The N2D Method is a system for deciding what to do next. It brings simplicity and clarity to the challenge of prioritizing initiatives in complex circumstances.
Algorithmic decision-making model based on jobs-to-be-done
The N2D Method is a system for deciding what to do next. It brings simplicity and clarity to the challenge of prioritizing initiatives in complex circumstances.
I've been using it across a couple of projects now, and it is great at removing some of the bias out of the prioritisation process. Jess and Phil are supportive and responsiveness - a tool made by practitioners for practitioners.
If you jobs to be done it's brilliant at prioritising between different stakeholders AND making sure he loudest erson in the room doesn't have an outsized impact on decision making
I first used N2D as MD of a development company that was being asked to build increasingly complex products, systems and transformation plans and we didn't always know; a) if we were 'answering the right exam question', b) how to prioritise the user needs and c) what functions or features to prioritise. This was a few years back – I used an earlier version of N2D that Phil had been developing for some years already. Our clients loved it and it gave us clarity and confidence, also helped us to up
Hi Product Hunt! Long-time fan but this is my first maker post 😬 I designed the N2D Method because people aren't great at making decisions, especially if the situation is complex or there are lots of opinions involved. People are subjective and biased - it's not our fault, it's just the way we are. The situation gets worse the more people are involved. It can get noisy and frustrating. On a complex project, it can sometimes feel like you're pushing water uphill, right? I believe that the purpose
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.
Check the similar products section on this page, or browse the category pages linked in the tags above. Each category page shows all products for a given year, sorted by engagement.
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.
Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.