Go-live is not the finish line. It is the starting line of a longer, more demanding, and far less documented phase: making sure the ERP delivers on its promises over time.
Most organisations wind down the project phase as soon as the system reaches production. The team disperses, the budget is spent, and rigorous measurement stops. The predictable result: secondary modules get abandoned, shadow spreadsheets resurface, and two years after go-live the executive committee is asking why the ERP has still not delivered the expected returns.
This guide gives CIOs the 15 structural KPIs needed to steer ERP performance from day one, organised into three groups: technical stability, real adoption, and measurable business value.
Why Measure After Go-Live — Not Just During the Project
During the project phase, KPIs focus on delivery: schedule adherence, budget burn, test coverage. These metrics are useful but incomplete. They measure whether you deployed the system, not whether the system is working.
The value of an ERP is built in the 12 to 36 months following go-live, not during the configuration sprints. Return on investment materialises on average between two and three years after production launch — provided the system is well used, the data is reliable, and the processes have genuinely changed.
A post-go-live dashboard has three distinct objectives:
- Detect drift early: an adoption rate stalling at 60% after three months is a warning signal, not a temporary anomaly.
- Quantify value created: without measurement, the ERP remains a cost. With business KPIs, it becomes an investment whose ROI can be demonstrated.
- Steer trade-offs: the ERP Centre of Excellence (CoE) prioritises its backlog of improvements based on facts, not intuition.
Group 1 — Technical Stability KPIs (5 Indicators)
Technical KPIs are the first to put in place. They measure the reliability of the foundation on which the entire system rests.
KPI 1 — System Availability (Uptime)
Definition: the percentage of time the system is accessible to users, excluding planned maintenance windows.
How to measure: via application monitoring tools (Dynatrace, Datadog, New Relic, or your cloud provider’s dashboard). Most SaaS vendors publish their uptime on a public status page.
Recommended thresholds:
- Minimum target: 99.5% (fewer than 44 hours of unplanned downtime per year)
- Target for a critical SaaS ERP: 99.9%
Frequency: monthly, with a quarterly trend report.
Watch point: distinguish uptime from functional availability. A system that is technically “up” can be unusable if a critical interface is failing. Include integration flows in your measurement (APIs, EDI, banking connectors).
KPI 2 — Response Time for Critical Transactions
Definition: execution time for high-volume or high-impact business transactions (order confirmation, production batch close, financial statement generation).
How to measure: via application logs or application performance monitoring (APM) tools. Identify the 10 to 15 most-used transactions and measure their P95 (the time that 95% of calls complete within).
Recommended thresholds:
- Standard transactions: < 3 seconds
- Reports and statements: < 15 seconds
- Overnight batch jobs: < 4 hours (adjust based on volume)
Frequency: weekly during the hypercare phase (day 0 to day 90), monthly thereafter.
KPI 3 — Application Error Rate
Definition: proportion of transactions ending in error (unhandled exception, timeout, technical validation failure) relative to total volume.
How to measure: via application server error logs and monitoring system alerts.
Recommended thresholds:
- Target: < 0.5% of transactions
- Immediate alert threshold: > 2% over a 15-minute window
Frequency: real-time during hypercare, monthly thereafter.
KPI 4 — Mean Time to Resolve Incidents
Definition: time elapsed between a support ticket being opened and its effective resolution — not its administrative closure, but its actual resolution for the user.
How to measure: via your ticketing tool (Jira Service Management, ServiceNow, or the integrator’s support portal). Measure critical incidents (business process blocked) and standard incidents separately.
Recommended thresholds:
- Critical incident (P1, production blocked): resolution < 4 hours
- Major incident (P2, workaround available): resolution < 48 hours
- Minor incident (P3, inconvenience without blockage): resolution < 5 business days
Frequency: monthly, with a systematic P1 review at the operational committee.
KPI 5 — Support Ticket Volume Trend
Definition: number of tickets opened per week or per month, tracked as a trend since go-live.
