In the fast-paced world of Agile, decision-making can often feel like a daunting task. How do you know if you’re on the right track? How can you ensure that your product delivers value while staying competitive? This is where Evidence-Based Management (EBM) comes into play. By leveraging data to drive decisions, EBM helps organizations make informed choices that align with their goals.
In this blog post, we’ll explore the fundamentals of Evidence-Based Management, focusing on its four key value areas, how to collect and analyze data, and how this process leads to more successful outcomes. Whether you’re a Scrum Master, Product Owner, or manager, this guide will show you how EBM can elevate your decision-making process.
EBM revolves around one simple principle: data-driven decisions. Gathering, analyzing, and acting on data allows teams to adjust their strategies based on real insights. By using evidence rather than gut feelings, organizations can stay focused on delivering value to their customers.
In EBM, there are four key value areas that serve as the foundation for data collection and decision-making:
Current Value (CV): How much value is your product delivering to customers today?
Unrealized Value (UV): What potential value can be unlocked by adding new features or improvements?
Ability to Innovate (A2I): How effectively can your organization innovate and deliver new features?
Time to Market (T2M): How quickly can you release new features or products to market?
For any team practicing Agile or Scrum, focusing on these value areas ensures that you’re continuously delivering the right value to your customers, while staying nimble enough to innovate and grow.
Once you understand the four key value areas, the next step is gathering data. Each area provides a unique lens to look through, offering insights that can drive your next steps.
This metric is all about understanding how well your product meets customer needs. To gather data here:
Customer Satisfaction Surveys: Are customers happy with your product?
Feature Usage Data: Which features are most used, and which are ignored?
Defect Trends: Are you seeing fewer bugs over time?
Personal example: I worked with a team that regularly measured customer satisfaction through surveys and support tickets. When we noticed a significant drop in satisfaction, we knew we had to focus on improving certain key features. We used this data to prioritize our backlog and saw customer satisfaction improve over the next two sprints.
This value focuses on potential features or improvements that could provide more value in the future.
Customer Feedback Interviews: What features do customers wish your product had?
Market Research: What gaps are competitors filling that you’re not?
Consider tracking these metrics through interviews or even direct customer interactions. One team I worked with was consistently rated highly by users, but when we dug into feedback, we found there were opportunities to create entirely new features that customers wanted, helping us identify unrealized value.
The ability to innovate speaks to your team’s capacity to generate new ideas and implement them quickly.
Innovation Rate: What percentage of your time is spent on innovation versus maintenance?
Technical Debt: Are you spending too much time fixing bugs instead of creating new features?
For example, tracking technical debt can give you a clear view of whether you’re allocating enough resources to new product development versus fixing existing problems.
Speed is often crucial in today’s market, so understanding how long it takes to release new features is critical.
Lead Time for Changes: Measure how quickly you can implement a new feature from idea to release.
Cycle Time: How long does it take for a feature to go from development to live?
Personal advice: In one organization, we focused heavily on reducing our cycle time by implementing continuous integration. This allowed us to identify bottlenecks and make process improvements, ultimately reducing our time to market by 40%.
Collecting data is only the first step. The true power of Evidence-Based Management lies in analyzing that data to inform your decisions.
Data tells a story, but it’s up to you to interpret that story. Let’s say your customer satisfaction is dropping. Before jumping to conclusions, look at other data points:
Is technical debt piling up?
Is your innovation rate too low?
It’s important not to overreact to a single data point but to look at the bigger picture. Data informs but does not control your decisions.
Take, for example, a team I coached. We noticed a high number of defects popping up after each release, which could have led us to increase testing time. But instead, by looking at usage data, we realized customers weren’t even using the affected features. We prioritized fixing only critical bugs and used the saved time to focus on innovation.
Real-time data, such as usage telemetry, can be a game-changer. Knowing how customers interact with your product in real time allows for quick adjustments.
For instance, I worked with a car manufacturer that collected telemetry data from vehicles. When they saw how often a certain feature was being used, they were able to make rapid improvements based on actual user behavior. That’s the kind of agility Evidence-Based Management enables!
Here are some popular tools that can help you collect and analyze data effectively:
Power BI: Excellent for creating visual dashboards that give you insights into your product and processes.
App Insights: Ideal for collecting telemetry data on how users interact with your features.
Google Analytics: Great for web-based products to track user behavior and feature engagement.
Excel: Don’t underestimate the power of a simple spreadsheet to track trends over time.
Remember, data doesn’t have to be complex to be useful. Sometimes, tracking metrics in Excel or using lightweight tools can provide all the insights you need to make informed decisions.
If you’re not already using Evidence-Based Management in your organization, now is the time to start. By gathering and analyzing data across the four key value areas, you can make more informed, impactful decisions that drive both innovation and customer satisfaction.
Start small: Begin by gathering data in one or two value areas.
Use the right tools: Power BI or even Excel can help you visualize your data.
Make data-driven decisions: Let the evidence guide your next steps, but remember that data informs—it doesn’t control.
Evidence-Based Management isn’t just a methodology; it’s a powerful way to stay ahead of the competition and continuously improve. As a Scrum Master or Product Owner, embracing this approach will help you build better products, improve customer satisfaction, and ensure long-term success.
Start gathering your data today, analyze it, and use it to propel your team towards success! 🚀
If you've made it this far, it's worth connecting with our principal consultant and coach, Martin Hinshelwood, for a 30-minute 'ask me anything' call.
We partner with businesses across diverse industries, including finance, insurance, healthcare, pharmaceuticals, technology, engineering, transportation, hospitality, entertainment, legal, government, and military sectors.
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