‘Success is a menace, it fools smart people into thinking they can’t lose‘.

– Bill Gates

Taken from one of my favourite movies of all time, ‘Pirates of the Silicon Valley‘ The profoundness of this quote that the character who played Bill Gates said to Steve Ballmer got me thinking. To give you context, Bill Gates and Steve Ballmer were at the time negotiating a deal to license an OS to IBM. IBM had just decided to enter the personal computing market to compete with Apple and had approached Microsoft to acquire an OS to run their first line of personal computers. IBM’s executives negotiating the deal were confident that their future business model would be in the sale of hardware, a business they were very familiar with and dominant in. Instead of acquiring the OS, they agreed to Microsoft’s terms of a non exclusive license of Microsoft’s OS to IBM. This allowed Microsoft to retain ownership of their OS while also technically giving them the ability to sell to IBM’s competitors in the future. IBM realised the folly of this decision when they soon found themselves battling for survival in a crowded PC market where the reducing cost of hardware left it unable to compete against cheap competing clones that also ran MS-DOS.

Bill Gates had sensed IBM executives’ lack of knowledge of the emerging software industry and the IBM executives’ own sense of overconfidence and used this against them to pull off an audacious sleight of hand licensing deal that made him one of the world’s richest men. IBM’s executives’ never caught up to, what in hindsight, was the worst deal in computing history until it was too late. IBM was so successful at the time and they never even considered that they had gifted Microsoft the golden goose.

What influenced them to skip thinking through a decision of such magnitude is what is known as confirmation bias. Bias, a cognitive shortcut that our brain takes allows us to make quick decisions. Bias in itself isn’t inherently bad it saves our brain from melting down from doing so much cognitive processing and is nature’s ways of conserving energy.

The downsides to bias are it tends to suspend cognitive processing and let people rely on these shortcuts for making critical decisions. People in product are routinely exposed to strategic decisions which can have a big profound impact on the outcome. However, leveraged well, biases can be used by people in product and used as a tool to influence product acquisition and engagement. That is however material for a completely different blog post. Some of the most common biases that affect both business strategy and product development are listed below:

Business strategy biases:

Confirmation bias
This bias shows up with giving more weight to information that is consistent with our own beliefs and experiences while discounting any information that contradicts it. A good example of confirmation bias is seen in many right wing groups that consistently refute any evidence no matter how strong it is that contradicts their belief.

Overconfidence bias
This bias shows up as an over estimation of our own abilities. In IBM’s case, its executives were so confident of their success that they never gave much thought to the licensing deal that they signed with Microsoft. This condition loosely overlaps with another related bias called the Dunning Kruger effect. A study discovered that competence and confidence in some individuals were actually inversely proportional. The more incompetent they were the higher was their level of self confidence. There is no one who is a better example of this bias than Donald Trump.

Product biases:

Bandwagon effect
The tendency to settle in and copy what everyone else is doing usually does mean you’re safe however this can also end up having a ‘me too’ product with no clear competitive differentiator. Knowing when to balance a feature that is required for your product while also having a competitive differentiator is key to creating a product ‘USP’.

Loss aversion
Sometimes carrying on with a failed idea can seem to be more tempting that abandoning it and using that energy into a new pursuit. This is caused by a loss aversion bias because of the emotional attachment and toll of having sunk time and effort into it. This can be seen especially with developers who may have spent a long time on a feature that is past its use by date any results but continues to invest time and effort in it.

Law of instrument
“To a carpenter with a hammer everything looks like a nail”. This can sometimes be seen from product people that have competencies in a different discipline and tend to rely on the knowledge they have acquired in that background. For example a product manager with a technical background may tend to be more reliant on using a technical solution to solve a problem over design thinking.

Base rate fallacy
We tend to ignore general information and tend to focus on specific cases in isolation. Sometimes quantitative data alone may not be good enough and may require qualitative data to get the full picture for evidence. This can be seen profoundly in Marissa Mayer’s 40 shades of blue experiment where she insisted on using quantitative data over trusting a designers intuition, honed through years of experience.

Authority bias
We attribute greater weight to the opinion of a person in authority than someone lower down the chain. This is a tough one to go around especially in company with well established hierarchies. This is why more startups are beginning to adopt flatter structures to reduce the effect of this bias on decision making.

Belief bias and Disconfirmation bias
This is where we are more likely to accept an argument in favour of us while rejecting counter argument. This is strongly tied to a person’s own ego and insecurity. So this can be a hard one to check and leave at the door unless you’re very self aware. The most effective way to get past this as a bias is through lean UX techniques that creates a culture of experimentation with the intention to learn.

Curse of knowledge
When we are experts in a field we automatically assume that others may understand what we already know. Sometimes explaining to developers or designers the intended vision and strategy allows them to align themselves and deliver better rather than just asking them to execute a piece of work.

Planning fallacy
We tend to underestimate as product managers the time it takes to complete a task. It’s one of the biggest reasons why projects get delayed and deadlines are missed. The effort taken to create possibly jointly with a Business analyst or a developer a well defined story will offer a higher fidelity of detail to assess what the real effort is likely to be.

Parkinsons’ law of triviality
We tend to waste time on trivial stuff and ignore the big looming issues. As Product Mangers, a lot of this is unintended as we get deeper into the product details or have fires to fight, however reprioritising your own tasks based on the vision can make a significant change where you need to spend your time.

The Ostrich effect
We deliberately avoid negative information hoping bad feedback will disappear. The best thing to overcome this is develop you own sense of empathy and live in your customers shoes and see what they are struggling with, that could well possibly be a fix that could make a significant impact to any of your golden metrics.

Blind spot bias
If you’ve read through this list and begun thinking you’ve seen this in others. It’s possibly because you haven’t seen them in yourself. Learning to be aware of your own biases is as important as checking these in others.

Bias can be tackled at a cultural level by ensuring diversity in a team and allows divergent thinking to be a norm. One tip on when to think things through to allow for a deeper level of cognitive processing comes packaged as a great tip from Jeff Bezos’ letter to shareholders. ‘Take time over decisions that have a big impact, spend very little time on decisions that have a minimal impact’. That will free up your cognitive processing to concentrate on the big decisions.