Interpretation: a high volume in the first weeks is normal (learning curve). The trajectory matters more than the absolute number. A volume that remains flat or increases after three months signals a training, configuration, or data quality problem — not a transient anomaly.
Alert threshold: volume rising more than 20% for two consecutive months after the hypercare phase.
Frequency: weekly during hypercare, monthly thereafter.
Group 2 — Adoption and Real-World Usage KPIs (5 Indicators)
Technical stability is necessary but not sufficient. A system available at 99.9% that nobody uses correctly creates no value.
KPI 6 — Adoption Rate by Licensed User
Definition: proportion of users who have completed at least one active session in the ERP during the past 30 days, relative to the total number of licensed users.
How to measure: via ERP login logs (most modern systems expose this report natively in their administration console).
Recommended thresholds:
- Day 30: > 70% (stragglers have legitimate reasons — leave, peak workload)
- Day 90: > 85%
- Day 180: > 90%
Watch point: a login is not enough. Cross this KPI with KPI 7 to distinguish real users from users who log in but continue to work outside the system.
KPI 7 — Direct Entry Rate vs Detected Workarounds
Definition: proportion of business transactions completed directly in the ERP, relative to transactions that are manually reworked or routed around the system (dual entry into a spreadsheet, email to compensate for an unused workflow, etc.).
How to measure: this is the hardest KPI to automate. Two approaches:
- Survey audit: ask key users in each business area about their actual practices (quarterly survey, 15 minutes).
- Data analysis: compare the purchase order volume in the ERP with the volume of paper POs or outbound email approvals. Any discrepancy reveals a workaround.
Alert threshold: more than 15% of transactions bypassing the ERP workflow after six months.
KPI 8 — Integrated Workflow Completion Rate
Definition: proportion of validation flows configured in the ERP (purchase order approval, invoice validation, work order close) that are actually completed within the system, with no manual exit.
How to measure: via the ERP’s workflow reports (SAP, Oracle, Microsoft Dynamics expose these reports in their native analytics tools).
Priority processes to track:
- Purchase order approval circuit
- Expense report validation
- Full order-to-cash cycle (order → shipment → invoice → collection)
- Automated bank reconciliation
Target: > 90% system completion after six months in production.
KPI 9 — Secondary Module Utilisation Rate
Definition: percentage of deployed modules (CRM, project management, quality, maintenance) actively used by their target teams.
Why this is critical: secondary modules are often the first to be abandoned after go-live. Non-use represents a double cost: licences paid for nothing, and the operational process reverting to the old system (typically spreadsheets or email).
How to measure: number of transactions entered per module over the past 30 days. Compare against the objectives defined during the scoping phase.
Alert threshold: a module with fewer than 20% of the transaction volume projected at design stage after three months is a module in freefall.
KPI 10 — User Satisfaction Score (Internal CSAT)
Definition: user satisfaction rating for the ERP, collected via a short, regular survey (3 to 5 questions, scored out of 5 or 10).
How to measure: quarterly survey sent by email or via an internal tool (Microsoft Forms, Typeform). Recommended questions:
- “Does the ERP allow you to do your job more efficiently than before?” (1–5)
- “Did you use any workarounds to complete your tasks this week?” (yes/no)
- “Would you recommend the current ERP to a colleague in a similar role?” (NPS 0–10)
Interpretation: a score drop over two consecutive quarters is a serious warning signal, often revealing a training gap, performance issue, or misconfigured module.
Group 3 — Business Value and ROI KPIs (5 Indicators)
This is the hardest group to measure, but the most important for justifying the ERP investment to the executive committee.
KPI 11 — Monthly Financial Close Cycle Time
Definition: number of business days between the end of the month and the availability of final financial statements (income statement, interim balance sheet, management reporting).
Why track it: reducing close cycle time is one of the easiest ERP gains to quantify and one of the most visible to the finance leadership. A poorly integrated ERP lengthens this cycle; a well-configured one shortens it significantly.
Baseline measurement: establish the pre-ERP baseline (how many days on average before the project?), then track the monthly evolution.
