Mastering Evidence-Based Management in Agile: Inform, Don’t Control

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5 minute read

What is Evidence-Based Management?

Evidence-Based Management (EBM) is the strategic use of data to inform decision-making processes at both the strategic and tactical levels of an organization. It’s about using data as a guide—not a dictator—to shape behaviors and drive outcomes that benefit your business.

In essence, it’s not about letting numbers rule your every move; instead, you gather data to inform your actions and understand the behaviors that impact the results. Let’s dive into how EBM can transform your approach to management and decision-making.


Why Data Matters (But Shouldn’t Control)

Data informs behaviors. The way you measure your team’s performance has a direct impact on how they behave. Ever encountered someone in your organization who seems to be working against the team’s goals or is less engaged than expected? 🤔 Often, it’s not a personal issue—it’s about the metrics they’re being judged on.

Here’s Why That Happens:

  • Metrics and measures often influence individual behaviors.

  • People respond to the metrics that are used to evaluate them.

  • Understanding these metrics can help you see why a person or team acts in a particular way.

Pro tip: If you notice a team member’s actions aren’t aligning with your expectations, dig into the metrics they are held accountable for. It can provide clarity on why they behave the way they do.


Using Metrics to Drive Positive Outcomes

Step 1: Define Your Desired Outcomes

Before diving into metrics, you need to establish what outcomes you want to achieve. Here are some common business outcomes you might aim for:

  • 📈 Increased revenue

  • 💡 Enhanced value delivery to customers

  • 💵 Cost savings

  • 🚀 Expanding market capabilities

Without a clear understanding of your desired outcomes, it’s challenging to select metrics that guide your organization in the right direction.

Step 2: Identify Metrics That Measure Progress

Once you have your outcomes defined, the next step is to identify metrics that can help you measure progress towards those goals. These metrics can be either:

  • Leading indicators: Metrics that predict future outcomes.

  • Lagging indicators: Metrics that show the results after the actions have been taken.

Example of a Useful Metric

Let’s say your organization is running a live service and you want to minimize service outages. A valuable metric might be:

  • Number of live site incidents that exist for longer than three sprints.

By tracking this, you can monitor whether issues are being resolved promptly and identify any trends. For instance, if most teams resolve issues quickly but one team struggles with incidents lingering beyond six or seven sprints, it’s a flag to investigate further. 🚩


Informing Decisions Without Over-Controlling

One of the key tenets of EBM is that data should inform, not control. Metrics provide signals, not absolute truths. For example, if you notice a team lagging in clearing incidents, it’s not always a sign of failure. It’s a signal that calls for deeper exploration.

A Real-World Scenario

Imagine a team has unresolved incidents beyond the typical three-sprint window. This doesn’t automatically mean they’re underperforming. They might be:

  • Waiting on actions from a third-party they have limited influence over.

  • Dealing with external dependencies that are slowing down their resolution process.

In such cases, the team might be doing everything right—chasing the issue, applying pressure, and keeping it on their radar—but progress is slow due to factors outside their control. 📅

The takeaway? Data informs but doesn’t dictate. Use it as a conversation starter to understand the challenges your teams face.


Making Data-Driven Decisions: A Balanced Approach

The Process of Evidence-Based Decision-Making

  1. Collect Data: Gather quantitative and qualitative data from your teams.

  2. Analyze the Metrics: Identify patterns, trends, and anomalies.

  3. Ask Questions: Use the data as a basis to ask deeper questions about what’s happening.

  4. Make Informed Decisions: Apply your findings to make decisions that align with your desired outcomes.

Why Metrics Have Gaps (And How to Bridge Them)

Data doesn’t always tell the whole story. There will be gaps and unknowns. The key is to extrapolate from what you do know and make informed assumptions about the rest. Think of it like putting together a puzzle—sometimes, you need to infer the missing pieces.

Practical Tips for Implementing EBM

  • Create a dashboard to track key metrics for your teams.

  • Review metrics regularly to spot trends early.

  • Engage your teams in the process, allowing them to understand how their work impacts the metrics and outcomes.


Transforming Your Organization with Evidence-Based Management

The Benefits of EBM

By adopting an evidence-based approach, your organization can enjoy several benefits:

  • 🚀 Better alignment between strategic goals and day-to-day actions.

  • 💬 Improved communication as data becomes a common language for decision-making.

