The average adult makes approx 35,000 decisions every single day. I would argue decision-making is as core to being human as breathing itself. Not all decisions are conscious or have the same impact on our lives. Some require deep thinking (like career choice) while others are almost second nature (like making coffee in the morning).
I’ve spent most of my last two years thinking about how to think better. That’s a muscle I try to build as a Product Manager. To think of creative ways to define problems and find the optimal way to solve them. To prioritize among an ocean of tasks for the team. To make several micro-decisions that steer the direction in which the product grows.
Is there one good way to think about decision-making? Given the number of variables in the real world, every decision needs a different recipe to suit the taste of the situation. There is no panacea for complex decision-making. But concepts from functional fields such as design, programming, philosophy, mathematics, etc. can help come to a well-thought-out decision at the very least.
I came across an interesting concept called “Bookending” in the book Decisive by Chip and Dan Heath. Bookending suggests considering the best and worst-case potential outcomes of a decision or a connected series of decisions (for example - a project initiative).
The idea suggests laying out the best and worst-case scenarios of the decision and then working backward to move closer to the best-case scenario and away from the worst-case scenario. Doing so helps better grasp the risks involved. Seeing the best possible future shows all the good things that would follow and the worst possible future surfaces everything at stake.
“The future is not a ‘point’—a single scenario that we must predict. It is a range. We should bookend the future, considering a range of outcomes from very bad to very good.”
Best comes first
Say, you’re gearing up for a new product launch. Your team has been working on the beta version for 6 months. The deadline is two months away. 👀
Begin by envisioning the most favorable and hopeful outcome. This exercise not only motivates you but also clarifies what you truly desire.
👉 Your product launches. Users love it. There are very few bugs. It goes viral. You get more users than expected. They have queries about using the product. Some users want bulk pricing. The idea seems to be catching on…
Will your infrastructure be able to handle a potentially high influx of users?
Can you set up a knowledge base for internal and external FAQs?
How would you capitalize on this traffic? A simple email workflow to onboard the new users perhaps…
Worst comes next
Now think of everything that could go wrong despite the decision. While this may seem daunting and even unnecessary, it can surface risks and fears that can help improve certain aspects of the decision itself.
👉 Your product launches. Users complain that the site is down often. You find a lot of bugs. The product doesn’t seem to be picking pace. Your users can’t find their method of choice available for payment on your platform…
Can you define a process to user source bugs, log, and prioritize them?
What can you do about preventing downtime?
Is your payment gateway flexible enough to add payment types in the future?
What are some of the guerilla tactics you can use to spread the word and keep building traction?
Finding Middle Ground
Knowing what you now know - consider unknowns and risks. A simple framework for a product launch situation would be to use the Kano model. Place each missing piece in one of three buckets: must-haves; satisfiers/performance factors; delighters/wow factors. And then prioritize in that order (barring exceptions).
The goal would be to push towards the best case and set reasonable expectations given inevitable trade-offs. This is where wisdom meets whimsy.
Bookending as a concept is simple yet powerful. It gives you space to surface fears and face the unknown. In the next article, I will discuss Premortems, a fascinating and practical technique used in project management but also very helpful in big life decisions.