Progress toward Goals in A Series of Small Steps
The first step in the journey toward a Strategic Goal is understanding your Current State. If your focus is to achieve a Strategic Goal related to Unrealized Value (UV), as is typically the case, then measuring the Current Value (CV) your product or service delivers is where you should start (of course, if your product or service is new then its CV will be zero). To understand where you need to improve, you may also need to understand your effectiveness (A2I), and your responsiveness (T2M).
The Experiment Loop (shown in Figure 1) helps organizations move from their Current State toward their Next Target Goal, and ultimately their Strategic Goal, by taking small, measured steps, called experiments, using explicit hypotheses.3 This loop consists of:
- Forming a hypothesis for improvement. Based on experience, form an idea of something you think will help you move toward your Next Target Goal, and decide how you will know whether this experiment succeeded based on measurement.
- Running your experiments. Make the change you think will help you to improve and gather data to support or refute your hypothesis.
- Inspecting your results. Did the change you made improve your results based on the measurements you have made? Not all changes do; some changes actually make things worse.
- Adapting your goals or your approach based on what you learned. Both your goals and your improvement experiments will likely evolve as you learn more about customers, competitors, and your organization’s capabilities. Goals can change because of outside events, and your tactics to reach your goals may need to be reconsidered and revised. Was the Intermediate Goal the right goal? Is the Strategic Goal still relevant? If you achieved the Intermediate Goal, you will need to choose a new Intermediate Goal. If you did not achieve it, you will need to decide whether you need to persevere, stop, or pivot toward something new. If your Strategic Goal is no longer relevant, you will need to either adapt it, or replace it.
Hypotheses, Experiments, Features, and Requirements
Features are “distinguishing characteristics of a product”, while a requirement is, practically speaking, something that someone thinks would be desirable in a product. A feature description is one kind of requirement.
Organizations can spend a lot of money implementing features and other requirements in products, only to find that customers don’t share the company’s opinion on their value; beliefs in what is valuable are merely assumptions until they are validated by customers. This is where hypotheses and experiments are useful.
In simplified terms, a hypothesis is a proposed explanation for some observation that has not yet been proven (or disproven). In the context of requirements, it is a belief that doing something will lead to something else, such as delivering feature X will lead to outcome Y. An experiment is a test that is designed to prove or reject some hypothesis.
Every feature and every requirement really represent a hypothesis about value. One of the goals of an empirical approach is to make these hypotheses explicit and to consciously design experiments that explicitly test the value of the features and requirements. The entire feature or requirement need not actually be built to determine whether it is valuable; it may be sufficient for a team to simply build enough of it to validate critical assumptions that would prove or disprove its value.
Explicitly forming hypotheses, measuring results, and inspecting and adapting goals based on those results are implicit parts of an agile approach. Making this work explicit and transparent is what EBM adds to the organizational improvement process.
End Note
Evidence-Based Management is free and offered in this Guide. Although implementing only parts of EBM is possible, the result is not Evidence-Based Management.
Acknowledgements
Evidence-Based Management was collaboratively developed by Scrum.org, the Professional Scrum Trainer Community, Ken Schwaber and Christina Schwaber.