  • 🎯 Focus on value rather than arbitrary targets, leading to more meaningful progress.

  • 🧠 More empowered teams, as they understand the rationale behind decisions and can adapt their actions accordingly.

Personal Advice from the Field

As a Scrum Trainer, I’ve seen firsthand the transformative power of EBM in organizations. It’s not about hitting a specific number every time—it’s about using data to guide meaningful conversations and adjust your course when needed.

Remember, it’s okay if the data doesn’t always tell you what you want to hear. 📊 It’s a tool to help you get closer to your goals, not a measure of your worth or your team’s value.


Final Thoughts: Using Data to Inform, Not Dictate

Evidence-Based Management is all about balance. You want to leverage data to improve your organization’s outcomes, but without letting those numbers control your every move. Focus on the bigger picture:

  • Define your outcomes clearly.

  • Choose metrics that align with those goals.

  • Use data to inform—not dictate—your decisions.

By following this approach, you can create a culture where data is a trusted advisor, not a demanding boss. This shift can lead to better decisions, more engaged teams, and ultimately, greater value delivery for your customers. 🚀 Now, go forth and let data be your guide—not your master!

Evidence-based management is the application of evidence-based practices at the strategic and tactical levels in an organisation. It involves using data to inform but not control the actions and behaviours that have been shown to impact outcomes. So what that means is that we’re going to collect a bunch of data within the organisation. The way we measure people informs the way they behave. So whenever you’re working within an organisation and you find somebody’s working against you or somebody’s not being as involved as you think they should be involved, and you’re wondering why, there’s probably some organisational measure or metric something being levied against them that enables, ensures, encourages that behaviour in that person.

So the best way to figure out why somebody is doing something in a particular way that maybe you feel has a negative impact on the way your things need to happen is to figure out how they’re measured. That can be difficult, but if you can glean that information, you can figure out why they’re behaving the way they’re behaving, why they’re taking the actions that they’re taking. We want to try and have more behaviours and actions that impact our outcomes positively. We want to deliver more value to our customers.

What other outcomes might your business want? Well, they might want more revenue. They might want more value for their customers. They might want to save money. What else might be good impactful outcomes for our business? We might want to increase our capability within a particular market. It’s difficult without a specific instance to have a specific outcome that you’re trying to achieve.

Once you’ve figured out what your outcomes are, you need to figure out what metrics are going to help you measure progress towards those outcomes. These can be super tactical things that help you move towards those outcomes. It can be leading or lagging measures; there’s all kinds of things that come into that. But evidence-based management is that application of practices within the context of that data to help you make decisions.

One of the reasons I very specifically said inform but not control is that the data is not always going to result in a specific action. For example, let’s say I had a metric for my team or teams. I’ve got a group of teams I’m working with, and my metric is the number of live site incidents that last or exist for longer than two sprints—let’s call it three sprints. We’re running a live service; we’re going to have outages and issues and things that happen in the live service. When those things happen, we’re going to create live site incidents or live site incident mitigating actions—things we’re going to change in the product in order to not have that type of live site incident happen again.

So we’ve done our analysis, we’ve come up with these ideas, and then we expect our metric to be that we expect teams to clear those off within three sprints. If I expect them to clear it off within three sprints, I maybe want to have a measure, a team dashboard, and I’m going to have a measure that says what is the number of live site incidents that have been existing for longer than three sprints and what is the trend of that number. Is it trending up or is it trending down?

You may see your list of teams, and you see the numbers, and they’re all good apart from this one team that has these four outstanding live site issues that have been there for longer than, let’s say, six or seven sprints. That doesn’t mean there’s something wrong in that team. These are indications, these are flags, pieces of evidence that you use to inform your decision-making. So you’ll probably need to go ask them how it’s going, and maybe there’s a team that they’re waiting on something else to happen. They can’t fix their thing until some other third party that they don’t control and we have limited influence over needs to do something.

So the team, that data looks bad, but the team’s doing fine. They’re chasing it on a regular basis; they’re putting pressure on that other group on a continuous basis. It’s just taking time to get resolved. That’s why it informs but does not control.

We’re making decisions based on the evidence. We’re collecting a bunch of evidence; we’re extrapolating what we don’t know or don’t understand. The evidence is going to have gaps in it, and then we’re making an informed decision based on our understanding of the current situation. That’s evidence-based management in a nutshell.

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