# What’s wrong with scores?

Resist the temptation to aggregate metrics into scores. Scores are problematic
for a variety of reasons.

# Issues

**Added Indirection** — Creating scores is tempting because it appears to reduce
the amount of information communicated to users. But, the issue is that a score
adds another layer of indirection. Rather than reducing the amount of
information needed to make decisions, scores add to it.

**Aggregates and Weights** — Scores require additional decisions to be made
about combining and weighting metrics. Agreeing to a standard set of weights
distracts from the main goal of using metrics to drive priorities and
improvements. It’s okay to let different teams prioritize different metrics.

**Stakeholder Buy-in** — Scores also require a lot of "buy-in" from
stakeholders. Getting the buy-in necessary for metrics is often difficult enough
that creating scores as "meta-metrics" isn’t worth the effort. Another option is
to have a strong sponsor for the score. But these top-down efforts are rare.

**Expensive to Develop** — When creating a metric, lots of decisions need to be
made about the telemetry and data pipeline. What is included or excluded from
the metric? When does the duration start or end? Prioritize and iterate on these
decisions before considering an aggregate score.

**Unactionable Changes** — Scores are less directly actionable and meaningful
than metrics. Creating an alert on a score is error prone as one metric’s
improvement may conceal another metric’s worsening.

**Increased Noise** — The changes in contributing metrics also make variance
calculations more difficult. As fluctuations are bound to occur, the combination
of those changes may increase the noise in the score.

**Missing Units** — Scores often have no units and therefore are not meaningful
or intuitive. To say that a score went from 50 to 60 is meaningless without more
context. Is the overall score out of 100 or 1,000? Is a 20% improvement typical
or remarkable?

**Potential for Gaming** — When a set of metrics are reduced to a single number,
there might be an incentive to "game" the system to achieve higher scores,
potentially at the expense of other important factors.

**Difficulty in Comparison** — Due to inherent differences in services or
systems, it may be difficult to meaningfully compare scores. The effort to
improve the score in one scenario by 10% may require ten times more effort in
another scenario for the same benefit.

Next: [Metrics and Performance Reviews](metrics-and-performance-reviews.md)