I consult, write, and speak on running better technology businesses (tech firms and IT captives) and the things that make it possible: good governance behaviors (activist investing in IT), what matters most (results, not effort), how we organize (restructure from the technologically abstract to the business concrete), how we execute and manage (replacing industrial with professional), how we plan (debunking the myth of control), and how we pay the bills (capital-intensive financing and budgeting in an agile world). I am increasingly interested in robustness over optimization.

I work for ThoughtWorks, the global leader in software delivery and consulting.

Sunday, April 29, 2018

Organizing for Innovation, Part II

Last month we defined autonomy by the classes of decisions that are devolved to the team level, specifically that the smallest organizational unit - a team - has the ability to decide what it should do, can do, and will do. Looking at it this way makes clear the sharp differences between autocratic and autonomous management philosophies. It also helps us to understand that there need to be very special conditions for autonomy to succeed, even on a small scale.

It seems plausible that autonomy can work among a small group of people having a natural predisposition to collaborate and low asymmetry in their depth of skills and knowledge. But there has to be more to it than just a handful of similarly talented and like-minded people working together. If there isn't, than successful autonomous teams are largely an accident of hiring, and not a replicable phenomenon.

According to Morgan, there are four things that characterize an autonomous team.

One is redundancy of functions. Team members have the skills to be able to perform each other's jobs and substitute for one another when necessary. They are called "redundant" functions because each team member has skills they are not using for the work they are doing at any point in time (e.g., coding a new feature doesn't require a change to the build script). A team of poly-skilled people is itself an organization that is flexible enough to reorganize down to its most atomic level - the individual contributor. It adapts naturally because "[t]he nature of one's job is set by the changing pattern of demands with which one is dealing."1

By comparison, a team of specialists can be an autonomous unit when the external environment is stable, but it cannot sustain autonomy in the face of changing conditions because specialists lack the ability to adapt. When a specialized skill becomes unnecessary, the specialist becomes redundant along with it. A revolving door of members destroys the cohesiveness of a team.

The lack of individual adaptability also creates apathy within each member of the team. Problems such as poor quality or long time-to-market are seen as "someone else's problem" to solve because specialists working on the line don't know, or don't care, or don't have the authority to solve them. As a result, "[a] degree of passivity and neglect is thus built into the system."2

The team of specialists therefore lacks the capacity to self-organize because its members cannot change their job to reflect the changing patterns of demand, and because each member is invested in their skillset more than the team itself. Fixing problems within a team of specialists must be initiated and controlled by higher authority that exists outside the team. In dynamic external conditions, a team of specialists is doomed because the whole will always be less than the sum of its parts, while a team of generalists will acquire the skills and knowledge it needs to solve whatever the problem at hand may be.

Another characteristic of autonomous teams is requisite variety. A team's internal capabilities must mirror the breadth and depth of the environment within which it functions if it is to deal with challenges and opportunities posed by the environment. That skill variety must exist within the team itself so that it can be directly applied where and when it is needed.

A team lacking diversity of function must depend on others so that it can respond to environmental challenges. That dependency impairs a team's ability to self-organize and act, and therefore erodes its autonomy. For example, a team that develops an appreciation for something it should do will be inhibited from doing it if it has to negotiate with other teams for skills it does not have itself.3

Satisfying requisite variety is where technology platforms enable autonomous teams. While it is true that it is people and not assets who innovate, the assets can enable or prohibit such innovation. Teams that can consume components produced by others in a self-service manner do not suffer a dependency. The more comprehensive the components available for consumption, the greater the requisite variety a consuming team can possess, the larger and more complex the environment a single team can engage.

There is more to requisite variety than just skills and capabilities. It also makes a case for human diversity within a team. The appreciations a team develops are richer and more nuanced when they are recognized and crystalized through the diversity of its participants. Another way to look at it is, a homogeneous team will develop homogeneous solutions, and through a lack of human diversity will be structurally blinded to both opportunity and threat. By way of example, I once worked with a bank that was slow to realize that the average age of their employee matched the average age of their customer, that the average had been steadily rising for many years and was now well above the national population average. Year-on-year growth of assets under management looked spectacularly good, primarily because wealth distribution overwhelmingly favored the baby boomer generation. Unfortunately, it completely masked a dearth of new customer acquisition. Along the way, they had become generationally tone deaf, failing to develop experiences and products that appealed to younger generations and subsequently grow their customer base.

The next characteristic of autonomous teams is minimum critical specification. Vague charters and ambiguous boundaries create the capacity for self-organization because they build-in the expectation that teams are responsible for self-definition. A team cannot rely on management edicts that tell them what to do and how to do it. A team must instead define itself through practice and inquiry. General guidelines give a team an abstraction that they must constantly solve for, bringing them face-to-face with the appreciations, or "why" they do or do not do something.

Telling a team precisely what to do robs it of the capacity for self-determination and self-organization because it locks them into a swim lane. A team that is precisely chartered is institutionally specialized. We saw earlier that a team loses adaptability when its individual members lack redundancy of function. In a similar fashion, an organization loses adaptability when individual teams lack minimum critical specification, because teams themselves are stripped of their capacity to adapt based on what they see on the line.

Finally, a team must be capable of learning how to learn. This is also known as double-loop learning. Single-loop learning is the ability to detect and correct deviations from the norm, responding to threats to contain and minimize the impact of exceptions. In double-loop learning, a team is able to analyze a situation in its totality and question the relevance of the things that it does as well as the need to do things it is not doing. Single-loop learning is concerned with staying on-course. Double-loop learning is concerned with determining whether a team is doing what it should be doing in the first place. A well-functioning Agile retrospective is an example of double-loop learning.

Both minimum critical specification and learning how to learn point to the need for abstract thinkers, people who can understand a situation and adjust accordingly. Large ex-growth enterprises are operating companies, not developing companies. Operating companies need efficient execution, so they are populated with concrete thinkers, people who are conditioned through incentives and rewards and professional certifications to keep the ship sailing "steady as she goes". Abstract thinkers are constantly questioning why and looking for the right course of action based on all available information. To the concrete thinker, an exception is a problem to be contained. To the abstract thinker an exception is an opportunity to learn.

These four characteristics - redundancy of function, requisite variety, minimum critical specification and learning how to learn - make it possible for a team to self-organize, self-direct and self-regulate in response to changing external conditions. It is not difficult to see how these form the core characteristics of autonomy. It is also not difficult to see how their respective antitheses - specialization, dependency, precise chartering and single-loop learning - are the defining characteristics of the sclerotic organization.

Combined, these characteristics create what Susman4 calls "learning cells" within an enterprise. While they form the basis of the autonomous team, a cell does not simply multiply to form a more complex organization. We’ll next look at what it takes to scale the learning organization.

1 Morgan, Gareth. Images of Organization Sage Publications, 1986.

2 Ibid

3 If "does not have" is institutionalized as "can not have" through shared services - for example, because of an acute shortage of supply, or because those functions are used as control mechanisms to "protect production" - then the pretense of "autonomy" is a veneer over the management anti-pattern of "responsibility without authority".

4 Susman, Gerald. Autonomy at Work: A Sociotechnical Analysis of Participative Management Prager Publishers, 1976.