steve-10
While we - human beings - like to think of ourselves as rational creatures, the truth is we are anything but.
We are prone to over 100 cognitive biases that may subconsciously shape our perceptions, beliefs and decisions.
As one might imagine, innovation and entrepreneurship are not immune from said biases.
In this post I’ve unpacked 36 cognitive biases that can stifle your innovation efforts, how they might apply to the field and a proposed solution or mitigant for each.
The tendency to avoid options for which missing information makes the probability seem “unknown”.
In innovation: today’s business world is more volatile, uncertain, complex and ambiguous than ever, thanks to exponential technology growth bringing with it low barriers to entry and business model innovation.
Management decisions tend to be shrouded in certainty — “if you fail to plan you plan to fail” is the old adage, and while a certain degree of planning is of course necessary for any venture, over-planning in order to feel in control, is something traditional project management such as the waterfall method teach us. It’s something business cases are designed for, to give decision makers a sense of control and certainty.
The problem with this is that it supports pursuing only that which we can reliably predict which is normally incremental, Horizon 1 innovation.
To truly innovate and stand a chance at surviving in a tumultuous environment, getting better at embracing uncertainty is key.
Solution: Introduce a process that supports taking many small bets to test uncertain assumptions. _For more on this topic read: _The Business Case Alternative — How to Support Uncertainty and Disruptive Innovation at Large Company
The tendency to rely too heavily, or “anchor”, on one trait or piece of information when making decisions (usually the first piece of information acquired on that subject).
In innovation: this is notoriously common during typical corporate brainstorming sessions, particularly where dominant personalities speak up first. What usually happens is everybody else usually anchors their ideas around this first ‘big idea’ rather than coming up with something completely new.
Solution: To combat this ensure people ‘work alone together’ first by writing down their ideas individually, grouping similar ideas and then voting on them in silence before engaging in a wider group discussion.
For more on brainstorming techniques check out How to Run an Ideation Session
The tendency to attribute greater accuracy to the opinion of an authority figure (unrelated to its content) and be more influenced by that opinion.
In innovation: Often manifests itself as HIPPO or highest paid person’s opinion.
See Overconfidence bias below.
For more on hippos, listen to episode #53 of the Future Squared podcast with former Sportsbet head of innovation, Leslie Barry.
A self-reinforcing process in which a collective belief gains more and more plausibility through its increasing repetition in public discourse (or “repeat something long enough and it will become true”).
One need not look any further than long held social institutions that trace back to a time when people thought the earth was flat.
The reaction to disconfirming evidence by strengthening one’s previous beliefs.
In innovation: Working in the corporate innovation space, I’ve lost count the number of times we’ve run experiments that disprove a sponsor’s initial thinking. More often than not, they take this in their stride and pivot accordingly. However, every now and again, after a company has engaged us to test their assumptions with target customers — and invested both time and money doing so — we hear something like this, and I provide a sanitised quote:
“Company X has decided to accelerate its efforts in respect of Product X and create an enterprise wide program that will touch every facet of our business above and beyond Product X; product and pricing design, operations, corporate social responsibility, brand and reputation, employee engagement and legal and regulatory lobbying.”
What?
We just learned that the market has no appetite for your idea and you’re not only going ahead with it, but ramping up its size and complexity significantly? Okay…
The tendency to do (or believe) things because many other people do (or believe) the same.
In innovation: Whether it’s companies simply copying what every other company is doing in the innovation space or whether it’s individuals falling into groupthink and agreeing, or building upon, the idea of others in a group.
Just because Britney Spears has sold over 100 million albums, it doesn’t mean her music is any good.
*Solution: *On how to avoid the bandwagon effect in ideation and brainstorming sessions, read How to Run an Ideation Session.
The tendency for people to appear more attractive in a group than in isolation.
In innovation: People seem to be somewhat enamored by the startup ecosystem and meetups and conferences that draw hundreds of people. But take the time to individually meet people at such events and you will quickly realise that, oftentimes, 90% of attendees are either from a corporate trying to sell something, recruiters looking for hires or wantrapreneurs that haven’t and probably won’t ever build anything.
*Solution: *As the great Roman Emperor Marcus Aurelius noted in his journals, “when things have such a plausible appearance, show them naked, see their shoddiness, strip away their own boastful account of themselves. Vanity is the greatest seducer of reason: when you are most convinced that your work (or the work of others) is important, that is when you are most under its spell.”
*Translation: *Observe things at a granular level to see them for what they really are and not let emotion cloud your judgment.
The tendency to search for, interpret, focus on and remember information in a way that confirms one’s preconceptions.
*In innovation: *Whatever your opinion about whatever the topic, you’ll find data that supports it. However, you will probably find lots of disproving data too.
And you will find that in most cases, there is a correlation between X and Y in the data, it doesn’t necessarily mean that X causes why.
*Solution: *When building experiments to test your assumptions, always ensure that your hypotheses is:
Or to borrow a leaf from the Hypothesis Kit, below:
1. Because we saw (qual & quant data)
2. We expect that (change) for (population) will cause (impact(s))
3. We expect to see (data metric(s) change) over a period of (x business cycles)
The tendency to test hypotheses exclusively through direct testing, instead of testing possible alternative hypotheses.
In innovation: An example of this might be testing a pricing model of, say, a $10 a month subscription service.
You might discover that 7% of your website visitors agree to pay this and with a target metric of 3% you’re ready to move on and implement this pricing model.
Or are you?
Have you tested other price subscriptions? Maybe people are willing to pay $20 or even $50 a month for the value your product delivers?
Or maybe there’s a better pricing model? Up-front pricing, value added pricing, scaled transactions, freemium, licensing, metered use, membership and countless other models might be more financially rewarding in the long run.
*Solution: *identify all key and high risk assumptions underpinning your idea or business model and test all of these assumptions before forming any conclusions on the best path forward.
The tendency to revise one’s belief insufficiently when presented with new evidence.
In innovation: See Backfire Effect.
