The Learning Machine: get agile with control
“Agile” is one of those horribly overused words in the IT industry that means different things to different people. Views range from “Great! No plans, documents or deadlines!” to “I am a Certified Practitioner and we do it this way.”
Successful “agile” means having enough process (and no more) to enable the release of meaningful, incremental product changes – then measure what difference those changes make and feed that back into deciding what to do next – a “Learning Machine”.
Most new product ideas turn out to be unsuccessful. Moreover, it is notoriously hard – indeed impossible – to predict in advance which of a range of plausible-sounding product ideas is actually going to work.
Most successful products are actually the sum of a large number of good design decisions. (Think Macbook Air.) If you can find a way to generate a lot of individual improvements, then you have a chance to make a big difference to your product. A good brainstorming session, combined with customer feedback, will generate a long list of candidates for “how to make the product better”.
So how does it work?
- For each plausible idea generate a quick and inexpensive plan for how to test it out and measure success – a hypothesis
- Run the Learning Machine in week-long cycles; sift the ideas and decide which experiments to run
- Probability. Is this idea going to pan out in a reasonable timeframe?
- Impact. Will the idea make a measurable, meaningful difference?
- Resources. Is this going to be costly to develop and test?
- Run the experiments and analyse the findings. Most hypotheses will prove unsuccessful. What matters is to test a lot of ideas in a short space of time, and minimise the amount of time and effort it takes to discover whether a hypothesis is successful
- Kill off the ideas with no legs; rework and retest the ideas with some potential until you find something that really works
- Once on to a winner, develop the idea properly – this can take longer than seven days for more complex ideas
The Learning Machine attempts to merge the best of Lean UX and agile to foster a culture of experimental iteration and continuous improvement. It directs resources and energy to the features that matter most to customers and saves considerable amounts of wasted time and effort.