Management Improvement Carnival

I’m honoured to have been asked by John Hunter to host an edition of his Management Improvement Carnival. That means that I get to pick a number of links to posts and articles on relevant topics. Here they are…

Agile Fluency

One set of posts that caught my eye was on Agile Fluency. The original post by James Shore and Diana Larsen proposes “a model of Agile fluency that will help you achieve Agile’s benefits. Fluency evolves through four distinct stages, each with its own benefits, costs of adoption, and key metrics”. Dave Nicolette responded that ” the gist of the article appears to be that we can effect organizational improvement in a large company by driving change from the level of individual software development teams. The major problem with that idea, in my opinion, is the bottom-up approach.” James then further clarified, by saying “Dave argues that the individual software teams in IT cannot drive bottom-up organizational change. I agree. Organizational change must occur if you want to achieve three- or four-star fluency, but our article doesn’t describe how to do so. It just says it’s necessary.”

Cynefin Agile Lean Mashups

One of the areas I have been involved in recently is in exploring how we can use ideas from social and complexity science to inform the theory and practice of Agile and Lean. This months CALM Beta event was specifically aimed at using Dave Snowden’s work with Cyenfin to do this. Dave has recently been blogging about his latest thinking on Complexity.

Employee Ranking

This link from Forbes has been doing the rounds in my twittersphere, describing how “a management system known as “stack ranking”—a program that forces every unit to declare a certain percentage of employees as top performers, good performers, average, and poor—effectively crippled Microsoft’s ability to innovate”. In response, Jabe Bloom described how “it’s been three years since we last ranked employees or gave performance reviews at TLC, and we think it’s working reasonably well.”

Agile Book

One of my colleagues, Bob Gower, has been putting together a book about Agile Business, including contributions from a number of Rally Coaches. “An important part of Agile is shipping things in a continuous and real-time manner. This is our effort of practicing what we preach. We are releasing the first increment of the book at the Agile 2012 conference to test how you think we’ve done—it’s not a complete copy of the book but enough we hope to whet your appetite.”

Introduction to Waterfall

Finally, here’s something fun I put together recently to help explain waterfall.

 

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The Science of Kanban – Conclusions

This is the final part of a write-up of a talk I gave at a number of conferences last year. The previous post was about the science of economics

Scientific Management Revisited

Is scientific management still relevant for product development then? As I have already said, I believe it is, with the following clarifications. I am making a distinction between scientific management and Taylorism. Whereas scientific management is the general application of scientific approach to improving processes, Taylorism was his specific application to the manufacturing domain. Further, in more complex domains such as software and systems development, a key difference in application is that the workers, rather than the managers, should be the scientists, being closer to the details of the work.

Run Experiments

The used of a scientific approach in a complex domain requires running lots of experiments. The most well-known version is PDCA (“Plan, Do, Check, Act”) popularised by Deming and originally described by Shewhart. Another variation is “Check, Plan, Do”, promoted by John Seddon as more applicable to knowledge work because an understanding of the current situation is a better starting point, and Act is redundant because experiments are not run in isolation. John Boyd’s OODA loop takes the idea further by focussing even more on the present, and less on the past. Finally, Dave Snowden suggests “Safe To Fail” experiments as ways of probing a complex situation to understand how to evolve.

Whichever form of experiment is run, it is important to be able to measure the results, or impact, in order to know whether to continue and amplify the changes, or cease and dampen them. The key to a successful experiment is whether it completes and provides learning, not whether the results are the ones that were anticipated.

Start with Why

Knowing whether the results of an experiment are desirable means knowing what the desired impact, or outcome might be. One model to understand this is the Golden Circle, by Simon Sinek. The Golden Circle suggests starting with WHY you want to do something, then understanding HOW to go about achieving, and then deciding WHAT to do.

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Axes of Improvement

One set of generalisations about WHY to implement Kanban, which can inform experiments and provide a basis for scientific management is the following:

  • Productivity – how much value for money is being generated
  • Predictability – how reliable are forecasts
  • Responsiveness – how quickly can requests be delivered
  • Quality – how good is the work
  • Customer Satisfaction – how happy are customers
  • Employee Satisfaction – how happy are employees

The common theme across these measures is that they relate to outcome or impact, rather than output or activity. Science helps inform how we might influence these measures, and what levers we might adjust in order to do so.

Lean

In these posts I have described Kanban in terms of the sciences of people, process and economics. However, this can actually be generalised to describe Lean as applied to knowledge work, as opposed to the traditional definition of Toyata’s manufacturing principles. The differentiation is also a close match back to my original Kanban, Flow and Cadence triad.

  • Kanban maps to process, with the emphasis on eliminating delays and creating flow rather than eliminating waste.
  • Flow maps to economics, with the emphasis on maximising customer value rather than reducing cost.
  • Cadence loosely maps people and their capability, with the emphasis on investing in those who use the tools rather than the tools themselves.

References

The ideas in this article have been inspired by the following references:

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