Prioritization is key in product management.

That's why we have built a flexible yet powerful prioritization system to help you identify the most urgent customer needs and build the right features at the right time.

In Harvestr, the Product interface helps you get a central view of all the Discoveries you are working on. This view has two main purposes: reviewing your product roadmap and deciding what to build next by prioritizing Discoveries.

Discoveries have several criteria that can be used to evaluate and prioritize them. The default criteria are:

You can also add custom numeric criteria to evaluate Discoveries more accurately and prioritize them according to your business and product criteria. 

Three types of fields can be added to Discoveries:

Numeric fields

Numeric fields let you assign an integer number to all your Discoveries.

Examples of numeric fields: 

Score fields

Score fields let you assign a score from 1 to 5 to all your Discoveries.

Examples of score fields: 

Financial value fields

Numeric fields let you assign an integer number to all your Discoveries.

Examples of numeric fields: 

Display/hide fields

You can choose which fields to display or hide by clicking the "Fields" button.

Once you have added all the numeric fields you need to your Discoveries, Harvestr takes the fields you created to compute a prioritization score that can be used to compare and rank Discoveries.

Weights

First, you must give each field a weight from 0 to 100 according to how much each criterion should count in the final score. To change weights, go to "Manage numeric fields".

The "Score influence" column tells you how much each field weighs in the final score, relative to the others. The bigger the Score influence of a field is, the more it will affect the Score.

If a field has a Score influence of 80%, it means that this field accounts for 80% of the Score value.

Score value

In order for the Score to be easily understandable, we chose to always give you a number between 0 and 100. 

To do that, Harvestr first converts all your fields' values into a number between 0 and 100, for all your Discoveries. How? By dividing the field's value for a Discovery by the highest existing value for this field among all your Discoveries. This process is called "normalization".

For example, let's say I have a financial field where I put the expected additional revenue of a Discovery. One Discovery has an expected revenue of $10,000. Among all my Discoveries, the highest expected revenue is $100,000. Then, Harvestr would give the former Discovery an intermediary score of 10% (10,000 divided by 100,000) for this financial field. 

To calculate the final Score, Harvestr does exactly the same for each field. We then multiply each field by its weight and sum all these values, giving you a final score between 0 and 100.

To give you a complete example, let's say you have 3 prioritization criteria: A, B, and C.

You set the following weights for each criteria: Weight_A = 20%, Weight_B = 30%, Weight_C = 50%

You have the following list of Discoveries with the following values for each criterion:

The value of the final score for Discovery #1 would then be equal to:

The score is always automatically calculated behind the scenes with the fields and weights you have defined. However, if you do not wish to use this score, you must hide it from the displayed fields. 

Once you have set your custom fields and weights, you can use Harvestr's advanced filtering and sorting capabilities to extract a subset of Discoveries according to your needs and to prioritize Discoveries.

In Harvestr, you can filter Discoveries by tags, user groups, states, date created, last updated, last feedback, and numeric fields.

Date and numeric fields can be sorted in a relative way. You can for example filter Discoveries that have more than 30 feedback, or Discoveries that were created more than 14 days ago.

Filters can be added with "AND" / "OR" conditions. If we go on with the same example, you could filter Discoveries with more than 30 feedback AND were created more than 14 days ago.

Discoveries can also be sorted alphabetically and numerically according to the field you want to sort by.

All these filtering and sorting options can be combined to prioritize Discoveries and decide what you should focus on according to your own criteria.

Here are a few examples.

Prioritize trending feature requests from large accounts customers

Prioritize quick wins

Prioritize Discoveries according to customer segments and a multi-criteria score

A specific set of filtering and sorting options can be saved in a View. For all your Views, you can also choose to display Discoveries as a table or as a board.

Here are a few examples of Views you can set up: