The title of the article, which reads “Strategies to Build a Culture of Data-Backed Decision-Making.”

Strategies to Build a Culture of Data-Backed Decision-Making

Anyone can see why adding data to the decision-making process is worthwhile. By establishing credibility and unifying collaborators, data informs you to take the next step with confidence, whatever that may be.

However, having data-backed decision-making become second nature in your organization can pose a challenge, especially if you’re unsure of which insights to prioritize. Not to mention, unorganized, missing, or dirty data can stall your progress or lead you down the wrong path.

To strengthen your organization’s informed decision-making, we’ve compiled a list of five strategies you can employ to back your ideas with solid evidence.

1. Lead by example

When your organization’s leaders set an example, the rest of the team will likely follow suit. Start at the top of your organization to explore ways your leadership can set the tone for following evidence-based strategies. A few leadership techniques could include:

  • Setting a regular cadence of reviewing organizational performance metrics to remind teams of what metrics to go after, what healthy results look like, and how to navigate any lacking or surprising results.
  • Sifting through case studies before finalizing decisions to allow previous insights to guide your strategy. This could mean diving into studies your organization has conducted or reviewing relevant ones within your industry.
  • Reviewing evidence-based action plans to ensure you have informed each step of your process with relevant data. For comprehensive action plans, this would mean citing multiple sources and proactively explaining any gaps.
  • Offering data research and presentation best practices from leadership’s expertise. Give tips and strategies for presenting data and research in a way that is both compelling and relevant for your audience.

These strategies should be unique to your company’s needs and objectives. For example, a healthcare organization may set expectations to review the risk adjustment process with new employees so that they understand the workflow and compliance requirements. According to Arcadia, this may mean breaking down each step to accurately suspect, engage, and assess patient needs while maintaining quality standards.

2. Provide data literacy training

While data is a useful tool for decision-making, it can sometimes be tricky to interpret, especially when gathering actionable insights from specific data points. Ensure everyone has the needed level of data literacy training to manage your organization’s data. Explore the following:

  • Hands-on data analysis projects related to team members’ roles, allowing them to explore and analyze data independently.
  • Peer-to-peer learning sessions where team members from various departments can collaborate and share their best practices.
  • External training opportunities, such as workshops or conferences, that provide team members with opportunities to learn more about data analysis.

By offering training and collaboration opportunities, your entire team will be on the same page when approaching various decisions. Additionally, you should avoid sequestering your data science team from the rest of the organization to ensure transparency across the team. Instead, make sure they are heavily involved in explaining any process or system updates and catching any new team members up to speed.

3. Offer secure data access and management

Although the majority of your team could benefit from data-backed decision-making, it’s important to safeguard sensitive information by ensuring it’s only viewed by authorized team members. Offer secure data access and management by employing the following strategies:

  • Leverage integration: Disorganized data lacks both efficiency and security, since it’s difficult to find and may be accessible by unauthorized parties. Convert your data to a digital format and aggregate it into a central location to keep it secure. For example, a healthcare organization might consolidate patient data by leveraging EHR integration.
  • Provide data security training: Set up a series of meetings or an official training program to cover basic security principles with your team. This may include tips on how to create strong passwords, identify phishing scams, and update software. You might also offer hands-on training through simulations to help your team put these tips into practice.
  • Use clear data access controls: Employ strict access controls to ensure only authorized users can access sensitive data. For example, you may use multi-factor authentication (MFA) or biometric authentication to verify a team member’s identity before allowing them access. You can also implement logging and monitoring mechanisms to keep an eye on who accesses this information.

Beyond implementing controls on which team members have access to specific data, you can also protect the organization’s information by determining which data sources are most relevant for certain team members. Consolidating data provides a comprehensive overview of your organization’s most important information.

This way, you’ll be able to build data-backed, team-based workflows so each department can access the data they need without sacrificing security. Just be sure to identify any incomplete or missing data before you finalize any workflows. If needed, request a data append to fill in any gaps.

4. Define clear objectives and KPIs

To reinforce a culture of data-backed decision-making, your organization must build its overall goals around relevant metrics. Double the Donation’s nonprofit marketing guide recommends using the SMART method to create specific, measurable, attainable, relevant, and time-bound goals. Then, you’ll have a clear plan for how and when you’ll achieve these goals.

Enforce a coordinated effort to leverage data in decision-making by aligning these data-backed goals across departments. A few ways you can do this include:

  • Encouraging collaboration: Enable teams to collaborate on projects by sharing relevant data and insights.
  • Establishing Key Performance Indicators (KPIs): Develop KPIs for each team that support the organization’s overarching goals. Track them regularly and share progress across the entire team.
  • Implementing data-backed performance reviews: Use KPIs to track team performance and acknowledge team members who go above and beyond.

A collective effort to achieve goals based on actionable data will not just enhance your organization’s culture. Equipped with clear goals and the support needed to accomplish them, your team can work cohesively toward the success of the organization.

5. Provide relevant resources and support

While you may have an organized approach to data collection, you should also leverage relevant resources to simplify decision-making for your team. Consider the following ways you can support data-backed decisions:

  • Leverage knowledge-sharing platforms: Enable team members to access tutorials, case studies, and best practices through internal knowledge-sharing platforms.
  • Use analytics: Allow your whole team to access analytics tools to collect data analysis from various perspectives.
  • Continually improve the process: Regularly evaluate and improve your organization’s data processes and practices. Ask for feedback from team members to determine data needs and address challenges.

An organization’s team can only employ data-backed decision-making when they’re equipped with the right resources and support. In addition to these tools and resources, provide data quality assurance so that team members can work with consistent and reliable information.

An organizational culture that encourages data-backed decision-making benefits not only your organization as a whole but also your individual team members. With enhanced collaboration and greater technical skills, your team will produce better organizational results.

Embrace data to drive innovation and growth relevant to your organization’s objectives, and establish clear expectations for team members to support this strategy. Where possible, explain the importance of data in team members’ roles to transparently implement data-driven processes. Prioritize data across your entire team for better results in every initiative.