Data Driven Design Thinking

Every year managers are investing significantly towards innovation projects and really do not understand what the return on that investment is. Managers overseeing projects that they are unable to measure the output from nor understand the process are in real trouble. The first thing management teams cut are R&D and product development, because they can’t make it predictable or figure out how to measure it. It’s an unfortunate dilemma because on the one hand we have to have new product development, have to respond to competitive threats and at the same time just firing money into the black hole of R&D is just poor management practice.

These problems are classified as wicked problems and some are suggesting that this thing we call Design Thinking is the potential answer is using innovation as a strategic weapon. In his book “The Design of Business” Dr. Roger Martin (Dean at University of Toronto) talks about using design thinking as a methodology of business management. IDEO’s CEO – Tim Brown – wrote a book called “Change by Design” which talks about case studies in which design is a strategic weapon in organizations. One of the frameworks we use at Ephlux on “Design Thinking” for a more tactical business outcome such as:

  • Empathize – is the process of using ethnography and need finding to understand the latent needs,
  • Define – is creating a point of view around those needs,
  • Ideation – is generating through brainstorming many solutions before zooming into finalization,
  • Prototype – the best fit and
  • Test – seeing what works, involving multiple stakeholders & their feedback in the BETA phase and either moving forward or circling back to Empathize

    design_thinking

At Ephlux, we consider the above to be a series of spaces (or mindsets) that our team occupies, that we’re mindful of. We use multi-disciplinary teams & mindsets in the design thinking process where almost everyone in the organization is involved. When you’re dealing with a classical business problem – one that you can reduce to alternatives, because you have the data to do so – you can decide whether A is more efficient than B or A is a larger market share than B based on which you can decide your way forward.

When we have an engineering problem, where we can isolate the variables, reduce the dependent & independent variables to a series of equations and solve for the correct answer. Then we can engineer our way forward or calculate the way forward. In design thinking, we don’t have enough data to decide an A/B thinking and you can’t reduce the problem to a well bounded set of equations. We say “you can’t think or decide your way forward” rather “you have to build your way forward” because we build through design.

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