How Experience and Productivity scores are calculated

Elements Pulse computes two composite scores, shown on your Dashboard: the Experience Score and the Productivity Score. Each one synthesises several indicators into a single score out of 100, with a visual status (Healthy / At Risk / Critical) so you can immediately see where your IT organisation needs attention.

This page explains how these scores are calculated, so you can interpret them, and trust them.

Principles shared by both scores

Before diving into each engine, a few rules apply to both scores:

• 0–100 scale. The higher the score, the better the situation.

• Identical statuses and thresholds:

• Handling of missing data. If an indicator has no data yet (for example, no survey responses collected for the period), it is simply excluded from the calculation — it is never counted as a zero, so it never artificially penalises your score. If all indicators feeding a score are missing, the score shows a "No data" state rather than a misleading value.

• Automatic recalculation. Scores are recalculated continuously (daily) as new tickets and survey responses come in, and update instantly whenever you change your analysis scope (Space, Organisation, Request Type, period).

1. Experience Score

What it measures

The Experience Score reflects the perceived quality of experience your users have with your IT service, as expressed directly by them through surveys. This is your "X data" (experience) indicator — to be combined with, rather than opposed to, the operational performance captured by the Productivity Score.

It is built from three satisfaction indicators:

CSAT can come from two sources, blended transparently: the native Jira Service Management CSAT field, and responses to your Elements Pulse surveys. Both are treated identically.

How it's calculated

Step 1 — Aggregating raw responses

Each indicator is first averaged across all responses within the selected scope. For NPS, respondents are first classified using the standard Bain & Company method:

• Promoters: score ≥ 9

• Passives: score 7 or 8 (counted but do not affect the score)

• Detractors: score ≤ 6

The raw NPS score is then: ((Promoters − Detractors) / Total responses) × 100, giving a result between -100 and +100.

Step 2 — Normalisation to a 0–100 scale

Each indicator is converted to a common 0–100 scale, so they can be compared and combined:

Step 3 — Composite score

The Experience Score is the average of the available (non-null) indicators only. If an indicator has no data yet — for example NPS before your first surveys launch — it is simply excluded from the calculation, without penalising the score:

• All 3 indicators present → average of all 3

• 2 indicators present → average of those 2 only

• Only 1 indicator present → the score equals that indicator alone

Step 4 — Status

The resulting composite score determines the Healthy / At Risk / Critical status using the shared thresholds above.

2. Productivity Score

What it measures

The Productivity Score reflects the operational performance of your IT teams — your "O data" (operational) indicator, based on factual data from your JSM tickets rather than self-reported feedback.

It combines four indicators:

How it's calculated

Step 1 — SLA attainment rate (TTR and FRT)

For each eligible ticket, Jira Service Management determines whether its SLA was met or breached. TTR and FRT are calculated as the share of tickets that did not breach their SLA, within the selected scope and period. Tickets with no SLA configured are simply excluded from the calculation (they count neither as a success nor a failure).

Step 2 — Normalisation to a 0–100 scale

TTR and FRT are normalised against a 95% target ceiling — an SLA attainment rate of 95% or above already scores 100, matching what's typically considered best-in-class performance across the industry. Below that ceiling, the score scales down proportionally:

RR and FCR are normalised directly from rates:

• RR: (1 − reopening rate / 15%) × 100, clamped between 0 and 100. A reopening rate of 15% or more scores 0; a rate of 0% scores 100.

• FCR: normalised against a 70% target ceiling — a first-contact resolution rate of 70% or above already scores 100, in line with what's generally considered good performance for IT/technical support. Below 70%, the score scales down proportionally (e.g. a 50% FCR rate scores 71).

Step 3 — Composite score

As with the Experience Score, the Productivity Score is the average of the available indicators. An indicator with insufficient data (for example, not enough resolved tickets to compute a reliable reopening rate) is excluded from the calculation rather than counted as zero.

Step 4 — Status

The same Healthy / At Risk / Critical thresholds apply.

Why this approach?

Elements Pulse was designed to expose the "watermelon effect": a situation where operational indicators (SLAs) look green on the surface, while the actual experience of your users is degraded underneath. By computing the Productivity Score and Experience Score with independent but consistent logic (same thresholds, same handling of missing data, same calculation transparency), Elements Pulse lets you cross-reference both dimensions — via the Focus Area Quadrant — to pinpoint exactly where to invest: where operational performance and real experience diverge.