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Traditional reporting tells you what happened. Decision Intelligence as-a-Service (DIaaS) explains why it happened, what could happen next, and which action to prioritize using causality, trend intelligence, predictive analytics, and governed AI-driven insights.
By transforming fragmented operational signals into real-time operational intelligence, DIaaS helps workforce, operations, QA, training, and CX teams move from reactive reporting to proactive decision-making.
Traditional reporting explains the past, but operational decisions need to be made in the moment.
As KPIs such as Service Level, Average Handle Time (AHT), abandonment, and shrinkage fluctuate, hidden operational drivers often remain undetected until performance is already affected.
Lumina Datamatics’ Decision Intelligence as-a-Service (DIaaS) delivers governed intelligence through prompts, dashboards, alerts, and configured reporting, helping teams understand why performance changed and what action should happen next.
DIaaS connects operational data, applies intelligence, and delivers governed insights through a single decision-making framework.
Connect intelligence across WFM, telephony, agent performance, QA, BQM, training, CRM/ticketing, CX signals, and operational metadata.
Apply causality models, trend intelligence, predictive models, anomaly detection, and cross-functional correlation maps to identify performance drivers.
Standardize KPIs through metric harmonization, root-cause drilldowns, role-based access, and auto-narratives for governed operational reporting.
Access intelligence through dashboards, alerts, prompts, and configured reports, tailored to operational roles and decision needs.
Connect insights with operational workflows to enable faster intervention and better business decisions.
DIaaS transforms operational data into statistically grounded, explainable decision support.
Identify operational relationships through correlation networks, lag dependencies, pattern co-movements, and noise filtering.
Understand performance drivers using variance decomposition, contribution scoring, trend stability, and change-point analysis.
Forecast outcomes with predictive modelling, anomaly detection, scenario simulation, and probability-based risk scoring to enable proactive intervention.
See how DIaaS turns operational questions into governed intelligence. Ask a question and receive causal explanations, predictive risk signals, and actionable recommendations based on enterprise-defined data and analytical models.
The prototype demonstrates the DI experience using simulated operational intelligence. A production implementation requires enterprise data ingestion, KPI harmonization, causal models, and role-based deployment.
Why did SLA performance decline yesterday?
AHT drift was the primary contributor to yesterday's SLA pressure. While volume exceeded forecast, the larger impact came from handle-time inflation and skill imbalance during the afternoon interval.
Prioritize skill rebalancing and short-interval AHT containment before increasing overtime. If the current AHT trend continues, SLA breach risk increases over the next 3–5 intervals.
Lagged impact on SLA
DOW-normalized deviation
Coverage gap
*The experience above is illustrative. Select “See How DI Works” below to explore the DI experience.
DIaaS helps organizations move from detecting operational risk to evaluating intervention options and understanding their impact across workforce and customer experience.
Are we about to lose control, when, and why?
Predicted SLA breach in the next 3–5 intervals due to volume deviation and shrinkage trends.
What happens if we intervene?
Compare intervention scenarios such as overtime, skill rebalancing, or break re-sequencing to determine the most effective response.
How do WFM decisions impact CX outcomes?
Understand how AHT, scheduling, occupancy, and workforce decisions influence SLA, CSAT, and QA performance.
DIaaS delivers governed operational intelligence through prompts that work within approved business rules, KPI definitions, and analytical frameworks.
Rather than generating unsupported insights, the platform explains governed intelligence using enterprise-defined metrics, validated causal logic, and operational context.
Trust is built into every intelligence output. DIaaS maintains transparency through role-based access, versioned logic, KPI ownership, audit trails, and governed AI interactions, ensuring every recommendation is traceable and explainable.
Maintain one definition for SLA, AHT, CSAT, FCR, QA, and shrinkage.
Ensure causality models, thresholds, and attribution logic remain traceable.
Link every insight back to its source data, KPI definition, and analytical method.
DIaaS connects operational intelligence with measurable business outcomes.
~12–15% improvement
Improve staffing decisions and reduce SLA surprises.
Up to ~22% lower breach likelihood
Detect risks earlier and respond proactively.
CSAT +0.15 to +0.30; NPS +3 to +7
Improve customer experience by addressing upstream performance drivers.
18–27% fewer QA errors
Enable more targeted coaching and faster performance improvement.
2–4% Opex reduction
Optimize headcount allocation, reduce operational variance, and lower repeat contacts.
Experience the DI approach through the interactive prototype or speak with Lumina Datamatics to explore how DIaaS can strengthen your reporting, decision-making, and operational performance.
The landing page includes a prototype prompt experience to demonstrate the DI approach. A full DIaaS implementation requires client data ingestion, KPI harmonization, causal models, and role-based deployment.
The prompt layer uses only enterprise-defined metrics and pre-approved statistical outputs. Unsupported prompts return insufficient evidence rather than generate unsupported insights.
The intended architecture keeps the LLM outside the trust boundary. It receives governed insight summaries instead of raw tables, PII, or event-level records.
Dashboards explain what happened. DIaaS adds causal explanation, predictive risk, confidence scoring, recommendations, and governed operational intelligence to support better decisions.
