Data-Driven Decision Making

Data-driven decision making is a critical leadership skill. The ability to leverage data to guide strategic decisions not only enhances the accuracy of these decisions but also fosters a culture of accountability and continuous improvement. Many times, we make decisions that are based on several biases, but when we let data guide us, we are likely to make the best decision for the most people. Data does not eliminate the use of our instincts – it helps us hone it for the best decisions.

Data-driven decision making involves collecting and analyzing data to guide strategic decisions. Rather than relying solely on intuition or anecdotal evidence, leaders use data to identify trends, measure performance, and predict future outcomes.

The key aspects of data-driven decision making include:

• Collection: Gathering relevant and accurate data from various sources.

• Analysis: Interpreting data to uncover insights and trends.

• Action: Making informed decisions based on data insights.

• Evaluation: Continuously monitoring and assessing the impact of decisions to refine strategies.

Not every leader will excel in all of these aspects. It’s important to understand that they all work in tandem and should all be leveraged appropriately to make the best decisions possible.

What prevents people from using data to make decisions? First, studies have shown that only about 30% of people believe the data that is shared with them, and in organizations only about 50% of decisions are made using data. We live in a time of information overload, and this makes it a challenge for many people to find the right information and when they get contradictory information, they are unsure of which information to believe.

When it comes to finding the right data, many people don’t actually know what data to look or ask for to make the decisions they need to make. When they speak with data analysists, it becomes a back and forth of “what do you have?”, “well, what do you need?” This results in people getting so much information that they don’t know how to filter, and it leads to further confusion because they didn’t know what data to ask for to start.

The key to getting the right data is identifying the right outcomes. What are you trying to accomplish? How are you going to use the data that you receive to make decisions? If I get a ton of data about my programs, that is great and how do I use this information to make my programs better?

I have the opportunity to work with an incredible ops person and she is probably the first person I have ever worked with who actually goes through the data we get in detail to make sure it is accurate and see if it was useful. She worked with the data team to make sure the data was accurate and she filtered our ask to ensure we got data we could take action on immediately.

Framework for Data-Driven Decision Making

There are a lot of different frameworks out there, especially around decision making. This is a framework that can help you capture the right details to make the decisions that lead to forward momentum.

1. Define Objectives: Clearly outline what you aim to achieve. This could be improving customer satisfaction, increasing operational efficiency, or driving sales growth. You don’t need to know the “how” yet – you will figure that out through the data.

2. Collect Data: Gather relevant data from various sources. This may include internal databases, customer feedback, market research, and industry reports. Some organizations have entire teams dedicated to this, so reach out to see how they can support.

3. Analyze Data: Use analytical tools and techniques to interpret the data. Look for patterns, trends, and correlations that can inform your decision.

4. Make Decisions: Based on your analysis, make informed decisions that align with your objectives. Consider potential risks and benefits not only for the immediate decision, but for the second and third order effects.

5. Implement Actions: Execute the decisions and monitor their impact. Ensure that your team understands their roles and responsibilities. Once we have the data and we make a decision, there is still storytelling and support that we need to garner from our stakeholders throughout the entire process. People will continue to question the data, so you will need to communicate consistently throughout the process.

6. Evaluate Outcomes: Continuously assess the effectiveness of your decisions. Use metrics and KPIs to measure success and identify areas for improvement. Just because a decision was made does not mean that there will not need to be any modifications. This is not about dramatically pivoting every time, but watching how the data evolves in alignment with your objectives and making necessary, data-driven decisions.

7. Refine Strategies: Based on your evaluation, refine your strategies to enhance future decision-making processes. This may involve adjusting your data collection methods, exploring new analytical tools, or shifting organizational priorities.

Improving Data-Driven Decision Making

• Develop Analytical Skills: Enhance your ability to interpret data by learning statistical and analytical techniques. Courses in data science, statistics, and business analytics can be particularly beneficial. You don’t have to be an expert, but you should understand the data you are looking at and how to use it when it comes to you.

• Invest in Technology: Utilize advanced tools and software for data collection and analysis. Business intelligence (BI) platforms, data visualization tools, and predictive analytics can significantly improve your ability to make data-driven decisions. We no longer live in a time when we have to sort through large spreadsheets and databases – use the technology!

• Foster a Data-Driven Culture: Encourage your team to prioritize data in their decision-making processes. This includes training staff on data literacy, promoting transparency, and celebrating data-driven successes.

• Ensure Data Quality: High-quality data is crucial. Implement rigorous data governance practices to ensure the accuracy, consistency, and reliability of your data. You may get a lot of data, but that doesn’t make it useful.

• Collaborate with Data Experts: Work closely with data scientists, analysts, and other experts who can provide deeper insights and help interpret complex data.

Reflection Questions for Leaders

Whether we use data to make decisions right now or not, we can always reflect to see how we could leverage it for better decision making and identify the thinking traps we fall into when it comes to data.

·       What types of data are most relevant to our organizational goals?

·       How do we currently collect and analyze data?

·       Are there gaps in our data that need to be addressed?

·       How can we improve the quality and accessibility of our data?

·       In what ways can we better integrate data into our decision-making processes?

·       What training or resources do our team members need to enhance their data literacy?

·       How do we measure the success of our data-driven decisions?

Embracing data-driven decision making can significantly enhance leadership effectiveness. By leveraging data to guide strategic decisions, leaders can improve accuracy, accountability, and overall organizational performance. By developing analytical skills, investing in technology, fostering a data-driven culture, and following a structured framework, leaders can harness the power of data to drive success.