What next after part I?

What’s next after part I of the new Agendashift book (published last month), that is.

The obvious answer would be part II, which I intend to consist mainly of case studies and smaller real-world examples of Lean-Agile change in action. Before that though, I’ve been experimenting with some machine learning tools, in particular in the area of dimension reduction. Broadly, this allows the 43-dimensional data of the Agendashift survey results to be boiled down to just a few key features (factors, traits, tendencies, etc).

This has considerable potential:

  1. I am already able to demonstrate the automatic identification of survey scores that don’t fit the model – areas in which the organisation in question has unusually strong areas to celebrate or weak areas for further investigation – all driven by the data, not the biases of the person facilitating the debrief
  2. Cluster analysis could allow representatives of organisations exhibiting similar traits to be introduced and their experiences compared
  3. A combination of 1 & 2 could lead to some kind of recommendation system – machine-assistance for the coach, perhaps

Expect an announcement very soon on point 1, a new commercial offering and new functionality available soon to paid users (ie Agendashift partners).

Point 2 is in fact my plan for part II. Technicalities aside: bring people together, get them talking, write it up 🙂

Point 3 is for the longer term. A “living” version of the book, if you like.

Technical footnote: The machine learning (ML) tools available in Python are truly awesome. Book recommendation: Python Machine Learning by Sebastian RaschkaI’ve made good use of his online tutorials too.

Questions? Go to #next-steps in our Slack.


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