Agile : Lean : Design

Building off of (and evolving) Jeff Gothelf and Bill Scott:

Agile = Engine = Quality, Efficiency, & Optimization
Lean = Brain = Decision Making, Risk Management
Design = Soul = Vision, Empathy, Poetics

The three can work great together when focused on their unique strengths and put to a value proposition for an organization such as the empowerment of a culture of learning, especially when applied to the creation of customer value, innovation, and disruption.

Further, if you turn these upside down, they create a unique operational model similar to previously mentioned dual-track systems where there are 3 tracks:

Delivery is well understood. it is where production leads to the ultimate creation of value points for customers.

Discovery is building in adoption in some form or another. It is when framing the problem space, and validating possible solutions comes in. It feeds the Delivery stream.

Understanding is a new track. This is an ongoing track focused on the goals of sensing insights and synthesizing strategies that give focus and direction for Discovery and Delivery.

This last track is not exactly parallel to the previous two, which are parallel to each other. I see the Understanding track as a constant looping weave of 3 actions:

  1. Learning from Delivery outcomes.
  2. Learning from the wide world.
  3. Synthesizing into the Discovery track.

These 3 points weave the Discovery and Delivery tracks together, amplifying their strengths with focus, direction, and data.

Here is a “napkin” sketch about how this sin wave might work to weave the other tracks together.

There is no beginning. There are just points to jump into this moving river. Also, time has no real scale in this image except moving forward. I can only be so god-like.

Analytics from a constant data stream is always available for analysis. The purpose here is two-fold.

  1. To create evolving baselines of your system.
  2. To find problem spaces that require more depth of observation to understanding causes and to frame problem spaces.

Through collecting data from customers and the wide world, a research team can best synthesize problem framing that can be converted into insights that generate new hypotheses. Further, insights can be converted into vision and strategy to provide focus, give direction, as well as give a sense of team mission to products and projects.

Finally, problem frames need guidance in order to be converted into actionable experiments that provide value back into the backlog of delivery.

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