We are constantly making decisions and I'm not talking only about work. How many pizza slices to order, what song to listen to while jogging, or what movie to watch on Friday… how many times have you chosen a cheesy and predictable RomCom? I'm not judging, but that was probably not the best decision… well, we are humans, and we make mistakes. In business the same happens, constantly making decisions will lead to some errors. Product prioritization frameworks will help you make more faster and effective decisions.
What are product prioritization frameworks?
We can think of it as a way to decide which products and features will work. Product prioritization decisions take into account customer expectations and business goals. Product prioritization frameworks are the way to achieve this. These frameworks guide a process of weighing variables for possible initiatives, helping you not to commit any essential errors that might clutter your work. PPFs are also very useful for reducing work time and making better use of your time. Product prioritization allows teams to make more objective and tactical decisions. Now we will go through 3 of the best product prioritization frameworks, however, these can not be followed o closely. These don't make the decisions, they are just a tool to help us accelerate and maximize our decision-making process.
The top 3 product prioritization frameworks
Value vs effort
Probably the simplest way of product prioritization. This method consists of making a list of your features and initiatives and comparing them based on their value and effort scores. The results will show a pretty precise estimation. This will help you know if that feature will help you achieve your goals and if you can realize it with the capacity and resources at your disposal. This framework will give you and your team the possibility of visualizing the pros and cons of every feature. Having the quantified value and effort values will also make room for group feedback and discussion. Roadmunk offers prioritization templates, one of which is Value vs effort.
Pros
- It's good for getting rid of assumptions. Quantificating value and effort scores will help you and your team visualize the importance of features in a much more rational and objective way. Of course, there's still room for subjectivity, but numbers will facilitate and shorten the discussion process.
- It's extremely easy to use. Without formulas, graphics, and complex math; value vs effort gives every team the possibility of having product prioritization.
- If your company has limited resources, this model will help you take the most out of these.
- It's flexible for any industry. Different types of companies have different concepts of value and effort. This framework can be used by any company.
Cons
- It's very estimated. Even though we will get some pretty clear results, these only show a not-so-accurate and precise score.
- It isn't suitable for large companies.
Kano
The Kano model consists of a cartesian graphic in which the X-axis represents the implementation values and the Y values represent the consumer's satisfaction. The implementation values can be seen as “up to what degree a customer's need is met” and there are 3 types. The basic features are those that if you don't have the customers won't see your product as a solution at all. The performance features have a positive effect on customer satisfaction. And lastly, the delight features are those a customer doesn't expect and create an exciting response. But how can you gather this information? with the so-called Kano tests. These are questionnaires where your customers will tell how would they’d feel with a certain feature.
To put it simpler, this feature prioritization framework states that the more you invest in improving features on the implementation values the higher your client satisfaction will be.
Pros
- Pretty accurate results that let teams make solid market predictions.
- Allows teams to understand what typical features are no longer useful
- Allows teams to discover underrated features
- It can generate a remarkably high level of delight in customers.
Cons
- Not suitable for short terms. It's a time-consuming process, the data gathering will take several weeks.
Buy a feature
This product prioritization framework is by far the most interactive one. In this role-play-type method, you'll be able to quantify how much features can be worth. The game has the following steps:
- Choose a bunch of features and assign a value to each one. This value must be influenced by the resources you and your team will have to spend.
- Gather around 7 people. These will play the role of our customers.
- Give your “customers” a set amount of fake money.
- Tell these people to spend their money on the features they prefer. You must be aware of how much money all the participants spend and on which products. Some might distribute their capital between different options, and some others might go all-in on just one favorite feature.
- Ask them to justify their decisions. “Why did they spend that much money on this one?” “Why not on this other one?” “Why more on this one and less on that one?” Feedback is fundamental for achieving good product prioritization.
- Make a list of the features in order of how much was spent on each.
Pros
- Making up these scenarios might generate a very honest and natural response from the participants.
- It's an innovative idea that's ideal for finding new and unique information.
Cons
- Might be difficult to organize.
Final thoughts
We are constantly making decisions and sometimes we make mistakes. Product prioritization help with the precision and simplicity of decisions. They help business teams decide which features will be more effective by taking into account different elements such as value, customer expectations, and more. There are other types, however, value vs effort, kano, and buy a feature are some of the key elements. Each one has its advantages and disadvantages but they all are pretty simple ad bring good results. After all, product prioritization frameworks are a key tool for any company that wants to upgrade its efficiency.
