“How big is it?”, “When will it be done?”, and how to stop asking the wrong questions

“How am I supposed to make decisions in the presence of uncertainty?” exclaimed the manager. “Tell me when the project will be done!”

It’s a very reasonable desire to want to know when something will be done. After all, it would be irresponsible to make decisions without considering the trade-off of time and money. However, the urge to ask, “When will it be done?” is causing software projects to fail. To improve decision making, we need to stop asking the wrong questions when estimating time.

If you find yourself in these conversations, you might be wondering what the “right” questions are. In this interactive presentation for managers and team members alike, you’ll learn two simple ways to reframe estimation conversations which greatly improve decision making and forecasting. Further, you’ll see how reframing with the right questions improves relationships, leading to increased trust, safety, and collaboration. Best of all, reframing the conversation takes no permission, budget, or technology; you can start today! Come learn how!


Outline/Structure of the Talk

  • Introduction: A brief story to set the stage and help the audience feel an emotional connection to the content
  • Survey the room: Using a digital tool, reveal the forms of estimation used by the audience AND what decisions are made w/ the estimates

  • The wrong question: "How big is it?"

    • Before we can tackle the demand for date certainty, we need to address variance (one component of Deming’s Theory of Profound Knowledge)
      • When work is neither predictable or repeatable, like software, the impact of variance is typically “special cause”: unlike common cause variation where historical data and probabilities are good predictors, special cause variance is unexpected and difficult to trace.
      • When we ask for estimates of time, effort, and size, we very often ask, “What is the estimate?” or “How big is this?” - this wrong question is so destructive with special cause variance, it is a systemic failure.
    • Table/group exercise to illustrate impact:
      • Tables/groups are given a set of (intentionally) vague tasks to estimate.
        • Part 1: “How big is it?”
          • Estimates are completed and summed up
          • Compare to all other groups - record the variance
        • Part 2: “Is it small enough?”
          • Tasks are broken up to be within a guiding rule of duration
          • New tasks & estimates are summed up
          • Compare to all other groups - record the variance
        • Which part has more variance? Why did this happen?
          • Reframing a reduction of size in how we estimate results in reduced variance (and improved outcomes)
    • Deep Dive: story points are an enabler of the wrong question (and poor outcomes)
      • Teach the audience about statistical categories of data types (Nominal, Ordinal, Interval, Ratio)
      • Story points are ordinal data - which cannot be added, divided, etc.
      • Story points encourage many scales of size, where variance becomes problematic
      • “Points are just symbols representing distributions. If you must use “points”, use colors before numbers to avoid data abuse.”
    • The “Right Question” #1: “Is it small enough?”
      • Naturally reduces variance
      • Enables us to use ratio data - which CAN be added, divided, etc. (how useful!)

  • The wrong question: “When will it be done?”

    • Finally, we can address the real elephant in the room! Now that we have a mechanism to work with ratio data, we can reframe this perfectly reasonable need.
    • Discuss the destructive assumptions we make with “when will it be done” (with point estimates, with story point velocity)
    • The “Right Question #1”: “When will it start?” (requires CAN start and SHOULD start)
      • A very powerful question! This necessarily asks us to consider both CAN and SHOULD it start!
      • Relationship and impact of arrival rate on departure rate - a required part of Little’s Law.
    • The “Right Question” #2: “What is our date range of confidence?”
      • When we work with “small enough” items, we can use probabilistic forecasting
      • What is that? Explain
      • Demonstrate and simulate a project which uses “small enough” items to create a confidence interval forecast.
      • Discuss how using variance in this way allows us to make improved trade-off decisions. Also, how we have a better idea of what probability we’re accepting (risk) - e.g, it's a 50/50 chance at completing on time and I’m willing to take that risk.
  • Wrap-up
    • How to reframe the “wrong” questions into right questions which enable us to make better decisions.

Learning Outcome

  • Use probabilistic forecasting and confidence intervals to improve predictability and expectations.
  • Explain how estimation questions like “how big is it?” and “when will it be done?” are ineffective when variance is unpredictable.
  • Recognize and correct the mis-application of “story points” in project and duration planning.
  • Discuss how the language and words we use can impact estimation conversations and affect relationships.

Target Audience

This interactive presentation is designed for managers (of all varieties) and team members alike. Whether you work with projects, releases, iterations, or simply "flow" work continuously, you’ll learn two simple ways to reframe estimation conversations which greatly improve decision making and forecasting.

Prerequisites for Attendees

Participants will benefit from experience with:

  • Wanting things faster than people can do them.
  • Wondering if we could get more done if people would just work harder.
  • Frustrating outcomes using things like "story points" for planning.
  • Struggles trusting people when they estimate time and effort.
schedule Submitted 1 year ago

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