Wiring the Winning Organization Influences: Authors, Thinkers, and Leaders

This post is adapted from Wiring the Winning Organization: Liberating Our Collective Greatness Through Slowification, Simplification, and Amplification.

We want to take a moment to explain the substantial number of influences and theories that inform this book, which draws on management, engineering, and mathematics. For the avid reader and thoughtful practitioner (and academics) who have spent time studying these areas, you may find the lineage of ideas interesting and surprising.

What is novel about our theory is that it directly addresses the mechanisms of the social circuitry that enables organizations to achieve these performance advantages. And it recognizes that coordinating and synchronizing various specialties is an information problem to support creative collaboration. The concept of circuitry will be familiar to those concerned with how machines connect to and communicate with other machines. We apply it here to how people and groups communicate and coordinate with each other.

Wiring the Winning Organization asserts that outsized performance doesn’t come merely from reorganizing the shop floor or from adjusting how materials pass through machines (literally or figuratively). Doing so still leaves people spending time and energy on heroics to get things they need to succeed (e.g., information, approvals, requirements, time), navigating often bewildering and byzantine work conditions, processes, procedures, policies, politics, rules, and regulations in their daily work (what we call the danger zone).

Instead, the most successful organizations are those that create conditions in which people can fully focus their intellects on solving difficult problems collaboratively and toward a common purpose, delivering solutions that have great societal value (conditions that we call the winning zone).

Creating such conditions requires developing and engaging three mechanisms to get out of an operating danger zone and into a contemplative winning zone: 

• slowification of the environment in which the problem-solving occurs to make problem-solving easier; 

• simplification of products, processes, and systems through the use of modularization, incrementalization, and linearization to make the problems themselves easier; and 

• amplification to make it more obvious that problems are occurring so they can be seen and solved.

This book explored each of these concepts at length. These insights build on and are informed by streams of research in management theory and adjacent areas that are worth breaking down briefly. We’ll start with slowification.

There are distinctions between fast and slow thinking, as explained by Dr. Daniel Kahneman and Dr. Amos Tversky, that we lean heavily into throughout Part II of the book. Their work distinguishes between slower conditions (in which people can be deliberate, reflective, and creative) versus faster-moving, higher-stakes conditions (in which people must depend upon the “muscle memory” of practiced habits and routines because there is neither sufficient time nor emotional or psychological safety to consider if new approaches might be warranted).

Slowification expands upon this concept by placing an emphasis on creating opportunities to absorb feedback that fosters self-reflection and self-correction. This connects to the literature on organizational learning from systems scientist Dr. Peter Senge’s The Fifth Discipline, business theorist Dr. Chris Argyris’s Organizational Learning, and work by philosopher Dr. Donald Schön.

Simplification may be the most difficult of the three mechanisms because there are three distinct techniques to engage it—modularization, incrementalization, and linearization.

Modularization simplifies problems by partitioning large, complex systems (the elements of which have highly intertwined interdependencies) into systems that are more modular in structure, with each module having clearly defined boundaries and established conventions for interactions with other modules. Clarity around modularization was influenced by Dr. Steve Eppinger’s design structure matrix concepts, Dr. Carliss Baldwin and Dr. Kim Clark’s book Design Rules, Dr. Charles Perrow’s ideas around complexity and coupling in Normal Accidents, and the wealth of architectural practices around APIs, containers, domain-driven design, and so forth.

Incrementalization simplifies problem-solving by converting a few, complex experiments (in which many factors are being tested simultaneously) into many smaller, faster, simpler experiments (in which fewer factors are being tested individually). It does this by partitioning what is already known and validated from what is novel and new, and by adding to the novelty in many small bits rather than in a few large bites. This simplification method is informed by agile processes for product development, and, for the enterprise more generally, by work about the “lean launchpad,” as explained by Steve Blank’s The Four Steps to the Epiphany and by Eric Ries in The Lean Startup.

Linearization sequences tasks associated with completing a larger set of work so that they flow successively, like a baton being passed from one person to the next. What follows is standardization for those sequences, for exchanges at partition boundaries, and for how individual tasks are performed. This creates opportunities to introduce stabilization, so that when a problem occurs, it triggers a reaction that contains the problem and prevents it from enduring and from its effects from spreading. This allows for self-synchronization, so the system is self-pacing without top-down monitoring and direction. Linearization (as well as amplification and slowification) draws from the teachings of the Toyota Production System and Taiichi Ohno; Hammer and Champy’s book Reengineering the Corporation (which championed a process view for organizing enterprises in lieu of an overly functionalized approach); Dr. Bob Hayes, Dr. Steve Wheelwright, and Dr. Kim Clark’s Dynamic Manufacturing (which also speaks to a process view of organizing versus a functional, metric-driven approach); Dr. Eliyahu Goldratt and Jeff Cox’s The Goal; Dr. James Womack, Dr. Daniel Jones, and Dr. Daniel Roos’s The Machine that Changed the World; and, of course, Dr. Jeffrey Liker’s monumental The Toyota Way.

