Today we are releasing three new white papers:
- Extending Lean for Knowledge Work: A Retrospective
- Lean Leadership in a Disruptive World
- Higher-Order Organizations and the Post-Lean Future
These papers should be of particular interest to those interested in the future evolution of Lean, and also to executives in mature organizations who wish to improve innovation and retain entrepreneurial employees.
The papers summarize what we have learned about reinventing Lean for knowledge work over the last ten years and how we believe we are now entering a new era with new rules for success. Because many of the most basic assumptions behind Lean are becoming less and less valid, we refer to this new era as the Post-Lean Future.
The nature of jobs, work and organizations is changing rapidly due to exponential improvements in many key technology areas. This has very dramatic implications for organizational structure, learning and leadership. One of our suggestions for how to deal with these changes and retain the relevance of Lean in enterprises is a type of hybrid organizational design we refer to as the higher-order organization. It combines core aspects of Lean such as developing people with proactive development of new ventures that utilize disruptive technologies.
We also discuss how Lean might apply in the new marketplace organizations, such as Uber and Airbnb, that are now rapidly emerging. In these organizations we are likely to see a resurgence of Taylorism, so the question is whether Lean in its conventional form is applicable to the freelancers at all.
To proceed directly to the papers, go here.
To learn about how all this came about, keep reading.
About a year ago Cindy Swain at the Cutter IT Journal had asked me to write an article about Lean and Big Data. I had thought it might make an interesting topic, because I had attended two of the annual Big Data summits put on by The Economist. Martin Giles, their Silicon Valley correspondent (who left in February this year to become a venture capitalist) had been kind enough to invite me.
From all the panel discussions and hallway conversations, I noticed that everyone seemed stuck in the command-and-control paradigm. What they all really wanted from Big Data was more centralized learning and decision-making, preferably automated. I wondered whether the choice was between machine learning and more Taylorism OR genuine Lean Thinking, including developing people? Could the two be combined? The working title for my paper was: “Lean and Big Data: Friends or Foes?”
To be honest, I now felt a bit discouraged about the topic. Changing managerial mindsets is difficult. The vast majority of organizations are still more prone to Taylorism than fulfilling the lofty ideals that came out of Toyota. So I did what we all do. I procrastinated.
In November I took a personal trip overseas and my mind drifted back to the paper. On my way back to California in December I was earnestly working on it. Friends and colleagues were subjected to many, many drafts. Several weeks later, I realized that the paper, which was now 25 pages and still growing, had become too complex.
Cindy gently pointed out that the paper was really five papers in one. Which of them did I want to write? Dr. Susan Stucky, a friend and colleague, identified several interweaving themes. There was definitely something deeper going on, something much more fundamental than just Big Data. I started over.
Meanwhile, over the last few months we at LSI had also engaged in some reflection about what we had learned in our first decade (2004-2014) from our research and client work. We had developed a rich methodology, the Lean Systems Framework (LSF), which extended Lean with new problem-solving methods as well as a broad range of models for organizational design.
We had been able to use the LSF in organizations from 20-100,000+ employees across many industries. Usually our work included help with teaching and facilitating organizational design. We were able to see some patterns in what influenced organizational design decisions. On one slide in our course on organizational redesign, we list the following design drivers:
- Business model(s) we need to implement or support
- Strategic goals – operating performance, entering/exiting markets
- Customer demand, now and in the future
- The nature of the work – knowledge creation, service delivery, production, etc.
- M&A efforts, getting ready for divestiture or integrating an acquired business
- Resource and talent cost and availability
- Mindset (beliefs about ourselves, our colleagues and the future)
- Leadership changes – leaders impose new goals, constraints
- Perceived business risks
This is certainly not an exhaustive list, but it reflects our field experience. We had a clear sense that these drivers were about to change, or were changing, because of new technology. But which ones? And how?
In February, Peter Diamandis’ inspiring new book, Bold, finally arrived. Diamandis provided a summary of dramatic developments in key technology areas and how entrepreneurs could use these technologies to build disruptive businesses.
We were most interested in the impact for existing businesses. We began tracing the evolution of organizations, starting with the Neolithic revolution beginning about 10,000 years ago. We wanted to understand why organizations are the way they are, both in terms of mindset and operations. Hopefully we could ascertain what technologies and drivers were most significant and why.
The introduction of agriculture meant organizing around a shared resource – crops and domesticated animals. It also introduced stratification, top-down coordination of work and division of labor. All of this continued into the industrial revolution, except that there was a new type of resource: the factory. Traditional pyramid-shaped organizations had evolved for good reasons.
In recent years, exponential progress in computing capacity and the emergence of the commercial Internet have reduced the time, space and cost requirements for coordinating work to almost zero. We have also been able to decouple the where and when of work from physical goods. The latter will increasingly be produced locally and on a just-in-time basis, thanks to the emergence of 3D printing.
The impact on organizational structure seemed “obvious”, but there was another key area being transformed as well. People. Human learning is already being augmented by machine learning. In many cases it seemed to become obsolete. Repetitive knowledge work as well as manual labor is increasingly being replaced by software and robots.
Self-actualization is becoming increasingly important. However, in a time of accelerating technology progress, staying current often means moving from one company to the next before one falls behind in one’s professional development. With short employee tenures, developing people in the sense advocated by Lean has become much more challenging.
When we looked at the world in which Lean was born and contrasted it with the world that is now emerging, the contrasts were simply huge. The term “Post-Lean” became too tempting not to use.
On June 23 I gave a preliminary talk in San Francisco where I used the slides below to contrast the usual assumptions of Lean with the Post-Lean Future. To find out where we think it is all leading, have a look at the new papers.
