# Operational Baseline Dashboard This page explains what you are seeing on the Tier 1 – Operational Baseline dashboard and how to read it quickly. It is written for non‑technical users. The purpose of this dashboard is not to judge performance. Its purpose is to establish a trusted baseline so you can be confident that demand patterns and data behavior make sense before moving to deeper analysis. -------------------------------------------------------------------------------- WHAT THIS DASHBOARD IS FOR This dashboard helps answer three simple questions: • Does the data look complete and consistent? • Is overall demand behaving as expected over time? • Are there any unusual patterns we should investigate before going deeper? If something looks off here, it is a signal to pause and investigate before drawing conclusions from other dashboards. -------------------------------------------------------------------------------- HOW THE KPI CARDS WORK Each KPI card shows two things: • The main number (the result for the date range you selected) • A comparison to the previous period (the same number of days immediately before it) EXAMPLE • If you select Jan 1–Jan 31 (31 days), the previous period is Dec 1–Dec 31 (31 days) • If you select the last 7 days, the previous period is the 7 days right before that WHY THIS MATTERS This keeps comparisons fair. You are always comparing the same length of time. -------------------------------------------------------------------------------- TREND INDICATORS (COLORS AND SYMBOLS) Next to each KPI, you will see: • ▲ or ▼ when there is a real change • --- when there is no change or when a comparison is not available COLOR RULES • Green means the KPI moved in a favorable direction • Red means the KPI moved in an unfavorable direction • Gray (---) means no meaningful change or no comparison IMPORTANT An increase is not always good: • Some KPIs are better when they go up (example: Visits Served) • Some KPIs are better when they go down (example: No‑Shows) -------------------------------------------------------------------------------- FILTERS (HOW TO DRILL DOWN) Use filters to narrow what you are looking at: • Date – Choose the time period • Branch – Focus on one location • Service – Focus on one service type TIP Start wide (All Branches, All Services). When something looks unusual, narrow down to find where it is coming from. -------------------------------------------------------------------------------- KPI DEFINITIONS AND HOW TO INTERPRET THEM TOTAL VISITS CREATED What it measures The total number of visits (tickets) created during the selected period. What question it answers “How many customers entered the system?” How to interpret changes • Up (Green): Higher customer demand • Down (Red): Lower customer demand Example • Today: 1,200 visits • Previous period: 1,050 visits • Change: +150 visits (more demand) -------------------------------------------------------------------------------- VISITS SERVED What it measures The number of visits that were completed (served). What question it answers “How many customers did we successfully serve?” How to interpret changes • Up (Green): Higher throughput (more customers served) • Down (Red): Lower throughput (fewer customers served) Example • Today: 900 served • Previous period: 850 served • Change: +50 served (good) -------------------------------------------------------------------------------- NO‑SHOWS What it measures The number of visits marked as a No‑Show outcome. Plain‑English meaning These are customers who did not complete service and were recorded as a no‑show in the queue system. What question it answers “How many customers did we not serve because they didn’t show up?” How to interpret changes For No‑Shows, lower is better. • Up (Red): More no‑shows (worse) • Down (Green): Fewer no‑shows (better) Example • Today: 120 no‑shows • Previous period: 160 no‑shows • Change: −40 no‑shows (good) -------------------------------------------------------------------------------- SERVICE COMPLETION RATE What it measures The percentage of visits that were served out of all visits created. What question it answers “How often are we successfully completing service?” How to interpret changes (percentage points) • Up (Green): Higher completion effectiveness • Down (Red): Lower completion effectiveness Example • Today: 75.0% • Previous period: 73.5% • Change: +1.5 pp What “pp” means “pp” stands for percentage points. -------------------------------------------------------------------------------- NO‑SHOW RATE What it measures The percentage of visits that ended as No‑Show out of all visits created. What question it answers “How large is the no‑show problem compared to total demand?” How to interpret changes (percentage points) For No‑Show Rate, lower is better. • Up (Red): A larger share of customers are no‑shows (worse) • Down (Green): A smaller share of customers are no‑shows (better) Example • Today: 10.0% • Previous period: 12.0% • Change: −2.0 pp (good) -------------------------------------------------------------------------------- HOW TO USE THIS DASHBOARD IN REAL LIFE Use this dashboard as a baseline check before taking action. • Look for unusual spikes, drops, or gaps in the data • Use filters to isolate where patterns are coming from • Confirm demand behaves as expected before reviewing performance dashboards If something looks unexpected here, investigate first before moving to Tier 2 or Tier 3 dashboards. -------------------------------------------------------------------------------- QUICK SUMMARY • This dashboard establishes a trusted operational baseline • It is descriptive, not evaluative • Green means favorable movement, red means unfavorable • ▲ and ▼ appear only when there is a real change • --- means no change or no valid comparison • Higher is better for Total Visits and Visits Served • Lower is better for No‑Shows and No‑Show Rate