Does it really exist?
Or are we still working in the blacksmith shop? Will it take AI to bridge the gap?
In Lean manufacturing companies that build physical things have been able to improve quality consistently and dramatically since the dawn of the industrial age.
Here many of us are in the post-industrial, Information Technology or Digital Age.
When we change the channel to knowledge work, companies struggle mightily to match the pace of quality and outcomes of physical manufacturers, even to this day. Why?
XP, Agile, Scrum, DEVOPS, Kanban for Software, Scaling Frameworks
Are these practices, methods, frameworks, and guidance really helping the knowledge worker factory catch up with companies that make physical things? Perhaps there is some evidence to support the claim.
But, there is still not a single source for patterns that can predictably improve knowledge factories. The Agile world is eating itself. The SAFe® is the first and best attempt to date to combine a bunch of good, yet disparate, things into a single cohesive set of structured patterns for the knowledge work factory. It does a good job of aligning knowledge workers to a value stream on a common way of working. Yet, something is still missing. Organizations still struggle with anti-patterns even after a proper SAFe implementation. Why?
Why going back to what works is important
Takt time is the average time between the start of production of one unit and the start of production of the next unit, when these production starts are set to match the rate of customer demand. Takt time – Wikipedia
One aspect of the problem with the industry as it is now is the common pattern of addressing only part of the problems. Then, solving part of the problem with a half-baked solution that becomes another problem.
Case in point…
It is interesting and obvious why knowledge workers immediately want to buy or build a refrigerator to help them manage the work when starting to scale “Agile,” or “Scrum.”
There is something though that gets broken when knowledge workers recreate siloed interfaces attached to screens in metal boxes. The silos that caused so many of the bad behaviors before Agile, stick around. The work is visible… but only through a small screen into the refrigerator. All we did was move the problems around, mix them up a bit, and re-baked it into a fancy tool.
Can you really see the entire picture through a keyhole?
Companies like Rentouch are making headway with their PI Planning application accompanied by large-format touchscreens. But this requires a significant investment in tooling. Most companies would say no to multiple large-format Kanban interfaces per team plus all the common areas. So we use stickies and butcher paper. Which worked really well, except for folks working on the other side of the planet.
Which brings up a fallacy of the knowledge factory. Look closely at any manufacturing plant and you will see LOTS of custom and automated tooling (robot painters!). Conversely, knowledge factories seem to invest only the very minimum in tooling and process workers! How often do they hide it behind being “lean” or because the budget will not support it?
Then they drive these broken mental models quarter by quarter with assumption chains that don’t achieve the desired business outcomes. They lack systems thinking, a holistic view of the entire value stream and what it takes to remove or optimize constraints and bottlenecks.
This is why Erik kept making Bill meet him on the catwalk in The Phoenix Project. So he could physically see how the work centers flow actually happens. How do you do this with knowledge work? DEVOPS attempts to solve this challenge through measurement, automation, and culture. The problem with this approach is that it focuses on Dev and Ops and largely ignores the enterprise as a whole.
DEVOPS alone isn’t enough. DEVOPS only addresses the value stream (perhaps only a portion of it as well) and meanwhile ignores the whole of the organization.
This is why I’m a big supporter of the organizational mindset movement. Building thinking tools to help organizations actually address challenges systemically, holistically while bridging the gaps between mental models, missing connections, and broken interfaces.
Learning how to manage assumptions and unknowns and minimize unmanaged assumptions is critical to successfully tying together all the parts of the knowledge factory into an optimized system.