How to Identify Key Team Members for a Data Analytics Project

Who are the key members of the project team? This is one of  five things that are important to know, even before the project kicks off, according to Innovative Solutions Partner co-founder Mustansir Saifuddin, who has shepherded a multitude of such projects over the past two decades. 

The success rate of projects increases by 50% when organizations invest in project management practices and establish effective project teams according to a recent study by McKinsey. 

To achieve success, the project team should consist of individuals with specific roles and expertise.

Roles and responsibilities of team members

Let’s delve deeper into each team member’s role and why they are essential for a data analytics project.

Team members with a good understanding of the architecture

To ensure the project’s success, it is crucial to have team members who possess a deep understanding of the architecture involved. This includes knowledge of tools and platforms such as SAC (SAP Analytics Cloud), Datasphere, BW4/HANA, and S4/HANA.

These team members act as the foundation for the project, providing expertise in selecting and implementing the right architecture to support data analytics initiatives.

A report by the Project Management Institute (PMI) found that organizations with highly effective project management practices waste 28 times less money than those with low practices.

Subject matter experts for different process areas

Implementing a data analytics solution often requires understanding of various process areas. For example, in an ERP implementation, experts in sales, financials, and supply chain management are vital for a successful project.

 These subject matter experts help bridge the gap between the technical aspects of the project and the business requirements. Their knowledge ensures that the implemented solution aligns with the organization’s specific needs and processes.

Technically sound front-end developers

Competent developers skilled in the relevant technologies are critical to implementing data analytics solutions effectively. For instance, expertise in SAC development ensures the team can leverage the full potential of the SAP Analytics Cloud platform. 

These developers should be well-versed in data visualization, data transformation, and building robust analytical models. Their technical acumen enables them to translate business requirements into tangible data analytics solutions.

Back-end developers who understand the business

In addition to technically sound front-end developers, having back-end developers who comprehend the business is crucial. These individuals bridge the gap between technical and functional aspects, ensuring that the data analytics solution integrates seamlessly with the organization’s existing systems. 

They possess a deep understanding of the underlying data structures, data modeling techniques, and the organization’s business processes.

Strong data modeling and data architect

Data modeling is a critical aspect of any data analytics project. Strong data modelers and data architects help design the database structure, define relationships between data entities, and optimize data storage and retrieval. Their expertise ensures that the data analytics solution can efficiently handle large volumes of data and provide accurate insights.


How to identify team members

Together with stakeholders and key organizational leaders, define the goals and objectives for the project. This will help determine the specific skills and expertise needed for the project, and will facilitate identifying the key members of the project team. 

Here are some specific elements of identifying those team members: 

Define project responsibilities

Clearly define the roles and responsibilities required for the data analytics project, such as data analyst, data scientist, business analyst, data engineer, and project manager. This ensures that the project team has a clear understanding of their roles and how they contribute to the project’s success.

Assess technical expertise

Evaluate the technical skills and expertise needed for the project, such as proficiency in data analysis tools  and knowledge of data visualization platforms. Identifying team members with the necessary technical skills ensures the project team can effectively execute the data analytics tasks.

Identify industry knowledge

Consider the importance of industry-specific knowledge in the project team. This includes understanding the organization’s business processes, industry regulations, and specific data analytics requirements. Having team members with industry knowledge helps ensure the project’s outcomes align with business needs and industry standards.

Evaluate analytical and problem-solving skills

Look for individuals with strong analytical and problem-solving skills. Data analytics projects often involve complex data analysis, modeling, and interpretation. Team members with excellent analytical skills can derive valuable insights and make informed decisions from the data.

Assess communication and collaboration skills

Effective communication and collaboration are crucial for project success. Identify team members who can effectively communicate complex data concepts to stakeholders and collaborate with cross-functional teams. Strong communication skills foster a shared understanding and enable smooth collaboration throughout the project.

Consider project management experience

Evaluate team members’ project management experience, including their ability to plan, organize, and coordinate project activities. Project managers with data analytics project experience can provide valuable guidance and ensure the project is executed in a structured and efficient manner.

Involve stakeholders in selection

Engage project stakeholders in the selection process to ensure their needs and expectations are considered. Stakeholders can provide insights into specific skill requirements and identify team members who have a good understanding of the business context.  This will help to ensure that the team’s skills and expertise align with the project’s requirements.

Evaluate team dynamics

Consider the team dynamics and interpersonal skills when forming the project team. A cohesive team that can collaborate effectively and leverage each other’s strengths is crucial for project success. Assessing team dynamics helps identify potential conflicts and ensures a harmonious working environment.

Hire experienced professionals

When building a team for a data analytics project, it is crucial to hire experienced professionals who have relevant experience and expertise. They should have a strong understanding of data analytics, cloud-based platforms, and project management.

Foster a culture of teamwork

It is important to foster a culture of teamwork and collaboration within the team. This will help ensure that the team members work well together, communicate effectively, and deliver the project on time and within budget.

Continuously monitor and adjust

As the project progresses, continuously monitor the team’s performance and assess if any adjustments are needed. This includes addressing skill gaps, addressing team dynamics issues, or considering additional resources as required.

By following these steps, project managers and stakeholders can assemble a capable and well-rounded team that possesses the necessary technical skills, industry knowledge, and collaborative abilities to execute the project successfully.

The role of the project manager

To ensure the success of the project, the identification and selection of key team members should begin during the early stages. A competent project manager and data architect play integral roles in the initial team-building process. They provide leadership, guidance, and direction to the team. Business analysts/architects with expertise in process areas act as liaisons, connecting the technical team members with the business stakeholders to ensure alignment between requirements and the solution design.

As the project progresses, additional team members such as developers and other specialists may join to contribute their expertise at different points in the project timeline.

By assembling a team with diverse skills and expertise, organizations can significantly enhance the chances of success for their data analytics projects. Each team member brings unique value to the project, and their collective efforts enable effective implementation and utilization of data analytics solutions.

According to the Pulse of the Profession 2020 report Future Focused Culture,  “It’s the leaders who can mobilize the right team members to help the company move faster and achieve results who will thrive in The Project Economy.”

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Mariyah Saifuddin