Applying the heuristics of “How Big Things Get Done” to adaptive delivery

I read a number of project leadership books each year but usually I find only one or two which really make an impact. Professor Bent Flyvbjerg and Dan Gardner‘s book “How Big Things Get Done” is one of the latter.

I have never had the opportunity to lead a megaproject (the term is typically used for those with a budget in excess of $1 billion), but over the last fifteen years I have read a number of the articles published by Prof. Flyvbjerg on the subject and always learned lessons which were applicable to the projects I was involved with.

In the book, the authors provide many case studies supporting eleven heuristics derived from Prof. Flyvbjerg’s decades of research into large, complex projects. While the term “heuristic” is apt as each is a useful mental shortcut, they could also be used as principles.

Given that twenty-two out of the twenty-three categories of the projects evaluated are physical projects (e.g. construction, mining, aerospace), it is tempting to assume that these heuristics are only relevant to projects delivered with a predictive approach.

That would be an invalid assumption as out of the eleven heuristics, I found that most are equally applicable to adaptive delivery. Here are just a few which fit well.

Hire a masterbuilder: we want to have someone with significant domain experience and a proven track record of success leading the work. Whether we are looking to fill the role of a project manager, an agile lead (e.g. Scrum Master) or a product owner, relevant experience and knowledge are critical.

Get your team right: The first value statement in the Manifesto for Agile Software Development is “Individuals and interactions over processes and tools”. And as Prof. Flyvbjerg states, the main job of the masterbuilder is to pick the right team members to get the work done.

Ask “Why?”: While the scope of a project is expected to emerge over its life when using an adaptive delivery approach, it can be a fatal mistake to not spend sufficient time upfront identifying an expected end vision. This North Star enables the team to challenge work items which will not achieve the desired outcomes and reduces the likelihood of an adaptive delivery approach being a random walk to nowhere.

Build with Lego: The idea of creating large systems from smaller components is a natural fit with the incremental nature of adaptive delivery. When a team takes a large work item and figures out a way to slice it into smaller pieces which still individually deliver value they are applying this heuristic.

Think slow, act fast: On the surface, this heuristic sounds like an invitation for big, heavy, upfront paper-based planning which agilists eschew. This is not what Prof. Flyvbjerg is advocating. What he is recommending is to reduce the cost of trial and error by taking the time to identify key areas of uncertainty which could impact successful delivery and to learn and find ways to address them effectively as early as possible in the project’s life cycle. The examples which are provided about how Pixar plans its films or how Frank Gehry designed the Guggenheim Museum in Bilbao both demonstrate early de-risking which is a core attribute of adaptive delivery.

Say no and walk away: Prof. Flyvbjerg highlights the importance of focus when delivering complex projects. If an action does not contribute to achieving the project’s outcomes, skip it. This aligns well with the tenth principle of the Manifesto: “Simplicity–the art of maximizing the amount of work not done–is essential.”

While I have not covered all of the heuristics and their adaptive delivery applicability in this article, I hope that I have encouraged all of you to read this book, regardless of the domain or the approach used to deliver your projects.

(If you liked this article, why not read my book Easy in Theory, Difficult in Practice which contains 100 other lessons on project leadership? It’s available on Amazon.com and on Amazon.ca as well as a number of other online book stores).

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Our project management future is analog…

I’ve just finished reading The Revenge of Analog and The Future is Analog by David Sax. In both of these books, he provides compelling arguments supported by a number of case studies taken from different domains to show that while some might envision the future as becoming more and more digital, we will continue to cherish and yearn for analog experiences. The latter of the two books was written during the COVID-19 pandemic where most of us underwent a rapid acceleration into a digital future and in most cases, didn’t like what we experienced.

So what does this have to do with project management, you ask?

Ever since ChatGPT hit mainstream consciousness in November 2022, a frequent topic of discussion in most project management online communities has been what progressive improvements in A.I. capabilities will mean for the profession.

As with any other disruptive change, there are some practitioners who go all in on the future for A.I. technologies whereas others marginalize their potential.

My opinion hasn’t changed.

So long as the scope of projects is delivered by human beings, I find it unlikely that we will abdicate leadership responsibilities to a machine. As unique endeavors, projects require team members to be creative, innovative and able to react in a timely manner to surprises. I don’t see automation being able to inspire the level of engagement and follow through required to deliver even moderately complex projects.

What I do expect is that A.I. advances will provide much richer decision support than is currently possible. Whereas there are specific use cases for such technology today such as estimation and forecasting within specific industries, I feel the scope of such support will increase as A.I. tools are able to proactively harvest relevant data sets, process those in real time, and provide probability-based forecasts on the relative merits of different options.

I also am confident that A.I. will be able to substantially (if not fully) eliminate rote, administrative work from the role. As the tools learn how a given project manager works, the quality of auto-generated reports and responses will improve. Similarly, A.I. will help to keep teams safe by providing guidance, evidence gathering and documentation capabilities for compliance and governance purposes.

And I view this as a good thing as it means project managers will find themselves with much more time to focus on analog activities such as engaging effectively with their key stakeholders, building high performing teams, and keeping their eyes on the road ahead rather than spending half or more of their time looking in the rear view mirror.

And that will make the profession that much more rewarding to its practitioners.

(If you liked this article, why not read my book Easy in Theory, Difficult in Practice which contains 100 other lessons on project leadership? It’s available on Amazon.com and on Amazon.ca as well as a number of other online book stores).

Can someone be a Product Owner and Agile Lead for a single team?

A question was posed on my Mastodon instance this morning about combining the roles of Product Owner and Agile Lead (e.g. Scrum Master). The requestor felt that this was a bad idea but wanted to get feedback on whether it was, in fact, possible to do so and under what conditions would it not cause problems.

To answer the question, we need to understand the responsibilities of each role.

The Product Owner has the responsibility of collaborating actively with stakeholders to help them prioritize all the potential needs and wants which might be addressed by the product or service. They are also expected to spend significant time working with the delivery team to ensure they have a clear understanding of these needs and wants and to provide ongoing feedback on product ideas and completed work items by the team.

The Agile Lead is responsible for supporting the team in becoming as effective and efficient as they can be. While the role might facilitate delivery events (e.g. daily coordination events) for the team, their greater value is in the positive changes they are able to catalyze outside of these events. While they are expected to have sufficient delivery expertise to advise the team when they need assistance, the team is expected to define their way of working.

Based on these two sets of responsibilities, there are two main concerns with having a single individual play both roles: knowledge and capacity.

An effective Product Owner is expected to have sufficient product domain knowledge and organizational awareness whereas an Agile Lead is expected to have sufficient breadth and depth of delivery experience. It is rare to find an individual who ticks all of these boxes.

Most of the Product Owners I’ve worked with are overwhelmed just in their roles with the responsibility of spending enough time engaging with stakeholders and understanding product domain changes along with supporting the team daily. Adding the Agile Lead responsibilities to this mix usually means something will slip which could result in valuable input into product feature prioritization being missed or the team being neglected.

So is there any circumstance where the roles would be combined?

When a new company is formed, unless the leader has sufficient confidence, funding and foresight to fill positions appropriately right away, it is common that the leader plays both roles for at least the first product or service launch. However, in most situations, as the company grows, the leader recognizes fairly quickly that they need to step out of the daily tactical work of delivery and will staff the two roles.

Are there other contexts where you’ve seen this work? If so, leave a comment below…

(If you liked this article, why not read my book Easy in Theory, Difficult in Practice which contains 100 other lessons on project leadership? It’s available on Amazon.com and on Amazon.ca as well as a number of other online book stores).