Building a data team from scratch is no small feat, and it comes with a host of challenges. Not only do you need to find the right people with the right skills, but you also need to build a culture of collaboration and data-driven decision-making. However, perhaps one of the most difficult challenges is dealing with new people joining the company who only see what you haven’t done compared to what you have done. In this blog post, we will explore the challenges of building a data team from scratch and offer insights into the importance of continuing to prove business value.
One of the biggest challenges of building a data team from scratch is finding the right people. You need to find people who not only have the technical skills to work with data, but also the soft skills to collaborate with others, communicate effectively, and translate data insights into actionable recommendations. Additionally, you need people who are passionate about data and who will go above and beyond to ensure that the data team is successful. Finding the right people can be time-consuming and difficult, but it’s essential for building a successful data team.
Another challenge is building a culture of collaboration and data-driven decision-making. Data teams are often siloed from other parts of the organization, which can lead to a lack of communication and collaboration. To overcome this challenge, data leaders must work to create a culture where data is shared across the organization and used to inform decisions. This requires not only technical skills but also strong leadership and communication skills to advocate for data-driven decision-making across the organization.
Here are three ways a data team can improve collaboration with the rest of the business, along with an example for each:
- Involve stakeholders in the data analysis process:
One of the most significant challenges for a data team is ensuring that the insights they generate are relevant and actionable for the rest of the business. One way to improve collaboration is by involving stakeholders in the data analysis process. This can include soliciting input from other teams, seeking feedback on findings, and collaborating on recommendations. For example, a data team working on a customer segmentation analysis might involve representatives from the marketing and sales teams in the process to ensure that the resulting segments are useful and actionable.
- Create dashboards and reports that are easy to understand:
Another way to improve collaboration is by creating dashboards and reports that are easy to understand for a non-technical audience. This can help other teams better understand the data and insights, and how they can be applied to their work. For example, a data team could create a dashboard that visualizes website traffic data and makes it easy for the marketing team to identify trends and patterns that they can leverage in their campaigns.
- Educate the rest of the business on data literacy:
Finally, data teams can improve collaboration by educating the rest of the business on data literacy. This includes teaching them about key data concepts, best practices for using data, and how to interpret data visualizations. This can help other teams become more self-sufficient and better equipped to work with data. For example, a data team might run a training program for the sales team to help them better understand how to use customer data in their sales pitches.
When new people join the company, they may only see what you haven’t done compared to what you have done. This can be frustrating for data leaders who have put in a lot of work to build the data team.
They may identify gaps in your data strategy that you haven’t considered or have ideas for new projects that can drive business value. It’s important to listen to their ideas and collaborate with them to build a stronger data team.
One way to overcome the challenge of new people only seeing what you haven’t done is to continue to prove business value. Data teams must demonstrate their value to the organization by delivering actionable insights that drive business outcomes. This requires a focus on identifying the key business problems that data can solve, and then using data to drive solutions to those problems. Data leaders must work with stakeholders across the organization to identify these problems and develop data solutions that will drive real business value. By consistently demonstrating the value of the data team, new people will see the potential for data-driven decision-making and become advocates for the data team.
Building a data team from scratch is a complex and challenging process. However, by focusing on finding the right people, building a culture of collaboration and data-driven decision-making, and continuing to prove business value, data leaders can build a successful data team. While new people may only see what you haven’t done compared to what you have done, it’s important to remember that they bring fresh perspectives and new ideas that can drive the data team forward. By collaborating with new people and consistently demonstrating the value of the data team, data leaders can build a strong and successful data-driven organization.