As an engineer, I love to hear about design, and I really liked Jeremy Alexis‘ talk on a Framework for Making Better Decisions during Product Definition. He teaches at the local Institute of Design (and has a blog about one of his design courses) and acts as a design consultant, and started out by talking about the problem with McDonalds’ ketchup packages — love it, even if it has nothing to do with BPM.
He moved on to some interesting graphs of patterns of good decision quality, and some fatal flaws in decision making:
- The endowment effect, where the owner of something feels that it is worth much more than it actually is (all Web 2.0 companies should pay attention to this)
- Loss aversion, such as fear of losing market share if a product is changed
- Horizontal flight/vertical flight: in areas of uncertainty, we tend to ignore what’s important and focus on what we feel more comfortable with
- Groupthink, where not enough outside ideas are introduced and a small group believes that what they have developed is the right thing
He presented some ideas about decision making at the “fuzzy front end” of product definition, that is, during discovery and scoping, where there are few good tools for making decisions, unlike during later points in product definition (business case, develop, validate and launch) where there are a number of robust tools for decision making. He had some great findings from research on decision making at these early stages, such as its ad hoc and unstructured nature and its internal focus, and how these can make things go terribly wrong. Since there are a lot more ideas in the pipeline at the front end, it’s pretty necessary to determine the winners and losers as early as possible.
Alexis showed us a high-level generalization of what really happens during the front-end discovery and scoping parts of product definition, which tends to just create more of the same rather than actually drive innovation. He then discussed a new approach — create an innovation strategy, triage concepts as they are created, and use a consistent approach to evaluate triaged ideas — and drove into detail on each of these steps. He brought together a number of interesting concepts, such as the 10 different types of innovation plotted against a company’s “ambition level” to see which types of innovation that organizations at different levels of innovation ambition should attempt.
He ended up by stating what we in the technology industry already know: that the ultimate goal of most startup companies creating an innovative product is to be acquired rather than taking their company public, and that many large companies are counting on acquiring their innovation rather than developing it themselves.