Experimentation is a fundamental activity for startups. Startups are leaping into a great unknown. Does anybody want to use my product? Will anybody pay for my product? How are we going to build this product? Startups are a pile of assumptions.
The goal of successful startups is to, as quickly as possible, prove or disprove assumptions and turn them into facts. They do this through experiments. In addition to the value of turning assumptions into facts, experiments are also key to effectively managing resources. They can help minimize the risk of investing too many resources into a product whose need or value has not been validated.
Experiments are simply a formal process for data collection. Why formal? Without the formality, experiments often produce less data, the wrong data, or even worse, no actionable data! When thinking about an experiment, startups must be able to clearly answer the following questions:
What we believe (our assumption).
What we will do to verify our assumption (our actions).
What we will measure (our metrics).
What our measurement results need to be if we are right (our expectations).
Nothing is perfect and innovation only comes from new experiments. With so much newness occurring every day, if L&D is not allowed to conduct some experiments of its own it will be forever behind the needs of its customers. Experiments, by definition, have an unknown outcome. Therefore, while L&D can’t know the outcome, it must know the parameters of the experiment and be able to work with the business to set the proper expectations. These expectations must be understood to get the most out of every experiment.
With a mutual understanding of the goals, structure, anticipated return and resources requirements, an experiment’s business sponsor can make a reasoned decision regarding participation in the experiment. Setting expectations is about knowing the risk and understanding that the potential reward is critical for experiments to be accepted in organizations unfamiliar with risk-taking.
For L&D, experiments can be used on any number of aspects of their organization. Content is the obvious one. I also believe that those organizations that adopt this approach in areas like process and people will see great return.
I recognize that a scientific approach can only take you so far. There are many factors that could influence the results of an experiment and there is not enough time or resources to prove everything. However, experimental results filtered through the experience and knowledge of the L&D organization can greatly increase the confidence level in any decision.