Human brains were designed for a world of lateral change. But, as Ray Kurzweil and others remind us, learning-by-trial-and-error systems introduce the potential for exponential change. This has huge implications for how we design and build organizations and systems.
You’re not imaging it – things really are moving faster
Among the most profound shifts facing organizations and their leaders today is that of going from linear change to exponential change. The “exponential” organizational form is radically different than one built to capitalize on linear evolution. Such organizations leverage technology and networks to create impacts that people working in more conventional settings could never accomplish.
A familiar example would be Instagram. Founded by Kevin Systrom and Mike Krieger in October of 2010, the startup appeared at exactly the right time for users to take advantage of high-resolution multi-megapixel smartphone cameras. Its growth in the initial phases wasn’t particularly inspiring – by 2012, the startup only worked for Apple IoS devices, had 50 million users and wasn’t making a whole lot of money. But then in April of that year, Instagram for Android was released. It was downloaded more than a million times in one day, clearly launching the beginning of a potentially meaningful growth curve.
Facebook’s Mark Zuckerberg and his team realized that they were facing an exponential competitor in the connect-with-friends-and-family space. On April 9, 2012, Facebook bought Instagram for $1 billion. At the time, the firm had all of 13 employees.
Facebook turned out to be right about the exponential nature of the Instagram organization. It reached a billion users in June of 2018. By 2024, Instagram was generating $51.4 billion in revenue (almost 45% of Facebook’s total) and had attracted over 2 billion users.
The difference between linear and exponential change
With linear growth, progress proceeds additively. 1+1 becomes 2. 2+1 becomes three. A journey that is to take 100 days will be 1/3 complete after 33, and so on. These mental models are deeply embedded in organizational mindsets and practices. Some of our most tried-and-true approaches to management, such as management by exception or management by objectives posit a “norm” from which deviations represent problems. Such techniques also emphasize specific targets and metrics which people ought to be meeting, making the assumption that such things are knowable in advance. And sometimes they are, as amazing advances in quality and supply chain design has shown us.
With exponential change, on the other hand, changes experience a compounding, for example, a doubling function. 1 becomes 2, 2 becomes 4, 4 becomes 8 and so forth. If we’re not specifically searching for the pattern, exponential change can completely mislead us. In the beginning, very little seems to be happening (indeed, often very little is happening) but the seeds are being planted for a major inflection point in the future. One of my favorite examples is offered by the Washington Post’s Megan McArdle:
There’s an old brain teaser that goes like this: You have a pond of a certain size, and upon that pond, a single lily pad. This particular species of lily pad reproduces once a day, so that on day two, you have two lily pads. On day three, you have four, and so on. Now the teaser. “If it takes the lily pads 48 days to cover the pond completely, how long will it take for the pond to be covered halfway?” The answer is 47 days. Moreover, at day 40, you’ll barely know the lily pads are there.
When planning for the future, in other words, if you are considering the future of your pond on day 35, you probably won’t even notice that the change is underway – unless you are specifically looking for it.
Zuckerberg was right and that’s unusual for incumbent companies facing exponential competitors
People find linear change straightforward to understand. For most of humanity’s evolution, that was all that was necessary. When the biggest challenge you face is a predator moving toward you, figuring out how to get from where you are to some other location makes a lot of sense. Similarly, when the assumption behind organizational design is that of incremental change, it makes sense to build on what we know incrementally. Industrial business models were often defined by their use of machines to create increasing returns to scale and scope, while simultaneously creating barriers to entry.
Everything changes, however, when systems are capable of rapid, trial-and-error learning. Change becomes exponential, rather than linear. Ray Kurzweil is well known for having developed this idea. In a famous 2001 essay entitled The Law of Accelerating Returns, he stipulates that “the rate of progress in any evolutionary learning environment (a system that learns via trial and error over time) increases exponentially. The more advanced a system that improves through iterative learning becomes, the faster it can progress.”. Digitally-enhanced business models create accelerating returns to scale, often without having to leverage much in the way of physical assets.
Examples of exponential technologies are all around us. They include augmented reality (AR), virtual reality (VR), artificial intelligence (AI), robotics, digital biology and many forms of data science. Together, they represent a potentially massive inflection point in what is possible, and consequently what organizations need to be able to master if they are to survive. As Kurzweil put it, “We won’t experience 100 years of progress in the 21st century – it will be more like 20,000 years of progress (at today’s rate).
Will you escape the “rule of 18 months?”
If you are building innovations with the goal of achieving exponential growth, you need to be extremely careful of imposing linear expectations of progress on them. Remember – in the early stages, exponential combinations are tiny and remain that way for some time. Progress looks slow. Results are not immediate. The danger is that projects subject to linear expectations are likely to be dropped or to lose support, even as they may have amazing potential.
Mark Bonchek, founder of Shift Thinking, writing in the Harvard Business Review illustrates the dilemma for conventionally managing projects. As he points out, executives looking for linear-oriented progress get impatient for results too early. Hunger for incremental, immediate results as he puts it can “lead teams to quit the exponential path too soon.”
Phil McKinney, the former Chief Technology Officer of Hewlett-Packard, offers a humorously painful observation on this phenomenon – a concept he calls the “Rule of 18 months.” It states, “A disproportionate large number of projects are cancelled by management at 18 months.” He goes on to explain:
Most projects start mid-year with funding and resources scraped together by management based on the potential merit and impact. When the next full budget cycle comes around, the project is well underway and the funding is all but assured given that it’s been less than a year and no one expects the project to have impact – yet. The result is that resources are kept in place and the project keeps going.
The second cycle is a different issue. When the budget cycle comes around, there are questions raised about the project: Is this project still important? Are there more important projects we should be funding instead? Are we making the progress we should?
As he says, management has a choice: fight to re-justify a project that hasn’t shown concrete results for a second time or simply let it die and eliminate the pain. And no amount of arguing, pleading or “just trust us” from the project teams is going to withstand management that doesn’t see results within the 18-month budget window. McKinney suggests that teams break each project down into 18-month or less deliverables. An alternative approach would be to redesign budget authorizations so that they acknowledge the reality that launching an exponential business might require multiple years. But so far, few firms are this enlightened.
Where from here?
An updated version of the original book Exponential Organizations has just been released – and true to the spirit of finding the best minds and resources to focus on it, it’s crowdsourced! The book would be a great place to start. There is also an accompanying web site which is still under construction, but well worth a look.
Meanwhile, we’re working away on our software intended to help you structure and leverage your own learning journeys, SparcHub. Our next live demo is on February 21 and you can register here.