With 7 technical coaches working with some 160 development teams, we find ourselves moving from team to team with little time for in-depth collaboration. I decided to try a different approach to introduce an effective work flow, encourage collaboration within and across roles, and provide direct experience with recommended technical practices in a short time. We have been running two-day intensive working sessions with one team at a time. We have done this with four teams so far. The experiences have been different, but the general results have been positive in all four cases.
I’m one of six technical coaches engaged by a large bank to support an initiative to improve software delivery performance. The IT department is an established agile software development shop that uses the SAFe framework with Scrum at the team level. They are seeking to achieve continuous delivery, improve software quality, establish a developer-friendly working environment, and foster a culture of continual improvement.
We want to be able to show the effects of changes the teams make in their working practices. Improving delivery performance involves changing the way people work; therefore, we need measurements that aren’t dependent on doing the work in any particular way. Three metrics from the Lean school of thought are helpful: Throughput, Cycle Time, and Process Cycle Efficiency (PCE).
Daniel Mezick confronts the elephant in the “agile” room in his post, Deviation from the Norm: “If current approaches actually worked well, then by now, thousands of organizations would have reached a state of self-sustaining, “freestanding” agility. Clearly, that is not the case.”
Pondering the question, several possible reasons for this result (or lack of) occurred to me. These are speculative and based on my own experience and observations.
Premise: Agile principles depend on biologically hard-wired limits on the effective size of collaborative human groups. For this reason, agile methods as such do not scale to “enterprise” levels.
Recently I noticed a post on Twitter that referred to this article by Eric Barker. Barker, in turn, shares information he learned in a conversation with Po Bronson, an author (with Ashley Merryman) of Top Dog: The Science of Winning and Losing. Now, notwithstanding the word “science” in the title, this is a “pop science” book, not a science book. It’s based in part on the authors’ “research” (reading statistical studies and so forth) and in part on popular assumptions – what we might call “leprechauns” or “urban legends.”.
The article rubbed me the wrong way, so I’m going to indulge myself with a bit of a rant.