What Does it Look Like to Be a Data-Driven Organization?

Intro

Beyond being a buzzword in business, the concept of being data-driven might be one of the single most important aspects of running a successful business. If you have read many business strategy books you'll have undoubtedly have seen an adage like, "If you can't measure it, you can't make a decision based on it". Eric Ries, in The Lean Startup, emphasizes that data-driven decision making is essential to success:

"A startup should measure everything that matters, and nothing that doesn’t. This means focusing on metrics that will help you understand whether your product is growing, whether customers are happy, and whether you have a sustainable business model."

Ries dedicates multiple chapters of the book to the discussion of data collection and testing. Ultimately, he points out that without data to measure the business and guide experimentation, businesses are essentially operating in the dark. Despite the focus on startups the lessons about the use of data and testing can be applied to any mature business as well.

Making decisions based on gut instincts is a necessary part guiding a company but using your gut exclusively will hamper the success of your business. The decisions your company makes should be based on data and testing as often as is possible.

Strategic Data Collection

Some analysts might tell you to collect any events and attributes you possibly can. On the surface, this seems like sound advice. More data is better right? The reality is that this approach is rarely feasible due to resource constraints. Developer time is at a premium in any organization and analytics vendor costs can quickly get out of control if your company tries to track every user interaction. The key is to be strategic about which events you collect and ensure that you’re gathering data that will drive meaningful insights.

One of the first questions I like to ask stakeholders when they say they need some specific piece of data is: “what decisions would you be able to make if you had this data that you can’t make right now?”. Whether they have an answer or not it at least challenges them to think about the application of the data and not just collecting it “just in case someone asks for it”. What do your users really care about? What behaviors predict churn, conversions, or high engagement? Once you have laid out these key behaviors you can begin designing your data collection strategy.

In a separate post I’ll lay out some data collection strategies that will help level up your organization’s data.

Reporting Tools For Everyone

Data democratization is the concept that everyone within an organization can get access to the data they need to do their jobs and create their own insight. This widespread availability of the data is critical for making the transition to a data-driven company. Don’t be fooled into thinking that giving everyone access to a dashboard or a few reports is going to be enough. Access and training are the two pillars of a successful democratization strategy. To build a truly data-driven organization, your team must have the correct tools and the knowledge to use those tools effectively.

Everyone within your company, not just the analysts, should be able to leverage your main reporting tools to help them make informed, data-backed decisions. All departments from marketing and product teams to sales and customer support should have access to data that is relevant to their day to day operations. In light of that, choosing a reporting tool that is intuitive for non-technical users but has the flexibility that technical users need for deep querying is essential.

Access alone isn’t enough. Without proper training, employees will inevitably experience friction using the tools or draw invalid conclusions which will discourage further use and completely kill any momentum your company had towards your transition to being data-driven. In addition to the obvious topic of tool use the training should also cover how to interpret that data in a meaningful way. Employees should feel empowered to analyze the data, spot trends, and make informed decisions that align with the company’s strategic goals.

Democratization of your company’s data will lead to better faster decision-making for the entire organization and fosters a culture of transparency and accountability.

Data Discoverability

Self-service reporting enabled by the excellent reporting tool choice and companion training is only possible when the data is easy to understand. Even with the best tools, employees can find it challenging to successfully analyze the data if they don’t understand how the data is structured. Your organization needs to ensure that the data itself is accessible but also that the definitions for which events and attributes are tracked is accessible and easy to interpret. Most organizations utilize a wiki page or a spreadsheet to keep track of their data schema but both of these can be cumbersome.

Anamp is a great option for making your data more discoverable and improving your documentation. By offering visual data maps, clear schema representations, and easy search functionality Anamap makes it easier for anyone in your organization to effectively utilize your data.

The Importance of Testing

A solid testing program in your organization can not only optimize various parts of your product or service but it can also lead to some unexpected insights about your customers. In an ideal world, testing is so interconnected with your company culture that it’s easy (and expected) to test nearly every new product feature, process, marketing campaign, etc. Even complicated elements of your business such as pricing can be successfully tested to find what drives the most customer growth.

Random interjection here: I hear the marketers reading this screaming at me about brand building and slow burn effects like awareness. I concede there are some things that are very challenging to measure, especially in the short timescales typically allowed for testing so those things get a pass. However, just because they are difficult to A/B test or measure doesn’t mean it’s not worth trying.

Testing fosters a mindset where assumptions and opinions are challenged, hypotheses about your customers are formed, and data provides the final verdict. Without methodical testing businesses are essentially throwing pasta at a wall in the dark trying to figure out what stuck. Each experiment (AKA test) provides valuable insights that either confirm your hypotheses or reject them which can ultimately lead your organization down a new path of discovery and understanding; you won’t just know WHAT works better you will begin to understand WHY it works better too.

Bringing Data to the Table

In meetings, decisions are often made based on opinions, past experiences, or intuition. These perspectives aren’t without value in a data-driven organization, but decisions should be backed by evidence whenever possible. Bringing data to the table doesn’t mean eliminating opinions, it just means those opinions should be supported with hard facts and insights. When stakeholders come to the table with statements supported by data the discussions are more productive and less frequently devolve into arguments based on pure speculation. Instead of debating subjective viewpoints, teams can focus on interpreting the data and understanding what it conveys about the business problem.

For example, let’s say you’re in a product meeting, and someone suggests a feature change to improve user engagement. Rather than simply moving forward based on intuition, a data-driven approach would involve gathering data from past user behavior, analyzing patterns, and even running small-scale tests to validate the assumption. This process not only reduces risk but also builds confidence that decisions are based on reliable information.

Bringing data to the table can become a powerful tool for alignment and keeps everyone on the same page with a clear understanding of why specific decisions are made.

Summary

Being a data-driven organization means making decisions grounded in data rather than gut feelings or assumptions. By strategically collecting the right data, providing everyone with access to reporting tools and training, making data easily discoverable, fostering a testing culture, and ensuring meetings are supported with analysis, your company will be well-equipped to succeed in today's fast-paced business environment. It’s not about turning every decision into an equation—it’s about creating a culture where data enhances every decision your business makes.