Behavioural Science for Product Managers
Part 1 — Assumptions and Biases
Behavioural sciences explore the cognitive processes within humans and the behavioural interactions between humans in the natural world. It involves the systematic analysis and investigation of human behaviour through the study of the past, controlled and naturalistic observation of the present, and disciplined scientific experimentation and modelling. It attempts to accomplish legitimate, objective conclusions through rigorous formulations and observation. Examples of behavioural sciences include psychology, psychobiology, anthropology, and cognitive science. Generally, behaviour science deals primarily with human action and often seeks to generalize about human behaviour as it relates to society.
Behavioural product management applies behavioural science and human psychology to management. Product managers can apply behavioural science from two perspectives to improve the success of the products that they manage.
The first is about the assumptions and decisions that they make as part of their product management activities. How these assumptions and biases that they have negatively influence the success of their products.
The second is how they can influence and nudge changes in the customer/ users behavior. They can use behavioral science to positively influence the choices that the customers of their products make.
In this post, we will look at the first aspect of how assumptions and biases negatively influence product decisions and hinder the success of the product.
The uncertainty in product development is very high and it makes it very risky. Product Managers make many complex decisions in unfamiliar conditions. They make assumptions about the problems that they are looking to solve. They make assumptions about who their customers are, the problem they are solving for them and the solution that they are looking to build to solve that problem.
They build a story about the problem and solution and work around it. The building blocks are our assumptions. We build our plausible solution and introduce it to customers. When we fail to experience the success we predicted, it is no longer convenient to avoid the truth. We are confused and uncomfortable after being so certain. It is only after this experience that we recognize the ignorance of our own ignorance.
Assumptions
As mentioned earlier, the unknowns while developing a product is very high. Every aspect from the problem statement to the target market to the customer segment is a complete unknown. In these situations, relying on our assumptions and allowing biases to creep in our decisions will prove to be even more detrimental to our product development effort.
If we know that assumptions work out to be negative, then why do we assume. We humans believe that we are perfectly rational beings yet end up making a lot of irrational decisions in our daily life.
In the 1970s Daniel Kahneman and Amos Traversky brought a paradigm shift in the way behavioural economics was looked at. Their work showed that people’s decisions are sometimes flawed because they constantly deviate from rationality. In his book Thinking Fast and Slow, Kahneman attributes this irrationality to the two modes of thinking “System 1” and “System 2”.
System 1 : This is the automatic, fast mode of thinking that is mostly intuitive and comes from your subconscious. This system kicks in when you have an existing pattern in your brain that directs you what to do. For example, changing gears in your car when you have been driving for many years or typing fast without looking at your keyboard (muscle memory).
System 2: This is the effortful, slow mode of thinking that is driven by our consciousness and is controlled in nature. For example — making retirement planning or buying your engagement ring.
We think that we are using System 2 all the time but in reality, we engage System 1 most of the time because it saves a lot of energy compared to System 2. System 1 looks out for existing patterns, information, associations available in our brain and creates a plausible story which might be influenced by our biases. When system 1 is unable to find an answer, it calls for help through System 2.
In humans the sophisticated allocation of attention has been honed by a long evolutionary history. Orienting and responding quickly to the gravest threats or most promising opportunities improved the chance of the survival. Even in modern humans, System 1 takes over in emergencies and assigns total priority.
Whenever we spot a pattern and fill in the missing details from our experience, we feel good about it.
Logically, in these uncertain situations, it would make sense for us to rely on our slow, System 2 thinking. Yet, we only engage our brain this way for about 5% of our decisions.
Biases
Cognitive biases are the brain’s way to shortcut processes to let us act quickly. Biases are a natural adaptation and serve us well in many scenarios. Cognitive biases trick us and skew our view of the world in ways that are proven to be anything but rational.
As a product manager it’s crucial that we are aware of these biases. It is impossible to completely get rid of the biases as many of them are hardwired in our brain and driven by our subconscious mind, but we can try and reduce their impact on our daily decision making. There are more than 100 cognitive biases, but I would like to highlight some of them.
1. Availability Heuristic
One of the essential biases to understand as a product owner. It is ‘the perception of importance or likelihood based on recent events’. An example would be, you see blanket coverage in the news about a plane crash, and you perceive the threat to be higher for air travel. The facts are that the risk has not changed, but the availability has altered your perception.
2. Confirmation Bias
The tendency to use, search for, interpret, weight and remember information that confirms your pre-existing beliefs. To counter this, you have to look at the fundamentals of the scientific method, to gather data in an unbiased manner.
3. Fundamental Attribution Error
Our tendency to attribute a negative outcome that relates to others as being down to their behaviour but to relate the same outcome of your own performance to circumstance.
4. Dunning-Kreuger Effect
‘You don’t know what you don’t know’. The Dunning-Kruger effect is a bias where a person with low ability, by definition, is not able to see their lack of ability and is also unable to see genuine ability on others. The same bias affects people with very high levels of skill in that they are often unable to get their point across as they are not able to perceive people would not have the same knowledge. This bias is impossible to see in yourself.
5. Not Invented Here
Our tendency to view ideas, technology etc. created in-house to be superior to external items. It has also been called the ‘reinvent the wheel syndrome’. Its often more exciting and may look cheaper to ‘roll your own’ but whenever internal and external selections are evaluated alarm bells should ring. Good research and data is the key here along with views external to the team to alert you to any bias issues.
6. Loss Aversion and the Sunk Cost effect
Humans have been proven to be loss averse so decisions based on loss or gain will not be made well unless you decide to plug them into Excel. In product management too often people look at what we have already spent as a reason to continue spending whereas we should remove any sunk cost from the equation.
7. IKEA Effect
A bias where you place a disproportionately high value on things you helped to build. In the product and development areas, I hope it’s obvious why we need to counter this bias. Products could easily be, for many people, ‘their baby’ and no one wants to throw the baby in the trash. Clear data is key to countering this although the biases above show that’s a fraught minefield in of itself. Outsiders and ‘devils advocates’ are critical to helping here. Understanding bias, in general, has helped me with this particular issue.
How to manage these assumptions and biases
It is very important to have healthy debates and create an environment in which opposing viewpoints thrive. The assumptions should be tested and based on that validated before being worked on or accepted.
Bias exists because we do not ask the right questions about our beliefs and hypothesis. Five Whys helps drill down any wrong assumptions that we might have taken. Also, so deliberate thinking would help in overcoming many of the biases that creep in unconsciously.
Decisions that are based on data will help to validate a lot of the assumptions that we make. This will help make better product decisions before building a product or after a launch. The KPIs set before building a feature is very important to avoid confirmation bias. The Use of scientific methods such as AB testing and Usability testing to gather feedback and data to drive decisions instead of irrational emotions. It would be helpful to keep the common objectives in mind and keep a tab on our ego. This will help in overcoming a lot of biases and also jumping to conclusions based on assumptions.
Good product managers do not base their decisions only on assumptions and hypothesis. They use experimentation/ testing and discovery processes to validate their assumptions and hypothesis. They use data-based decision making to ensure that only validated assumptions are used in their decision-making process. They also use the processes, metrics and environment is there so that the biases do not creep in compromising the overall product objective.
