Agile Organization

Before the introduction of new technology, work organization was based upon pair-based units, which contained the full range of coal-face skills; each collier was an all-round workman. He was usually able to substitute for his workmate. The choice of workmates was made by the men themselves.

Leadership and supervision was internal to the group, which enjoyed a responsible autonomy. This organization had the advantage of placing responsibility for the complete coal-getting task onto the shoulders of a single small group. Work was meaningful and colliers could relate it to clearly identified outcomes.

When pair-based teams encountered hazardous conditions, they had enough skills and autonomy to respond in an appropriate way. The capacity of these small teams for self-regulation and self-adaptation was a function of the wholeness of their work task.

The authors of the study make it clear that the new technology was incompatible with the old work system: “With the advent of coal-cutters and mechanical conveyors, the degree of technological complexity of the coal-getting task was raised to a different level. Mechanization made possible the working of a single long face in place of a series of short faces”.

The organizational construct of a “longwall” production unit was based upon a series of shifts with cycle groups of 40-50 men, their shot-firer, and the shift deputies responsible for the working as a whole. The introduction of the new system disturbed the social balance: “It was impossible for the methods to develop as a technological system without bringing into existence a work relationship structure radically different …​”.

In many coal mines, the consequence of the introduction of new technology was disorganization and waste: “Disorganization on the filling shift disorganizes the subsequent shifts, and its own disorganization is often produced by the bad preparation left by these teams. Every time the cycle is stopped, some 200 tons of coals are lost. So close is the task interdependence that the system becomes vulnerable from its need for one hundred percent performance at each stop”.

Autonomy and trust was replaced by blame and lack of accountability: “Since bad conditions and bad work interact so closely, it is usually difficult to pin blame specifically. Mutual scapegoating is a self-perpetuating system, in which nothing is resolved and no ones feels guilt”, the authors of the study observe.

Not all coal mines that deployed new technology suffered from these problems. The mines that let teams of multi-skilled workers form spontaneously and take on responsibility for the entire mining operations cycle did much better [Pasmore 2019]. The new form of organization that emerged features men who allocated themselves to tasks and shifts.

Although the tasks are those of conventional mechanized systems, management and supervisors do not monitor, enforce, and reward single task execution. The multi-skilled group takes over some of the managerial tasks as it had in the pre-mechanized organization, such as the selection of group members and the informal monitoring of work. Problems are solved by teams as they are encountered, resulting in operations running more smoothly and safely.

Pasmore and his co-authors list a set of socio-technical systems design principles:

To this day, these principles remain valid and should influence the enterprise that deploys agility at scale.

Stream-aligned teams make a functioning whole because they are responsible for all the activities necessary to deliver valuable streams of work. They are closer to external or internal customers because they deliver value to them. Stream-aligned teams usually interact with customers and are able to quickly integrate their feedback.

A great number of streams exist in an Agile at scale organization. The intentional architecture defines a modular decomposition of the architecture at all levels of the enterprise. Stream-aligned teams are assigned the responsibility of segments of the enterprise at different levels of granularity. For example, a “team of teams” can be entrusted the responsibility of lending products that target small businesses. At a lower level of granularity, a small “two-pizzas” team can be entrusted with the responsibility of the customer appointment management feature.

When assigning responsibilities to a team, it is critical to ensure the resulting cognitive load will not be too high [Skelton 2019]. When the capacity of a team is spread too thin over a scope that is too large, it affects team morale and work quality. Taking cognitive load into consideration when defining the scope of Agile teams is critical.

Another consideration is the “Dunbar number”, which is a limit to the number of people with whom a person can maintain stable social relationships. Robin Dunbar found a correlation between a primate’s brain size and the average social group size. Extrapolating this result to humans, the Dunbar number estimates that the size of a stable and cohesive human group should not exceed 150 to 200 people.

When the architecture of a system and the structure of the organization that is responsible for that system are at odds, the likelihood that the structure of the organization will win is high. This is why the Inverse Conway Maneuver recommends shaping the organization so that communication lines mirror intentional architecture boundaries.

This document recommends the decomposition of the enterprise into segments that are:

Agile Organization at Scale summarizes the ideas developed in this section.

Platform teams deliver an architecture and a set of integrated components to internal customers.

For example, the automotive industry develops platforms that consist of the floor panels, suspension system, firewall, and rocker panels. It constrains the architecture of the product. It provides a structure for major components by determining the body size and type of engine and transmission [Cusumano 1998].

In software engineering, a software product line is equivalent to an automotive platform. It is a “set of software-intensive systems that share a common, managed set of features satisfying the specific needs of a particular market segment or mission and that are developed from a common set of core assets in a prescribed way” [Northrop 2012].

Stream-aligned and platform teams are at risk of becoming silos if they are not completed by another type of organizational construct: competency teams.

Competency teams regroup people from the same discipline or competency area. Competencies can be of various types, ranging from “hard” engineering disciplines to “soft” disciplines such as anthropology or psychology.

Competency teams can take various forms, ranging from a virtual organization, such as Spotify’s Chapters or Guilds [Kniberg 2019], to a functional department which regroups similarly-skilled people to manage their career and develop specialized knowledge.

Competency teams can also take the form of enabling teams, as described by Matthew Skelton and Manuel Pais [Skelton 2019].

A product manager leads a product team. This is not a management role, but a true leadership role that requires those assigned to be among the strongest talent in the enterprise. Marty Cagan claims that a product manager who operates according to the Silicon Valley model must, like a CEO:

The product owner role definition differs depending on the Agile framework:

Marty Cagan compares and contrasts the product owner role with the product manager role. He observes product owners tends to be less qualified than product managers. Too often, a product owner is a “recycled” project manager or Project Management Officer (PMO) who does not possess enough experience, competencies, and skills to truly play a product manager role. When a true product manager is appointed, it is critical that they play a product owner role too.

Unlike most product owners who prioritize features, successful product managers prioritize outcomes rather than product features.

Unlike the project‐oriented model, which is all about getting product features developed and deployed, a product team is accountable for business outcomes. Success is measured through experience and business results metrics.

The chief engineer is an entrepreneur and architect. They represent the voice of the customer and are accountable for the economic performance of the product; for example, a new car model. They have enough technology and business insight to solve cross-disciplinary problems.

The chief engineer has a passion for the new product and can inspire excellent engineers. They are too busy designing the product and the value stream that will produce it to have the time to manage team members. Functional departments manage people and capitalize knowledge in their engineering discipline.

Lean Chief Engineer Model illustrates how the system works.

The Lean Product Development organization is quite similar to Marty Cagan’s product team model; a similarity worth acknowledging as these practices come from different industries and were developed independently. Both models also differ from the way Agile frameworks usually define the product owner role.