Strategies for Building a Highly Efficient Analytics Team

Strategies for Building a Highly Efficient Analytics Team

A strong analytics team can mean the difference between mediocre insights and a significant competitive advantage. However, putting together an analytics team is not something that can be done overnight. Bringing together the right people with the right mix of skills takes time and effort.

What happens when a company adopts the most cutting-edge data analytics tools but fails to establish a top-notch analytics team? A lot of missed opportunities, and a waste of time and money.

One of the biggest challenges for companies is not the collection of the data itself, it is building a team that will apply the data and drives change throughout the organization. It’s never been more difficult to build and maintain a successful team than it has been in the previous 18 months. It is, however, possible. Here are a few best practices to keep in mind.

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Meaningful work and modern, effective tools

Top-tier data analysts must have the tools and data they need to be successful. They must also be given significant tasks. No data analyst wants to be a part of a team whose work has no impact on the company’s bottom line. This entails picking projects with a significant impact. This is easier said than done, yet it is critical to the development of a trustworthy data analyst team. Furthermore, members of the team must be shown how their work contributes to the world at large.

Internal training programs

Data analytics professionals are in short supply, and competition for these skills is fierce. Companies with the resources should consider providing training and continuous learning programs to help develop in-house talent. They can incorporate both internal and external programs. Mentorships or bringing together cross-functional teams to share experiences and information can also be part of these training programs.

Projects provide an opportunity for cross-functional teams to collaborate. It is worthwhile to spend the money to hire a few junior members so that they can gain experience and learn how things work outside of their own organization. It’s also a good idea to rotate individuals across tasks so that they don’t get bored or comfortable in one area.

Diversity is crucial

Many companies are focusing on workforce diversity these days, and data analytics teams should be a part of that endeavor. This encompasses a wide range of employment experiences.

Corporate leaders should put together a group of people with a variety of professional backgrounds. This method results in a team with all of the necessary skills to solve a wide range of challenges. Even if no one person in the team can solve every problem on their own, the end result is a stronger team with people who can learn from one another and handle a broader range of problems collectively.

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Engaging with people across the organization

The analytics team isn’t supposed to work in silos. Interaction with others around the company allows the team to stay on top of business goals and get a better insight of what matters to a diverse group of co-workers. It also allows team members to communicate the value of analytics to others in the company.

By bringing together analysts and business users, leaders can establish a learning environment while also improving the business process and speeding up the outcomes. A lot of time can be lost in communication or trial-and-error development if an analyst understands the data in its raw form but does not grasp the business needs or the specific data sets required to arrive at a solution.

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Prangya Pandab is an Associate Editor with OnDot Media. She is a seasoned journalist with almost seven years of experience in the business news sector. Before joining ODM, she was a journalist with CNBC-TV18 for four years. She also had a brief stint with an infrastructure finance company working for their communications and branding vertical.