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A failed implementation announces itself. A failed adoption does not. What data from 161 local governments shows about software that gets bought and never used.
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- Across 161 local governments on the ClearPoint platform, 6.4% of strategic goals and 26.3% of measures carry an active performance status (21 August 2026).
- 75.3% of local governments score fewer than one goal in ten, and only 3.2% score more than half — adoption distributes as a cliff, not a curve.
- 75.3% of assigned owners in local government have never recorded a single update. The name is in the field; the work never followed.
- Plan weight predicts adoption better than training does. Cities running under 3 measures per goal score 58.3% of them; cities running 12 or more score 8.6%.
- Both failure conditions are visible within 90 days of go-live, using four metrics a city can pull from the platform it already pays for.
Every city that buys strategy software buys it for the same reason: the spreadsheet stopped telling the truth. The plan lived in four places, the quarterly report took three weeks to assemble, and nobody could answer "are we on track?" without a meeting first.
Then the platform goes in. Configuration finishes. Training happens. And somewhere in month five, the thing quietly stops being used — while the license renews, the logo stays on the org chart, and nobody files a report saying so.
That silence is the interesting part. A failed implementation announces itself. A failed adoption does not. It looks exactly like a working one from the outside, which is why most cities discover it at renewal, eighteen months after the moment it could have been fixed.
We can see that moment, because we host the plans. What follows is what post-purchase adoption looks like when you measure it with behavior instead of a survey — across 161 local governments running 6,627 active plans on the ClearPoint platform, as of 21 August 2026.
What "software adoption" means once a local government has already bought
Adoption, in the post-purchase sense, is the share of the work the software was bought to carry that it is actually carrying. Licenses issued is a procurement fact. Logins are an attendance record. Adoption is narrower and harder: the plan lives in the system, the numbers get refreshed on a cadence, the goals carry a current status, and the report a council member reads is generated rather than assembled.
Generic SaaS benchmarks put healthy adoption at roughly 60–70% of licensed users active within the first three to six months. That figure travels widely, and it measures the wrong thing for a city. A public works director who logs in monthly to update six measures is fully adopted. A department head who opens the dashboard weekly and updates nothing is not. Presence and maintenance are different behaviors, and only one of them keeps a strategic plan alive.
What most adoption guides skip
We read the six highest-ranking guides on public sector software adoption. Between them they cover change management, executive sponsorship, communication cadence, training design, and resistance — five of the six treat change management as the central answer. Not one of them tells a city how to measure whether adoption is happening after go-live.
The data in that corpus is failure-rate data borrowed from elsewhere — large-project success rates, ERP overrun percentages, the cost of famous public sector IT disasters. Most of it is quoted secondhand from other blogs rather than from the underlying research. It is useful for a budget memo and useless on a Tuesday in month five, when a city manager wants to know whether the thing they bought is working.
The one proprietary dataset in that corpus is ICMA's 2026 survey of 59 municipalities and counties — and it is self-report. Asked what they would change, 39% named how they managed goals and accountability, and 37% pointed to the absence of a formalized reporting process. Those managers were describing a measurement gap from the inside.
What adoption actually measures out at: 6.4%
Inside a strategic plan, two things can carry a live performance status: measures (the KPIs) and objectives (the goals the KPIs are supposed to serve). Scoring is the act that turns a plan into a report — it is what makes a goal green, yellow, or red on the day someone asks.
Across 161 local governments as of 21 August 2026:
- 26.3% of measures carry an active performance status (32,742 of 124,755).
- 6.4% of objectives carry one (1,524 of 23,806).
Roughly one KPI in four is scored. Roughly one goal in sixteen. The layer closest to the council — the goals a city actually campaigned on — is the layer that goes dark first.
How we define it: "actively scored" means the element carries a live evaluation rule that assigns it a performance status. It is a measure of whether the scoring habit was ever installed, not of whether a human has ever touched the record. We report it in aggregate only, and we never publish a named customer's rate — an actively maintained city that tracks without status rules reads as zero, and a handful of them do.
Adoption is a cliff, not a slope
The average conceals the shape. Sorted by the share of goals carrying a live status, 158 local governments distribute like this:
ClearPoint platform data
The adoption cliff: share of goals carrying a live status
Source: ClearPoint platform · 158 local governments with at least one goal · 21 August 2026. Bars scaled to the largest band.
