Why Startups Run Such A Rocky Unpredictable Course

It would be great if investors could develop a formula to be able to determine which startups will be successful. We’d become rich extremely quickly, and wouldn’t have to waste so much money on those which fail. One would expect that over so many years, after investing so many billions of dollars in startups, the super-smart people who run venture capital firms would have been able to come up with a formula for success, so that we could determine which startups we should be investing in.

However, the fact is that we still don’t know which startups will do well. A lot of it is still hit-and-miss, and most investors will accept that there is a major element of relying on gut-feeling when they decide which startups to back. This is not because investors are stupid – it’s just that startups are complex adaptive systems (CAS), which means they are unpredictable and unknowable.

Two of the most prominent properties of complex systems are self-organization and emergence. This means that no individual agent in the system (either the founder or the VC) is able to control the outcomes in the system, as these are a consequence of interactions within the system. Complex systems by nature are unpredictable and generate surprises, which is why investing in them can be such a roller-coaster ride.

The startup ecosystem has lots of players –  employees, customers, other startups, investors, large companies, established competitors, government policies and regulation. The complexity relates to the unexpected emergent behaviour of the overall system which can not be predicted from the behaviour of an individual player, nor understood by decomposition of the system. In a complex system, cause and effect follow a non-linear relationship where small changes  can potentially have a big impact. This is why complexity has been dubbed the “science of surprise” and startups have surprised lots of established players in a variety of markets – for example, the Apple iPhone disrupted the incumbent mobile phone players; and Google transformed the advertising industry.

Paradoxically, a startup has no command and control structure, so that even though it may seem that the founder is in charge, in reality it is the initial core group of early employees who are forced to create rules and make things up as they to run the business on the fly. Execution as learning becomes the DNA of successful startup cultures, because there are no readymade processes which they can follow. This is why startups follow a chaotic process of discontinuous growth, and the glue which holds them together is the vision and passion of the founder, which guides the activities of the employees during their early journey.

Complex adaptive systems are dynamic self-organsing systems which are able to adapt in and evolve with a changing environment. This is one of the strengths of a startup, which gives it the agility, resilience and flexibility it needs so that it can be far more innovative than a traditional large company.

Complex systems seem to be always teetering on the edge of chaos – and this is a feeling I am sure lots of entrepreneurs can identify with! The dynamics of a complex adaptive system combines both order and chaos, which means there is bounded instability that is characterized by a state of paradox: stability and instability, competition and cooperation, order and disorder.

Complexity theory provides a new perspective through which we can observe the development of new business startups because they do not follow the standard linear life cycle theory of the growth of a mature company. This is why startup founders need to embrace chaos, encourage experiments, and tolerate mistakes. Given that no one is in charge of a complex adaptive system, the management approach should emphasize collaboration and agility to create desired outcomes.

Atul Gawande  points out that complexity theory divides problems into three general categories: simple, complicated and complex. Simple problems are ones in which the inputs and the outputs are known, and you simply need to follow a set of rules – for example, you use a checklist to make sure your tax returns are filed properly. Complicated decisions involve significant uncertainty. In these situations, the solutions may not be known, but they are potentially knowable, but it can take time and money to find them. Some startups will get tripped up by these because they run out of cash when they get to this stage. Finally, complex situations are those in which the formula for success is unknowable. While you may use rules of thumb to try to improve your chances of success, you do not know what will work, and cannot predict the outcome. Being a parent is a good example. You can raise children using the best evidence-based rules, but you can never be sure how they will turn out!

The problem is that most investors think of a startup as being a complicated system, while it is really a complex system. This is why they expect that the entrepreneur should be able to deliver controllable and predictable outcomes if the proper processes are put in place properly and the founder runs a tight ship. They assume that an intelligent analysis of past events improves their capacity to predict future events. The truth is that in complex environments that change all the time, we cannot anticipate all situations and we cannot pre-design a system that is always guaranteed to work – all we can do is experiment and correct course intelligently, by trying to fail as quickly and  cheaply as possible, until we stumble across what works.

Startups are complex systems, and we need to learn to be humble, and not assume that we have all the answers, just because we are domain experts or have tons of money. The best approach to supporting a startup is to accept that everyone is equally clueless but well-meaning, and allow the founder to try something that seems to make sense, based on his knowledge, your instincts, and the available data. You must then jointly measure the results and often repeat the cycle many times in search of the best possible outcome.

Now I am not advocating that investors take a nihilistic “chalta hai”,  anything goes” attitude. After all, as parents, even though we know that we cannot control how well our children will do in life, we do our best to provide them with a high quality education ; and do set boundaries until they are mature enough to make their own decisions.

Complex adaptive systems produce novel, creative, and emergent outcomes, which we cannot predict or control. Investors who understand how complex systems work drop the burden of trying to control the founder and instead focus on the small actions they can take to influence patterns of interaction. If we understand our limits, we will be able to do a better job!

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