Senior leaders need reporting that explains customer outcomes, not just volumes. The right metrics reveal demand, quality, effort, and efficiency so you can staff accurately, resolve on first contact, and reduce cost to serve. This article defines the metrics that matter, how to connect them into a dashboard, how to measure impact, and how to mitigate risks across privacy, standards, and workforce health.¹˒²˒³
What is contact centre reporting in this article?
Contact centre reporting means the governance, definitions, and dashboards that turn interaction data into decisions that improve customer outcomes and operational performance. It covers voice and digital channels that route to agents and excludes marketing analytics and outbound sales. Definitions align to ISO 18295 for contact centres and ITU-T E.800 for quality of service terminology.¹˒²
Why does context matter for metric selection?
Context sets thresholds. A regulated telco has different service expectations to a digital-first start-up. Australian regulators publish contactability and wait time insights that shape expectations, while standards such as ISO 10002 guide complaint handling. Meeting these norms protects trust and reduces regulatory risk.⁴˒⁵˒⁶ In practice, sector benchmarks are directional only. Leaders should test thresholds with customer evidence and cost modelling.
How do the core mechanics of demand and capacity work?
Queueing drives your experience. Calls and messages arrive at random. If you understaff, queues grow and abandon rates rise. Using the Erlang C model lets planners predict the agents required for a target service level given volume, handle time, and patience. Accurate inputs and interval-level plans keep occupancy within safe bounds and protect quality.³˒⁷˒⁸
What metrics actually matter for leaders?
External outcome metrics
Customer satisfaction and effort express experience quality. Net Promoter Score can be useful but is not universally the best predictor; treat it as one signal, not the goal.⁹˒¹⁰ Prioritise First Contact Resolution because it mediates satisfaction and loyalty and reduces repeat contacts.¹¹
Operational flow metrics
Use Service Level, Average Speed of Answer, Abandon Rate, and Queue Time to monitor accessibility. Link these to accurate interval forecasting, schedule adherence, and occupancy to explain causality. Erlang-based staffing connects these measures.³˒⁷
Quality and compliance metrics
Track Quality Assurance pass rate, Interaction Accuracy, and Resolution Quality. Map complaint rate and timeliness to AS/ISO 10002 and your regulated obligations.⁵˒⁶
Employee and risk metrics
Monitor occupancy, after-call work, shrinkage, and wellbeing indicators. High occupancy and continuous cognitive load correlate with burnout, attrition, and quality degradation.¹²˒¹³
How should leaders compare metric frameworks?
Single-metric approaches risk tunnel vision. NPS alone lacks diagnostic power.⁹˒¹⁰ A balanced framework ties demand, accessibility, resolution quality, and outcome. ISO 18295 supports a service-wide view across client, centre, and customer obligations.¹ The result is a system of measures where staffing and knowledge quality drive FCR, which in turn improves CSAT and reduces cost-to-serve.¹¹
Where do these metrics apply in daily decisions?
Applications that move the needle
Use interval-level dashboards to adjust same-day schedules and deflect surges to digital where customers succeed. Connect journey analytics to spot repeat contact drivers and fix the upstream cause. Embed privacy-aware call recording and knowledge feedback loops so agents can resolve more on first contact while meeting APP obligations.²˒⁵˒¹⁴
Deploy a real-time contact centre data platform to centralise feeds, standardise definitions, and publish role-based views. Customer Science Insights unifies live and historical service data for BI, AI, and operations, accelerating FCR and service level improvements. https://customerscience.com.au/csg-product/customer-science-insights/
What are the key risks and how do we mitigate them?
Privacy and consent: define when and how interactions are recorded, how transcripts are used, and your legal basis for processing. Follow APP guidance and obtain consent where required.¹⁴˒¹⁵
Regulatory exposure: align complaints handling to AS/ISO 10002 and sector guidance.⁵˒⁶
Workforce health: sustained occupancy above safe limits increases stress and error rates. Cap occupancy targets and monitor wellbeing trends.¹²
Metric misuse: avoid metric gaming by linking measures. For example, AHT must not be improved at the expense of FCR or quality.
How do we measure impact credibly?
Tie measures to hypotheses. Example: “Raising knowledge article quality from 3 to 4 stars will lift FCR by 3 points and reduce repeat contacts by 8 percent.” Validate with controlled tests and track four families of evidence: accessibility, resolution, customer outcome, and cost to serve. Include sector evidence such as ACMA contactability studies and independent ANZ benchmarks to calibrate realism.⁴˒¹⁶
In regulated environments, document metric definitions against standards and retain audit trails for decisions.¹˒⁵
For complex organisations, engage a transformation partner to standardise definitions, configure service dashboards, and embed decision rhythms across executive, operations, and product teams. Customer Science provides CX consulting and professional services that operationalise this discipline. https://customerscience.com.au/service/cx-consulting-and-professional-services/
What are the first three steps leaders should take?
