Dual-Valence Metric Dashboard¶
Monitoring dashboard — instantiates Goal Valence Decomposition and Separation
Tracks approach strength and avoidance strength as two separate channels over time, so rising resistance is never masked by rising enthusiasm.
The Dual-Valence Metric Dashboard is an ongoing measurement instrument that runs after an intervention lands. Its defining idea is that it carries the archetype's valence separation forward into monitoring: it tracks the pull toward the goal and the push away from it as two independent time-series and never nets them into one figure — because the whole point is that a rise in avoidance can hide inside a rise in adoption, and a single "success" number will paper over exactly the resistance the archetype was built to keep visible. It measures two channels moving through time; it is not the pre-launch diagnostic display, and it does not decide what to do when a channel moves the wrong way.
Example¶
A platform team ships an internal deployment tool and watches a single adoption % climb week over week. It looks like a win. The Dual-Valence Dashboard refuses the single number and splits it in two. The approach channel gathers pull signals — teams actively self-serving deploys, positive mentions, feature requests. The avoidance channel gathers push signals — opt-out requests, support tickets tagged frustration, and teams still quietly running their old shadow tooling on the side.
Adoption is up forty percent — and the avoidance channel is climbing right alongside it. Teams are onboarding because a mandate tells them to, while resentment and workarounds accumulate underneath. The net adoption figure, a textbook Goodhart metric, hid a brewing backlash.[n1] Because the two channels were plotted apart, the team catches the divergence early, pauses the mandate, and fixes the friction before the rollout curdles — a signal that a single index would have buried until it was too late.
How it works¶
- Define two metric sets. One set of pull signals, one set of push signals, chosen so each channel genuinely reflects its valence.
- Forbid the net. No composite index that combines the channels; the missing single number is deliberate.
- Plot both over time. Show each channel's trajectory so divergence — approach up, avoidance also up — is legible at a glance.
- Alert on rising avoidance. Trigger attention whenever the push channel climbs, even when the pull channel is climbing faster.
Tuning parameters¶
- Metric choice per channel — behavioral signals (usage, opt-outs) versus sentiment signals (survey, mentions); each captures a different slice of the valence and misses others.
- Alert sensitivity — how large an avoidance rise triggers a flag; sensitive settings warn early but cry wolf, dull ones warn late.
- Cadence — refresh frequency; real-time catches fast backlashes but adds noise, weekly smooths but lags.
- Silent-signal weighting — how much to instrument for quiet avoidance (disuse, exit) versus loud avoidance (complaints), since the dangerous resistance is often the quiet kind.
When it helps, and when it misleads¶
Its strength is that it keeps the two valences separated after the intervention, catching masked resistance — the rising avoidance that a headline adoption number is structurally built to hide — while there is still time to act on it.
Its failure mode is measuring the wrong proxy: avoidance frequently shows up as silence — quiet disuse, a slow exit, a shadow tool — rather than as tickets, so a dashboard that only counts complaints will read a defecting population as content. And any metric that becomes a target invites the Goodhart distortion it was meant to expose. The classic misuse is celebrating the approach channel while the avoidance channel is instrumented too weakly to see. The guarding discipline is to instrument for silent avoidance (exit rates, dormancy, workaround usage), not just loud complaints, and to treat every channel as a signal to interpret rather than a score to maximize.
How it implements the components¶
This mechanism fills the post-intervention feedback side of the archetype:
dual_channel_feedback— it is the dual channel: approach strength and avoidance strength measured as two independent streams that are never combined.temporal_valence_gradient— it plots each valence's trajectory through time, making a rising-avoidance gradient visible as it forms rather than after the fact.
It does NOT lay out the pre-intervention diagnostic split by stakeholder — that is Benefit-Barrier Split Matrix (valence_separation_boundary, stakeholder_specific_valence_profiles), the display it is most easily confused with, which diagnoses before while this monitors after; and it does not decide what to do when the avoidance channel rises — that is Recomposition Commitment Review (recomposition_decision_rule).
Related¶
- Instantiates: Goal Valence Decomposition and Separation — this dashboard carries the valence separation into ongoing monitoring.
- Consumes: Approach-Avoidance Elicitation Protocol supplies the two driver maps that define which pull and push signals each channel should track.
- Sibling mechanisms: Approach-Avoidance Elicitation Protocol · Benefit-Barrier Split Matrix · Paired Message Frame · Barrier-to-Support Conversion · Staged Commitment Ladder · Concern Validity Review · Recomposition Commitment Review
Editorial Notes¶
Form Classification¶
Form family: Monitoring, Sensing & Alerting
Rationale: Dual-Valence Metric Dashboard operates as an ongoing sensing arrangement that repeatedly observes actual state and surfaces changes or alerts because it tracks approach strength and avoidance strength as two separate channels over time, so rising resistance is never masked by rising enthusiasm.
Independent corroboration: The frozen evidence defines Dual-Valence Metric Dashboard as 'Tracks approach strength and avoidance strength as two separate channels over time, so rising resistance is never masked by rising enthusiasm', so its operative form is Monitoring, Sensing & Alerting.
Review outcome: Independent reviewer agreement; high confidence.
Origin Attribution¶
Primary origin: Psychology
Origin pattern: Cross-disciplinary synthesis
Present-day reach: Multi-domain
Rationale: Motivational psychology cohered approach and avoidance as separable systems whose simultaneous strength cannot be represented by one net attitude.
Related originating lineages:
- Data Science & Analytics — Dashboard practice supplied separate time-series instrumentation that prevents growing avoidance from disappearing inside a net adoption score.
- Organizational & Management Science — Change and adoption analytics supplied the live dashboard form for tracking enthusiasm and resistance over time.
Review resolution: Psychology is primary because independent approach and avoidance systems define the two measures; data visualization and organizational monitoring shape the standing dashboard.
Attribution caveat: The dual-valence construct is psychological, while its governed metric dashboard is managerial synthesis.
Encyclopedia synthesis: The exact catalogued form synthesizes established practice rather than reproducing a single standard historical label.
Review outcome: Reconciled after independent review; medium confidence.
Notes¶
[n1] Goodhart's law — "when a measure becomes a target, it ceases to be a good measure." A single netted adoption figure is exactly such a target, which is why the dashboard splits it into two uncombinable channels and treats each as a signal rather than a goal. ↩