75.3% of local governments score fewer than one goal in ten. Five score more than half. There is no comfortable middle to drift toward. A city is either in the habit or out of it, and the population in between is thin enough to count on two hands.
This is the number that makes adoption legible. A city sitting at 4% is not underperforming an average — it is sitting in the largest band on the chart, which means the condition is ordinary and the fix is known.
The owner who was assigned and never arrived
Assigning an owner is the single most repeated instruction in strategic planning. It is also the instruction most likely to be completed on paper and abandoned in practice.
Across local government users who hold at least one assigned element, 75.3% have never recorded a single update (2,900 of 3,849). Platform-wide the figure is 76.0%. The name is in the field. The work never followed.
What makes this an adoption metric rather than an accountability complaint: a phantom owner is visible on day 30. You do not need a year of decay to detect one — you need a report that lists every owner with zero updates since assignment, which takes about a minute to run and almost nobody runs.
We have written about the mechanics of this at length in why department heads resist strategy execution software, and about how it compounds through a first year in why most local government software implementations fail in Year 1.
The variable that predicts adoption better than training does
Here is where the platform data disagrees with the corpus most sharply.
We grouped 156 local governments by how many measures they hang on each objective — a proxy for how heavy the plan is — and looked at the median share of measures actually scored in each band:
ClearPoint platform data
Lighter plans get scored: median share of measures with a live status
Source: ClearPoint platform · 156 local governments with at least 3 goals and 20 measures (n=72 / 39 / 27 / 18 by band) · 21 August 2026.
A city running fewer than three measures per goal scores 58.3% of them. A city running twelve or more scores 8.6%. That is close to a sevenfold spread, produced entirely by how much a city asked itself to maintain.
We also tested whether automation rescues a heavy plan — whether cities with update workflows and scheduled reminders configured show better adoption. Once we controlled for plan size, the effect disappeared and the direction flipped between size bands on small samples. We are not publishing a number for it, because there is not an honest one to publish. Scope did the work that tooling was credited with.
Failure mode: the ambitious first build
What it looks like: configuration goes beautifully. Every department contributes measures, nobody wants to be the one who submitted too few, and the plan launches as the most complete picture of itself the city has ever assembled.
Where it lands in the data: the 18 local governments carrying 12 or more measures per goal score a median 8.6% of them. The 72 carrying fewer than three score 58.3%. Completeness at build time and maintenance a year later pull in opposite directions, and the build is the half that has a deadline.
The early symptom: measures created keeps outrunning measures updated for two consecutive cycles. That divergence shows up in the first two quarters — well before the renewal conversation where cities usually discover it.
Four adoption metrics worth putting on your own dashboard
The instrument a city needs is small. Four numbers, pulled monthly, each one a behavior rather than an opinion:
- Scored-goal rate. Share of strategic goals carrying a current status. Benchmark: the median local government sits under 10%; above 25% puts a city in the top fifth.
- Phantom-owner count. Number of named owners with zero updates since assignment. Benchmark: three in four owners platform-wide. Target is a number you can fix, not a percentage you can admire.
- Maintenance load. Measures per goal. Under three is the band where scoring holds; past six it decays regardless of what else is in place.
- Report origin. Share of council and leadership reports generated from the system rather than rebuilt by hand. This is the one that tells you whether the software replaced the spreadsheet or joined it.
None of these requires a survey, a consultant, or a satisfaction score. All four are visible from inside the platform a city already pays for — which is what makes the measurement gap a habit problem rather than a data problem.
The 90-day checkpoint
The corpus is unanimous that adoption should be planned for, and silent on when to check. Ninety days after go-live is early enough that the configuration is still fresh in everyone's memory and late enough that the first real update cycle has happened.
Three questions, answered with numbers rather than impressions:
- Did every goal get scored at least once? If a goal has never carried a status, the habit was never installed for it, and the first cycle is where that is cheapest to correct.
- Which owners have never updated? Reassign or retire the element. An owner who has not acted in 90 days will not act in 900.
- Is the plan too heavy to maintain at this cadence? If updating took more than a few days of staff time, cut the measure list before the next cycle rather than after the third.