The science around the amplification (or suppression) of small problems includes “normalization of deviance,” as explained by Dr. Diane Vaughan in The Challenger Launch Decision, and feedback as critical for stability and progress, as explained by Dr. Jay Forrester and the systems dynamics community. The common link is that in the absence of fast, frequent, and useful feedback, systems of any type—technological, biological, social, psychological—will experience instability and even collapse. Systems with reliable feedback that triggers appropriate reactions are stable, resilient, and agile in even the most arduous situations. In the long term, systems that have adequate feedback and are capable of adaptation will improve, sometimes in dramatic ways, both by direction and magnitude.

Amplification also draws heavily on the work about control systems of Dr. Harry Nyquist and Dr. Claude Shannon in “Communication in the Presence of Noise,” and Shannon and Dr. Warren Weaver’s 1948 book The Mathematical Theory of Communication.

There’s a meta-acknowledgment necessary here, and that is from Steve to mentors Dr. Clay Christensen and Dr. H. Kent Bowen for pushing so hard on developing a bona fide theory that explains competitive success. Both emphasized, supported, and coached the “inductive” element of theory building—observation, description, categorization, classification, and finally, declaration of causality. They were both wildly supportive of the “deductive” element of theory testing by creating hypotheses that could be refuted or not in practice. Neither Gene nor Steve would have been so obsessive in creating a “simple” theory of learning-based operational excellence without having this thinking in mind.

Last, we don’t want to understate how strongly we argue against the static transactional notions of management and leadership that have so relentlessly gripped theory and practice. Decades ago, economist Dr. Michael Porter compared industrial sectors. He found that those in which competition was less perfect—due to the firms’ ability to lock in customers and suppliers and lock out rivals—offered higher returns than those in which competition was more perfect—due to the ruthlessness of challenge and the greater difficulty of differentiating one’s own offerings from those of rivals.

However, by having the “unit of analysis” of the industrial sector, Porter’s theory of differentiation by positioning couldn’t explain the sustained heterogeneity of outcomes, even within highly competitive sectors. In other words, competitive advantage alone couldn’t explain Toyota’s outlandish successes, overcoming whatever barriers to entry existed to newcomers and beating rivals in an otherwise level playing field, once it was established in the sector. 

Yet, obsessiveness about grand strategic vision has, it seems, blinded too many manager/leaders to the opportunity to take a developmental approach, as we saw throughout the book. That developmental approach is not one of incessantly figuring out what transactions will yield the highest reward from existing resources in already established ways. While the transactions may be many, the mindset is not sufficiently dynamic. Rather, the developmental approach requires designing and improving the social circuitry by which people can best apply their creative energies to find new and better things to do with their time and the resources they have, and by developing new and better ways to do so. 

Similarly, agency theory, as credited to economists Dr. Michael Jensen and Dr. William Meckling, takes the general notion that people respond to incentives in motivating their actions and creates a reductionist view of characterizing enterprises as primarily a collection of contractual relationships. Get the metrics and incentives right, it would suggest, and people will behave accordingly. Again, this is a rather transactional notion of people’s efforts, one that leaves little consideration for collaboration or coordination.

The problem is, of course, that the right metrics vary by degree of aggregation, phase, type of value creation, and so forth. How one measures performance in pharmaceutical research and development is different from measuring performance in clinical trials or production. So, you’d either have to measure everything by the same standards (so measure everything poorly) or you’d have to create metrics and rewards that are too impossibly diverse to monitor effectively. 

And, of course, there’s an implied assumption that you know well enough about what needs to be done individually and collectively, and you know well enough about how to get it done that contracts can be well written. So, organizations trying to create metrics, accountability, and incentives to drive performance—rather than designing systems that are able to harness the investment people are already willing to make in achieving great things together—miss the developmental opportunities that create the chance for greatness. 

In contrast, we present slowification, simplification, and amplification as the mechanisms by which a developmental approach of creating new and better things in new and better ways can be most fully expressed.

- About The Authors

Gene Kim

Gene Kim is a Wall Street Journal bestselling author, researcher, and multiple award-winning CTO. He has been studying high-performing technology organizations since 1999 and was the founder and CTO of Tripwire for 13 years. He is the author of six books, The Unicorn Project (2019), and co-author of the Shingo Publication Award winning Accelerate (2018), The DevOps Handbook (2016), and The Phoenix Project (2013). Since 2014, he has been the founder and organizer of DevOps Enterprise Summit, studying the technology transformations of large, complex organizations.

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Dr. Steven J. Spear

Dr. Steven J. Spear (DBA MS MS) is principal for HVE LLC, the award-winning author of The High-Velocity Edge, and patent holder for the See to Solve Real Time Alert System. A Senior Lecturer at MIT’s Sloan School and a Senior Fellow at the Institute, Dr. Spear’s work focuses on accelerating learning dynamics within organizations so that they know better and faster what to do and how to do it. This has been informed and tested in practice in multiple industries including heavy industry, high tech design, biopharm R&D, healthcare delivery and other social services, US Army rapid equipping, and US Navy readiness.

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