Typical target: move from 10–15 business days (without ERP, or with a poorly used one) to 4–6 business days after 12 months of stabilisation.
KPI 12 — Inventory Accuracy Rate
Definition: variance between stock quantities shown in the ERP and quantities physically counted during cycle counts or spot checks.
How to measure: (ERP stock − physical stock) / ERP stock × 100. Measure by product category and by warehouse.
Target: < 2% variance for fast-moving references, < 5% for slow-moving references.
Proxy indicator: if your variance rate is flat or rising after six months, it usually signals non-compliant manual entries or inbound/outbound flows not being recorded in the ERP.
KPI 13 — Order-to-Cash Cycle Duration
Definition: average time between receiving a customer order and collecting the corresponding payment.
Why it matters strategically: this cycle encompasses order entry, fulfilment, shipping, invoicing, and collections. Every step not automated in the ERP extends the cycle and directly impacts working capital requirements.
How to measure: in modern ERPs, this report is native (SAP, Oracle, Microsoft Dynamics). For older systems, cross-reference order, shipping, invoice, and collection dates from the data tables.
Improvement target: a 20–30% reduction in the average cycle within 18 months post go-live, calibrated against your baseline and sector norms.
KPI 14 — Process Automation Rate
Definition: proportion of repetitive tasks (bank reconciliation, automated customer reminders, replenishment order generation, payroll calculation) executed without manual intervention via automations configured in the ERP.
How to measure: list the automatable processes identified during the design phase. For each one, verify whether it is actually automated and measure the volume of cases handled automatically versus manually.
Progressive targets:
- Month 6: > 60% of automatable processes active
- Month 12: > 80%
- Month 24: > 90% (the remaining 10% correspond to legitimate exception cases)
KPI 15 — Cumulative ROI (Documented Gains / Total Cost of Ownership)
Definition: ratio of documented savings and gains since go-live (reduction in administrative headcount, fewer billing errors, optimised inventory, shorter collection cycles) to the total cost of ownership of the ERP (licences, integration, maintenance, ongoing training).
How to measure: build a financial dashboard with:
- Cost column: annual licences + maintenance costs + internal costs (CoE team time)
- Gain column: measured savings relative to the pre-ERP baseline, tracked quarterly
Frequency: semi-annual review, presented to the executive committee.
Ground reality: industry research places the average ERP ROI at roughly 1.5× the investment over three years (Panorama Consulting ERP Report), but that figure is only meaningful if you are actually measuring your gains. Without rigorous measurement, the ROI is unverifiable — and the next budget negotiation will be difficult.
Building This Dashboard: Organisation and Tooling
Having these 15 KPIs on paper is not enough. You need a structure to collect, analyse, and act on them.
Step 1 — Assign an owner: each KPI must have a named owner (CoE lead for technical KPIs, CFO for financial KPIs, business director for adoption). Without an owner, KPIs go unmeasured.
Step 2 — Automate data collection: technical KPIs (uptime, response time, tickets) must be automated. Adoption and business-value KPIs may require manual extracts in the first months, but the goal is to automate them progressively.
Step 3 — Build the dashboard: most vendors offer native reporting tools (SAP Analytics Cloud, Oracle Analytics, Power BI connected to Dynamics). Start simple — a table with 15 rows is enough. Sophistication comes later.
Step 4 — Set a review cadence: a monthly operational committee on technical and adoption KPIs, a quarterly strategic committee on business value. Without a formal review, data accumulates without decisions.
For implementing the governance framework that goes alongside this dashboard, see our complete guide on ERP post-deployment governance and centre of excellence and our Day-90 stabilisation checklist.
Key Takeaways
An ERP without a post-go-live dashboard is an investment without a steering wheel. These 15 KPIs are not an exhaustive list — they are the indicators that surface 80% of problems before they become crises.
The golden rule: measure what can be improved, improve what is measured. A KPI that drives no action is just a number. A KPI that drives a decision is a management lever.
To go further: download our ERP evaluation grid — 30 criteria out of 100 points to benchmark your current implementation against market best practices.
