Starting a new project and not finishing it can be quite a discouraging experience. If it ends up becoming something you tend to do often, you lose the motivation to pursue new ideas and that can be bad.
How many times have you started a project and felt like you should’ve picked another one? What if you have a technique to figure out which idea/project to pick next? You should pick the one that you’re more inclined towards. But, how do you get clarity around this inclination?
It’s extremely important to have clarity on why you want to work on a project, how interested you are, and which technology you want to use. I’ve come up with a technique that I use myself for getting this clarity. It’s simple really.
PIT Score
PIT stands for Purpose Interest Technology. I consider these three as the key factors that provide clarity on which idea to pick next. I’ve tried this technique with a few ideas/projects now and I’m pleased to inform you that it has worked really well.
Who is it for?
- Do you enjoy working on side projects in your spare time?
- Do you have a lot of ideas that you want to work on, but never get around to?
- Do you have trouble prioritizing your ideas?
If you’ve answered “Yes” to the above questions, this technique is for you. Although, it is not entirely just for people that fall in to this category.
How does it work?
The technique itself is fairly straight forward. You assign a certain inclination value for each of the key factors, for each of your ideas and calculate the PIT score of each idea and sort them by the score. Here’s how it is done.
I’ll be using the following list of ideas to explain and demonstrate the technique:
- Learn Machine learning
- Build a web UI for a CLI tool
- Write a fun new game
Step 0: Define inclination values for each factor and assign scores
Each of the key factors i.e. Purpose, Interest, and Technology, need a pre-defined set of values that denote your inclination towards the corresponding idea.
Even though you can update these later, it will be rare.
For Purpose, your inclination values could be:
- Personal use
- Learning new technology
- Help solve a problem for others
For Interest, your inclination values could be:
- Very interested
- Interested
- May be with some external motivation
For Technology, your inclination values could be:
- Very familiar
- Sort-of familiar
- Unfamiliar
These are some examples that I’ve come up with. They can be customized and changed per your needs.
Assign a score to each of these inclination values. You need to be careful with assigning scores since they make or break this technique. You can set up a scale for yourself and assign a score from that scale. In the current example, I’ve used a scale from 1 to 10.
Some example scores are –
Purpose:
| Name | Score |
|---|---|
| Personal use | 10 |
| Acquire new skill | 5 |
| Help solve a problem for others | 1 |
Interest:
| Name | Score |
|---|---|
| Very interested | 10 |
| Interested | 7 |
| May be with some external motivation | 2 |
Technology:
| Name | Score |
|---|---|
| Very familiar | 9 |
| Sort-of familiar | 6 |
| Unfamiliar | 2 |
These are just values that I’ve come up with. These are extremely subjective. So, you’d have to define these values appropriately, according to you. For instance, the scores you’d assign to “Unfamiliar” technology or “Acquire new skill” purpose, might be completely different from the scores I’d assign myself. As you’ll see, these scores play a crucial role in computing the PIT score.
Step 1: Apply PIT values to your ideas
For each of your idea, populate the Purpose inclination, Interest inclination, and Technology inclination values.
| Idea | Purpose | Interest | Technology |
|---|---|---|---|
| Learn Machine learning | Acquire new skill | Interested | Sort-of familiar |
| Build a web UI for a CLI tool | Help solve a problem for others | Very interested | Unfamiliar |
| Write a fun new game | Personal use | Interested | Very familiar |
Step 2: Calculate
This is by far the easiest part. You substitute the scores for each of the values and calculate the PIT score of each of your ideas using the following formula:
PITscore = Pscore + Iscore + Tscore
Here’s how the table would look like –
| Idea | P score | I score | T score | PIT score |
|---|---|---|---|---|
| Learn Machine learning | 5 | 7 | 6 | 18 |
| Build a web UI for a CLI tool | 1 | 10 | 2 | 13 |
| Write a fun new game | 10 | 7 | 9 | 26 |
Step 3: Sort
Sort the ideas by the PIT score in descending order. Voila! Your projects are now sorted by a score that provides clarity on which idea you’re most likely to finish once you start. This is due to the inclination you have towards the project or the idea.
| Idea | P score | I score | T score | PIT score |
|---|---|---|---|---|
| Write a fun new game | 10 | 7 | 9 | 26 |
| Learn Machine learning | 5 | 7 | 6 | 18 |
| Build a web UI for a CLI tool | 1 | 10 | 2 | 13 |
This sorted list provides clarity around the friction you’d face in order to start a project.
Higher the PIT score, lower the friction.
As you have probably noticed, even though the interest level is “Very interested” for the project “Build a web UI for a CLI tool”, the PIT score ended up being pretty low. This is due to the fact that the technology is “Unfamiliar” and the purpose is “Help solve a problem for others”, the scores of which are pretty low in the given example. Just by looking at the original list and assuming that you would want to start with that project would’ve been a mistake. On the other hand, “Write a fun new game” has the highest PIT score, even though the interest level is only “Interested”.
A spreadsheet can be a convenient option to maintain this list and the scores. Bonus, use spreadsheet functions to automate the calculation and sorting process. This is what I currently do. Building a simple web page to handle this would be really easy, but, it had a very low PIT score 😉 and so I avoided it.
Important
In order for this technique to work, you need to be careful while picking the scores for the inclination values.
Extensibility
You can extend this technique to add more factors to your ideas, finer-grained inclination values, and better scoring.
Applying this technique to my personal list of projects surfaced a lot more information about my projects. I was happy with the outcome.