Analysis of sprint metrics & AI usage
Analysis Tab – Deep Dive into Delivery & AI Adoption
🧭 Overview
The Analysis Tab in KnowHOW provides deeper visibility into delivery performance and AI adoption trends within your projects.
It complements standard dashboards by surfacing sprint metrics and AI usage analytics, helping teams identify opportunities for improvement and track the adoption of AI-assisted practices across the organization.
⚙️ Structure of the Analysis Tab
The Analysis tab consists of two main sections:
1️⃣ Sprint Metrics View – Tracks additional process and sprint health indicators.
2️⃣ AI Usage Analytics – Provides visibility into how teams are leveraging AI assistants in their day-to-day work.
📈 1. Sprint Metrics View
🎯 Purpose
Offers fine-grained visibility into delivery hygiene, refinement discipline, and sprint predictability.
These indicators highlight the maturity of planning, grooming, and execution practices across teams, helping leaders spot inefficiencies early and ensure consistency in agile ceremonies.
💡 How to Use This View
Review these metrics to monitor process adherence and planning discipline across sprints.
Identify recurring patterns, such as high scope changes or frequent estimation misses.
Discuss outliers in sprint retrospectives to drive corrective actions.
Track progress over time to evaluate the effectiveness of agile maturity initiatives.
📈 Consistent monitoring of these metrics ensures predictability and stronger sprint outcomes.
🤖 2. AI Usage Analytics View
🎯 Purpose
The AI Usage Analytics view provides a snapshot of how projects are adopting AI assistants.
It helps leaders understand where AI is being used, how frequently, and by which projects -enabling data-driven strategies for scaling AI adoption across the organization.
💡 Why It Matters
Tracking AI usage helps the organization:
Measure the adoption levels of AI assistants across teams
Identify high-engagement projects that can serve as AI champions
Spot underutilized areas where more enablement is needed
Quantify the impact of AI-assisted practices on delivery performance
🤖 AI Usage Analytics is a step towards linking adoption with measurable business outcomes.
🧭 In Summary
The Analysis Tab is designed for teams and leaders who want to go beyond traditional metrics.
It combines delivery indicators with AI usage insights, offering a deeper understanding of process efficiency, planning discipline, and technology adoption.
By using this tab regularly, organizations can strengthen their delivery foundation today and prepare for AI-driven excellence tomorrow.
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