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Assemble an Effective Cross-functional Data Team Featured

Assemble an Effective Cross-functional Data Team Simon Kadula

As the world and businesses become increasingly data-driven, data quality is critical in making informed decisions. This means that the right people must be put in place to collect and analyze data for better decisions. Having a cross-functional data quality team is the first step in the right direction in achieving this. The right team ensures that the data collected, processed, and analyzed is accurate, complete, and relevant to the organization’s goals and objectives. However, if you have worked in a cross-functional team before- that is, a team that brings together individuals from different departments and areas of expertise- to collaborate and deliver high-quality data, you already know how challenging it can be to put together is not easy. Here is what a cross-functional team is and how to set up a good one for your organization.

What Is a Cross-Functional Team?

Simply put, a cross-functional team involves individuals from different departments or functional areas within an organization coming together to work on a common project or goal. These individuals have different skills, experiences, and perspectives, which gives them a unique opportunity for collaboration, innovation, and problem-solving. In the context of data quality, a cross-functional team is tasked with ensuring that the data that the organization uses is accurate, reliable, and meets the business goals.

How do you Set up a Cross-Functional Team?

Setting up a cross-functional data quality team is not an easy task. It requires some dedication and skill and involves several steps. Some steps that should be considered include:

  1. Determining the team’s objectives and scope
  2. Identify the necessary people or stakeholders from different departments and areas of expertise that will be part of the cross-functional data team.
  3. Assign a team leader to the team, whose work will be to lead the team and ensure that the organization’s and team’s objectives are met.
  4. Establish clear roles and responsibilities for each member.
  5. Establish methods and mechanisms for regular communication and collaboration, such as regular meetings and progress reports to ensure that each member works towards the common goal.

Challenges of Cross-Functional Teams

While developing a cross-functional team can be easy, they are not without its challenges. Some of the common challenges include:

  • Team members might have different perspectives and priorities
  • Coordinating and communicating among members from different departments and areas of expertise can be difficult.
  • Resistance to change among team members.

The cross-functional approach to handling data and how it looks within an organization

A cross-functional data quality team brings together individuals from different departments and areas of expertise, enabling them to work together towards a common goal. These individuals will collaborate to establish data quality standards, processes, and metrics and monitor data quality to ensure that it meets the company’s goals.

Benefits of cross-functional data planning

Some of the benefits of having a cross-functional data quality team include the following:

Improved data quality

Bringing together individuals from different areas of expertise means that the cross-functional team can identify and address data quality issues sometimes overlooked by a single functional area or department.

Increased collaboration and communication

Collaboration and regular communication among people from different departments and expertise help to resolve issues more efficiently within a team. It also increases productivity and builds strong relationships.

Better decision-making

The main reason for building a cross-functional data team is to ensure that the collected data is used to make better decisions. Accurate and reliable data is necessary for better decision-making, and a cross-functional team is better positioned to ensure that the data is high quality.

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

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