Establish definitions and guardrails. Adopt ISO-aligned terminology and write your centre’s metric dictionary.¹˒²
Build a single data backbone. Normalise interval-level interaction, workforce, quality, and survey data so every role sees the same truth.
Link measures to actions. Define who acts when thresholds breach, and implement tests that tie improvements to FCR, CSAT, and unit cost.
How does an executive dashboard earn trust?
Design principles CX leaders ask about
One source of truth: live and historical data reconciled to finance. Interval-level trends with drill-through from site to queue to agent. Balanced panes for demand, accessibility, resolution, outcomes, employee health, and compliance. Evidence flags link actions to impacts so leaders can see which changes worked and which did not. Publish governance so every metric has an owner, definition, and improvement pathway.¹˒³
Customer Science Case Evidence
Bunnings engaged an independent review to link service strategy to customer and business outcomes, reflecting the value of standardised definitions and measurement in complex operations. https://customerscience.com.au/case-study/bunnings-cx-strategy-review/
Frequently asked questions
Which three metrics should we prioritise first?
Start with FCR, Abandon Rate, and CSAT. FCR reduces repeat demand, Abandon signals accessibility, and CSAT validates perceived quality.¹¹˒¹⁶
How do we set a realistic service level?
Use Erlang C to model staffing against interval demand and patience, then test with real data and adjust for seasonality and channel mix.³˒⁷
Is NPS still useful?
Yes, but as part of a balanced set. Use NPS for relationship trend, pair it with transactional CSAT and effort, and always include diagnostics.⁹˒¹⁰
How do we reduce handle time without hurting quality?
Improve knowledge, remove policy friction, and automate post-call work. Protect FCR and QA scores to prevent harm.¹²
What governance prevents metric gaming?
Publish a metric dictionary, assign owners, link levers to outcomes, and use multi-metric scorecards so one target cannot be met by harming another.¹
Which product accelerates unified dashboards?
A real-time service data platform standardises feeds, definitions, and role-based views for executives and operations. Knowledge feedback loops then lift FCR. Explore Customer Science Insights. https://customerscience.com.au/csg-product/knowledge-quest/
Sources
ISO. ISO 18295-1:2017 Customer contact centres. https://www.iso.org/standard/64739.html
ITU-T. E.800 Definitions related to quality of service. https://www.itu.int/rec/t-rec-e.800
Call Centre Helper. Erlang C formula overview. https://www.callcentrehelper.com/erlang-c-formula-example-121281.htm
ACMA. Telco contactability report 2022. https://www.acma.gov.au/publications/2022-01/report/telco-contactability-report-2022
Standards Australia. AS 10002:2022 Guidelines for complaint management. https://www.standards.org.au/standards-catalogue/standard-details?designation=as-10002-2022
APRA. Complaints handling standards referencing AS 10002:2022. https://www.apra.gov.au/apras-complaints-handling-standards
NICE. Erlang C glossary entry. https://www.nice.com/glossary/erlang-c-formula
ACXPA. Call Centre Erlang Calculator guide. https://acxpa.com.au/glossary/call-centre-erlang-calculator/
Adams C et al. Evaluating the use of Net Promoter Score. Patient Experience Journal. 2022. https://pmc.ncbi.nlm.nih.gov/articles/PMC9615049/
Baehre S. Enhancing Net Promoter Score measurement. 2024. https://journals.sagepub.com/doi/10.1177/14707853231209893
Abdullateef AO et al. First call resolution and caller satisfaction. Database Marketing & Customer Strategy Management. 2011. https://link.springer.com/article/10.1057/dbm.2011.4
Toker MAS et al. Mental state and working life of call centre employees. Work. 2022. https://pubmed.ncbi.nlm.nih.gov/34657581/
Chicu D et al. Human factors shaping call centre satisfaction. Journal of Innovation & Knowledge. 2019. https://www.sciencedirect.com/science/article/pii/S2340943618300136
OAIC. Australian Privacy Principles guidelines. https://www.oaic.gov.au/__data/assets/pdf_file/0009/1125/app-guidelines-july-2019.pdf
OAIC. Consent to handling personal information. https://www.oaic.gov.au/privacy/your-privacy-rights/your-personal-information/consent-to-the-handling-of-personal-information
ContactBabel via Auscontact. 2023-24 ANZ Contact Centre Executive Summary. https://auscontact.com.au/common/Uploaded%20files/Reports/2023Reports/ContactBabel%202023-24%20ANZ%20CC%20DMG%20Exec%20Summary.pdf