Produktivitätsverlust durch manuelle Qualitätsbewertung von Anrufen

Definition

Australian QA guidance emphasises that for large call centres it is impractical to review every call manually and recommends AI-driven analytics and automation to improve QA efficiency.[1] Industry vendors describe that modern call monitoring and QA tools can automatically score 100% of calls based on custom QA forms, allowing QA teams to audit more calls without hiring more reviewers and surfacing true coaching needs.[5][6] Without such tools, QA analysts and team leaders must listen to calls in real time or near-real time, annotate scorecards, and compile reports. This significantly limits coverage (often to 1–3 calls per agent per month) and consumes many hours that could be used on coaching or handling complex customer issues. Logic-based estimation: A 100‑seat call centre with a typical ratio of 1 QA analyst per 25–30 agents will employ ~3–4 QA FTE. If each QA specialist spends 70% of their time on manual listening and scoring (~100 hours per person per month), that is 300–400 hours/month spent largely on repetitive review. Automation that reduces manual listening/scoring time by 50–70%, as claimed by AI QA vendors, would free 150–280 hours/month. At a fully loaded cost of ~AUD 50/hour, this equates to AUD 7,500–14,000 per month (AUD 90,000–168,000 per year) in capacity that could be redirected to higher-value work, representing a current capacity loss when automation is not used.[1][4][5][6][7]

Why This Matters

The Pitch: Australian 🇦🇺 call centres waste 80–160 Stunden QA-Kapazität pro Monat auf manuelles Abhören statt auf wirksames Coaching. Automatisierte 100%-Überwachung und Scoring reduziert den manuellen Prüfaufwand um 50–70% und gibt Kapazität im Wert von AUD 100,000+ jährlich frei.

Affected Stakeholders

Quality Assurance Manager, QA Analysts, Team Leaders, Contact Centre Manager, Head of Operations

Related Business Risks