Complicated vs. Complex: the human factor in project management

Classic, agile or hybrid project management – what do I choose in a project?  The Stacey Matrix (after the organizational theorist Ralph D. Stacey) can provide a decision support. A criteria catalog is used to assess how well a project plan is already understood – in terms of requirements on the one hand and the solution approach on the other. Are the requirements clear or are we moving into a new, as yet unknown market? Are you using a well mastered technology or a new one with which you have no experience?

Simple, complicated, chaotic?

Along these two axes, the Stacey matrix divides a project into the categories simple, complicated, complex and chaotic. According to the so-called Cynefin framework, simple systems are ordered so clearly that they can be understood immediately. Complicated systems are difficult to understand. With expert knowledge, however, it is possible to understand and predict their cause-effect relationships in advance.

Although complex systems are also determined by clear causalities, they exhibit so many interactions that even experts are no longer able to analyze them sufficiently in advance. The correlations can only be recognized and understood afterwards. A system is described as chaotic if there are no clear causal relationships and one and the same cause can produce completely different effects.

A small example illustrates this:
For a meteorologist, for example, a weather forecast for the next hour may be simple, one for the next day complicated. A forecast for the next week, on the other hand, might be a complex problem, while the forecast for one day of the next year is certainly a chaotic one.

As long as project plans are simple or complicated, they can be well mastered with a waterfall like, firmly predefined procedure depending on the expertise. However, the more they tend towards complexity, the more an agile, flexible approach with many feedback loops and the possibility of trial and error is recommended. I think this is a plausible approach, which, by the way, can be applied not only to entire projects, but also selectively to individual areas in a project.

The social dimension

But perhaps this approach is not quite enough. We have talked about requirements and about approaches to solutions, but not yet about the people who work together in the project. Isn’t their organizational and social interaction also simple, complicated or complex to chaotic? And doesn’t this factor have the same major impact on the success of the project? In my opinion, this is precisely the point at which one must speak of unpredictability, i.e. complexity.

A well-rehearsed team that has been working together for years can certainly be classified as easy. However, it is often forgotten that hardly predictable dynamics can occur in a newly assembled team or in a new cooperation of different departments with different interests. Here, agile methods with their focus on results-oriented communication can be the key to mastering the project.

So perhaps we should add a third dimension, “social interaction”, to the two axes “requirements” and “solution approach” in order to complete the decision model and lay the foundation for project success.

Agile physical product development?

My last blog post was about teams that only become really agile through experience. Today, the focus is on the challenges that agility brings to engineering.

Almost 20 years after the Agile Manifesto, agile software development has become widely accepted. It is no longer about whether, but only about best practices in detail and agile scalability. The success and ease of use of task boards, for example, have led to agile procedures also finding enthusiastic users outside software development where tasks are processed in a team.

This finally led to the increasingly intensively discussed question of whether physical products could also be developed more efficiently with an agile approach.

Why?

For many years, there have been established product development processes that have reached great maturity and support successful development. Why abandon them and take on the risks of a completely new approach?

The more unclear the requirements on the product are and the less known the technology to be used, the less suitable classical project management methods are, because they are very strongly forward-planning. It is precisely this tendency to start projects despite initially incomplete requirements that we are increasingly observing. Digitization and new technologies require new business models or new technological capabilities. This speaks for an agile approach, as it was invented to deal with ambiguity and not-yet-knowledge.

Is that even possible?

The decisive question here is: Are agile methods from software development at all suitable for mastering the challenges of “classical” product development? In contrast to software, physical products are developed with a much greater division of labour. The production of faulty components causes high consequential costs and the validation depends on physical prototypes. It is not possible to present a new, functioning and potentially deliverable stand every two weeks. Solutions for such problems require a creative further development of the known agile process models. A very simple example: The teams of different domains use different sprint durations. While the software team delivers every 2 weeks, the mechanics team delivers every 6 weeks. It is important to synchronize the sprints so that a common increment is achieved every 6 weeks.

The challenge

The challenge of introducing agile methods is therefore twofold: On the one hand, it is necessary to adapt the agile methods from software development to the conditions in product development. On the other hand – and this brings me back to my previous contribution – a lot of agile experience is needed to successfully make such adjustments. In order to resolve this contradiction, one should bring together the pioneers who dare to venture into new territory with experienced “agilicans” who master their craft in software development. Mutual learning and sharing of knowledge leads to a better mastery of product development under rapidly changing conditions.

Being agile or appearing agile?

When I first heard about agility years ago, I first had the impression that processes and rules should be thrown overboard in order to miraculously realize volatile requirements in the twinkling of an eye. I couldn’t imagine how this would work: agility sounded to me like an unattainable wish concert.

Initially, when our software development team started to work with Scrum – with me as the product Owner and guided by an experienced Scrum Master – I seriously dealt with the topic.

I learned that agility does not mean chaos, but quite the opposite was true:

Lesson 1: Discipline

Agile approach has rules. We learned them in the previous Scrum training, but most of all our Scrum Master advised us to strictly adhere to the Scrum rules instead of interpreting them in the way that seemed most appropriate to us. What I learned: Agility is not a laissez-faire, but requires a very disciplined approach that only works if it is lived consistently and not bent as needed.

Lesson 2: The Sense

Fixed roles and rituals are useful. We had learned them for Scrum, but real understanding grew gradually through coaching and the questions of the Scrum Master. For example, when in the process of a sprint it turned out that several of the agreed user stories would not be reached. Of course, all team members tried to do their own job in the best possible way. This would have meant that the individual user stories would only be completed to 70%. The Scrum Master, however, put up for discussion the idea of discarding one or two user stories for the sprint instead and helping to complete the others. What we learned: Results orientation and focusing on a common goal make teamwork more productive and team members more satisfied.

Lesson 3: Team Spirit

The more we internalised the meaning of the rules, roles and rituals, the more efficient the projects became. The team grew more and more together and not only a common focus on achieving the goal developed, but real cohesion. Where previously colleagues had expressed a lack of understanding for each other’s work or had blamed each other, everyone in the team now knew what the others were doing and why. They helped each other to the best of their ability and trusted each other more and more. And because sustainable learning works above all through positive emotions, this was the point at which we developed a real understanding of agility.

In the end it became clear to me that agility only comes about through the interaction of rules, people and motivation. Understanding the agile values behind the rules is crucial. Otherwise there is the danger – by picking out or bending individual rules to one’s own needs – of failing with the agile approach.

This does not mean that the agile frameworks must not be adapted or selectively applied. But you have to understand them first.