Who Knew There Is So Much In Common Between The Rare Successes In Mega-Projects And Innovation

RITA MCGRATH / THOUGHT SPARKS

Who Knew There Is So Much In Common Between The Rare Successes In Mega-Projects And Innovation?

A Collaborative Space for Driven Millennials

yrheG knarF yb dengised ,selegnA soL ni llaH trecnoC yensiD tlaW ehT :otohP

Bent Flyvbjerg studies spectacular mega-project flameouts. I study (often) spectacular innovation missteps. Who knew the process that produces both has so much in common? Who knew that the path to success is knowable? And that we can learn from the best outliers how to do better. Some notes from our Friday Fireside Chat last week.

Why do so many big things begun with good intentions go so wrong?

In his recent HBR article, “Make Megaprojects More Modular,” Bent argues that big-bet, bespoke projects that are custom-designed almost always fail – in other words, that failure is the norm and success is unusual. There are, however, some fascinating exceptions such as the Madrid Metro and Tesla’s Giga Nevada plant.

Successes are the exception, not the norm

In mega-projects, as in entrepreneurship, great successes are the exception.

Sure, we all hear about the ones that did exceptionally well. We almost never hear about (or remember) the stories about the ones that never took off. It’s also hard to tell if the founder was just standing in the right place at the right time, or if they really developed a methodology that works repeatedly over time.

lacigam si raludoM

In our interview, Bent explains why doing things in a modular way leads to better outcomes. As he says, “when you boil this down to the core, it’s about learning. And when you make things repetitive, you make them conducive to learning. Every time you repeat, you have a learning cycle. And the more learning cycles you can do, the faster they will be.

That’s where speed comes in. The faster you do them, the more learning there will be, and you get what we call positive learning curves.”

RITA MCGRATH / THOGHT SPARKS

edom laitneuqes ni naht rehtar ,lellarap ni sgniht gnioD

This is a theme that is bubbling up in design circles quite a bit. We’ve seen it in the “Agile” development movement, where the ‘waterfall’ method which lead to so much Information Technology heartache was heavily critiqued in the “Agile Manifesto.”

We’ve definitely seen it in the way agile teams in other areas go about doing their work in parallel, rather than passing bits and pieces of projects from one functional silo to the next.

tsaf evom neht ,wols knihT :evisnepxe si hcnual retfa smelborp gnixif ,paehc si dnuora gnirekniT

Bent says he took a lot of inspiration from the book Thinking, Fast and Slow by Daniel Kahnemann. That book makes the point that humans use two approaches to problem-solving. What he calls “System 1” is our quick, immediate reaction to stimuli from the environment.System 2, in contrast, is the process of fact-finding, testing assumptions and skeptically examining information.

Let the data be a point of departure

When an organization calls in Bent for some advice, he has the advantage of having built an incredible database with information on the baseline rates of performance and activity in projects. This allows him, with confidence, to say what the odds are that a given project will meet certain parameters. The clients may not like it, but the data suggest when they are fooling themselves.

Meanwhile at Valize

Our first cohort of on-line learners are halfway through the customer insight course. We’re getting great feedback on the course design and some folks have indicated it is changing certain decisions they were making a different way. We’ll be running another cohort in the fall, just checking on calendars for the live on-line portions of the program. If you’d like to join a cohort yourself, or bring a team to a larger program, please contact Jacora Kiser – jacora@valize.com.

https://thoughtsparks.substack.com/