Cities that get through those three questions honestly tend to end up in the thin top band on the first chart. The ones that skip it end up describing, eighteen months later, a tool that never quite took — which is the abandonment story we mapped in the seven reasons mid-size cities abandon strategic planning software.
The short version
Local governments do not lose software to a bad product or an untrained staff. They lose it to a scoring habit that was never installed and never measured, on a plan built heavier than the staff who inherited it could carry. Both of those conditions are visible in the first ninety days, and both are cheaper to fix there than anywhere downstream.
The cities in the top 3% are not better resourced. They are running fewer things, more often, with names attached that mean something.
Get the 2026 Government Status Rule Benchmark
The Status Rule Playbook shows you how to install the scoring habit this article measures — the rules, the thresholds, and the benchmark data behind the 6.4%.
If you would rather see the four metrics running against your own plan, book a 30-minute walkthrough and we will build the adoption view with your data in it. You can also browse how the rest of this fits together in the strategic planning content hub, or see what the platform looks like for a city in strategic planning software for local government.
Frequently asked questions
Why does strategic planning software fail to get adopted in local government?
Adoption fails when the scoring habit is never installed and never measured. Across 161 local governments on the ClearPoint platform, only 6.4% of strategic goals and 26.3% of measures carry an active performance status as of 21 August 2026. The second driver is plan weight: cities that hang 12 or more measures on each goal score a median 8.6% of them, against 58.3% for cities running fewer than three.
How do you measure software adoption in a local government?
Use four behavioral metrics rather than a satisfaction survey: the share of strategic goals carrying a current status, the number of named owners with zero updates since assignment, the number of measures per goal, and the share of leadership reports generated from the system rather than rebuilt by hand. All four can be pulled from the platform a city already pays for. Logins and licenses issued measure attendance, not adoption.
What percentage of local government strategic goals are actively scored?
6.4% of local government strategic goals carry an active performance status, against 26.3% of measures, across 161 local governments as of 21 August 2026. The distribution is a cliff rather than a curve: 25.3% of local governments score no goals at all, 75.3% score fewer than one in ten, and only 3.2% score more than half. "Actively scored" here means the element carries a live evaluation rule that assigns it a status.
What is a phantom owner in a strategic plan?
A phantom owner is a person named as the owner of a goal or measure who has never recorded a single update against it. Across local government users holding at least one assigned element, 75.3% are phantom owners; platform-wide the figure is 76.0% as of 21 August 2026. They are detectable within 30 days of go-live by listing every owner with zero updates since assignment.
How many KPIs should a city track per strategic goal?
Fewer than three measures per goal is the band where scoring holds up. Local governments running under three measures per goal score a median 58.3% of them; the figure falls to about 25% between three and twelve, and to 8.6% at twelve or more. Plan weight predicts whether a plan stays maintained more reliably than training or automation does.
When should a city check whether its new software is actually being adopted?
Ninety days after go-live, once the first real update cycle has happened but while the configuration is still fresh. Check three things: whether every goal has been scored at least once, which owners have never updated, and whether the plan proved too heavy to maintain at the intended cadence. Cities that skip this checkpoint typically discover the problem at renewal, roughly eighteen months later.
Methodology and sources
Platform figures are drawn from aggregated, anonymized ClearPoint platform data as of 21 August 2026, covering 161 local government organizations (cities, counties, towns, villages, boroughs, townships and metropolitan authorities) running 6,627 active plans, 124,755 measures and 23,806 objectives. "Actively scored" means an element carries a live evaluation rule assigning it a performance status; it is reported in aggregate only and is not a per-customer usage claim. Sub-analyses restrict to organizations with at least 3 objectives and 20 measures (n=156) to avoid small-plan distortion.
The one external dataset cited here is ICMA, Strategic Plan Implementation: Off The Shelf And Into Action (June 2026, n=59 US municipalities and counties, self-reported survey). The corpus review referenced above covers the six highest-ranking guides on public sector software adoption as of 21 August 2026; we counted which subtopics each one covered and did not reproduce the third-party failure-rate figures they quote, because those figures largely trace back to other blog posts rather than to primary research. Further background on plan-level benchmarks is in strategic planning: what 21,000+ plans taught us and local government KPIs.
