5 factors that make your data team successful

With the value of data lying in its potential to generate business insights, 2 questions jump to mind. First, what are the steps to create long-term value from data? And second, what makes a data team succeed? Over the years, we at Datashift have worked closely with many clients to create long-term value using their data. In the process, we've identified 5 factors essential to making data teams successful.

1. An agile way of working

Your data team needs to work efficiently. Period. Rather than sticking to more traditional waterfall methods, apply agile project management principles such as working in two-week sprint cycles, preferably supported by a tool like Jira. Don't try to capture all requirements before developing the solution to a business problem. Just iterate quickly and improve your data products incrementally. That will make it possible to remain in touch with the business, focus on what’s most important and reduce lead times. And most of all, the work of your data team will immediately impact the business.

2. Focus on business impact

If you want to keep your data team relevant, your primary focus should be building data products that impact the business. Whatever your data team builds, it should always increase revenues, reduce costs, or mitigate risks. Building something complex and performant doesn't make sense if it doesn't solve a business problem or help the business achieve its goals.

3. Great relationships

Don’t underestimate the importance of having great personal relationships with all people interacting with your data team. Make sure you get along personally with both the consumers of your data products and the owners of the source systems that feed your data platform. What keeps them awake at night? What are their professional ambitions? If you aim for the best possible collaboration, it is vital to understand their needs, problems, and priorities and to speak their language.

4. A well-designed platform

This factor might be the most obvious one. Your data team needs a well-designed, performant data platform that suits your current needs and, preferably, your near future needs. It should be clear to all data team members which components are used for which purpose and how to prevent your architecture from becoming an unmanageable patchwork. A minimum set of documentation, best practices, naming conventions, …, will keep the house tidy and all data team members happy.

5. An exciting roadmap

We all need things to look forward to as reference points on our horizon. Your data team is no exception to that rule. Try to satisfy that need by developing a long-term roadmap with energizing topics, ambitious goals, and impactful projects. If you stick to day-to-day operations and merely pick up one request after the other, you will sooner or later end up in a reactive mode instead of a proactive one. Even worse, the stream of requests might dry up one day. Your data team should, therefore, not only deliver data products requested by your data consumers. You should also sell potential data products, as your data team often has the best view of the hidden value within the available datasets.

So where does your data team stand?

You’ve recognized some areas where your data team can improve, but you're unsure how to address them? Let us help you by bringing our experience on board to move forward together.