  • Software Engineer
  • Coordinator / Project Manager

Defining roles goes beyond job titles; you’ll also need to delineate responsibilities, too. Determine who owns which piece of your project and make sure everyone understands their unique contribution to it. Conversely, each member of the team should understand the responsibilities of their peers. This way, everyone knows where to go for the information and solutions they need in the event of a challenge or roadblock.

Ask yourself the following questions when defining your team structure:

  • Who is sourcing the data?
  • Who is manipulating and prepping it?
  • Who is responsible for cleaning up the data?
  • Who will prepare it for final presentation?
  • Who is responsible to manage the overall project?

Additionally, outline micro-partnerships within the team. By creating a “buddy system” that encourages members to work together, you will establish a professional (and personal) framework that supports overall team collaboration.

Start Every Project with a Question

Start Data Projects with a Question

Collaboration starts with questions, and the first question your team should strive to answer is “What’s our objective?” Next, brainstorm the questions related to that objective and begin answering them as a team. During this phase, you’ll not only help your team understand their objectives but foster an immediate sense of collaboration – one that will carry through the duration of the project. In this initial meeting, encourage everyone to contribute. Make sure they feel comfortable sharing ideas and build trust by validating their individual perspectives. With trust, your team will be more comfortable sharing ideas that seem “outside the box.” Often, these ideas are the kind that lead to innovative problem solving and solutions.

Once you have an idea of your larger goal or “question,” begin breaking it into bite-sized pieces (sub-questions). Then refine these questions into measurable factors. These factors should relate to and support the overall goal while focusing on just one facet of the project. Most importantly, you should be able to attach them to specific, actionable metrics.

Data Teamwork is for Everyone, Not Just Your Immediate Team

Teamwork is for everyone

Collaboration should extend beyond your nuclear team. Specifically, you’ll need to define and communicate with stakeholders. While teambuilding efforts should be largely focused on those responsible for the project, it’s important to understand the best ways to communicate the data you’re working with, along with who to communicate it to.

The questions below can help you understand how to best reach stakeholders with your data:

  • Who needs the data? What specific metrics do they need?
  • Should the data be text-based or does it merit a dynamic dashboard?
  • What context does the audience need to understand the implications of each metric?
  • What is the most important metric? What sub-metrics do you need to support it?

Read next: How to Improve Your Team’s Productivity (Without Compromising Quality and Efficiency)

Take Advantage of Collaboration Tools and Software

Data teamwork and collaboration

There are a myriad of apps, plug-ins, and tools you can use to support team collaboration. The most important thing is to ensure everyone on your team is using the same communication, organization, and management platforms. It might seem like a no-brainer, but the sheer volume of options available can make it easy for individuals to get stuck in the “rut” of their own productivity tools. The key is finding one that works for everyone and implementing it universally. Some of the most common (and helpful!) collaboration tools include:

  • Project management software
  • Organization software
  • Instant messaging and chat apps
  • Online storage hubs
  • Team discussion boards or Wikis
  • Shared documents

Don’t be afraid to experiment and find the tools that work best for your projects. If a better option comes along, simply switch over and use it moving forward. Just make sure you provide training so everyone on your team knows how to use each tool and sees the value in using them.

Practical Ways to Foster Communication on Your Data Team

  • Make space for everyone’s ideas
  • Encourage team members to understand each other’s communication styles
  • Foster trust between yourself and your team
  • Reward outside-the-box ideas
  • Set aside time for your team to work together (brainstorming sessions, etc.)
  • Be creative and encourage your team to follow suit
  • Encourage honest communication and open collaboration
  • Work from a single source of truth (a centralized data set)

It’s Not Always About Work Stuff. It’s About the People.

Data Teamwork People

At the end of the day, your team is isn’t defined by the job titles each member holds; it’s defined by the people. Sure, projects require hard work – but it’s important for your team to communicate on the personal level too. Foster a sense of unity by getting to know them and encouraging them to do the same with each other.

True collaboration happens when individuals with unique skills and perspectives come together to reach a common goal, and it’s the job of any team leader to make sure collaboration is not only encouraged, but firing on all cylinders.

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Jenna Ryberg Human Resources Director @iDashboards

An iDashboards employee since 2009, Jenna Ryberg has extensive experience within accounting and HR, and has been the driving force behind the iDashboards Conferences.


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