Scoring, or grading, is probably one of the most challenging and confusing parts of the OKR framework.

πŸ”· Current most-known scoring techniques πŸ”·

Problem

Current techniques, like only using binary scoring (0/1, True/False) or Google's (0, 0.3, 0.7, and 1.0), can be too simple or too subjective and often illogical. More often than not, without an upfront agreement, the event at the end of the OKR cycle can be messy and harm the OKR adoption process.

πŸ”· Upfront agreement πŸ”·

The major difference from existing practices is that you agree with the team members on scores upfront - at the time of drafting the Key Result.

πŸ”· Predictive scoring πŸ”·

I would also suggest using a predictive indicator to keep unpleasant surprises to a minimum at the end of the cycle. When you create a Key Result, it is only natural that your confidence is high. During the recurring check-ins, when you debate the progress, you should mark the confidence level to be different, less optimistic, if the circumstances paint that picture.

Using predictive indicators is a great technique to focus your efforts, change expectations, or even abandon the attempt to complete the Key Result.

The credit for the "Pre-scoring" goes to Ben Lamorte which inspired some of my work on the Agile Tools digital OKR platform for team-oriented modern organizations where there is no room for personal OKRs. #Accountability is achieved within the team

OKRs part 2

Besides confusing Google-style grading, as they call it, that includes using numbers 0.0, 0.3, 0.7, and 1.0, there is another style of scoring that is probably the most popular: binary, a Yes/No (over)simplistic system.

A few examples of alternative systems

πŸ”· No Scoring πŸ”·

The use case for the "No Scoring" scoring type is just for the cases where you want to establish a baseline. When you do not know the initial value of a metric you wish to increase or decrease, that should not be an excuse not to use it! In that case, you can choose the "Baseline" Key Result type and use the "No Scoring" scoring type.

πŸ”· 2 Zones Yes No πŸ”·

Also called "Binary". Simple to use, only two states, green and red. There are no additional thresholds to set. The "Yes" is achieved when the metric value is equal to or greater than the "To" value. Remember, we strive to create Key Results structured like this: "Verb + what you're going to track + from X to Y".

πŸ”· 3 Zones πŸ”·