Executive Summary
Bookings · Quota · Cost across all versions
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Total Bookings
Year actuals
vs Plan Target
Actuals vs PoR
Quota Attainment
Bookings / Quota
Net Income
Bookings − Cost
Plan Target
Plan PoR target
YoY Bookings
vs prior year
Monthly Bookings — Actuals vs Quota vs Plan
Bars = Actuals · Line = Quota · Dashed = Plan Target
Quarterly Summary
Actuals vs Plan by quarter · click for detail
Regional Bookings Contribution Bridge
How each region builds to WW total · sorted by contribution
Quarterly Detail
Bookings, Quota, Plan and attainment by quarter
QuarterBookingsQuotaPlan TargetQuota Att%vs Plan%
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Bookings by Region
Sorted by total bookings · click for detail
Quota Attainment by Region
Bookings ÷ Quota · click for detail
Regional Performance Detail
Actuals vs Quota vs Plan Target · sorted by bookings
RegionSegBookingsQuotaPlan TargetCostQuota Att%vs Plan%
Quota vs Bookings — Monthly Trend
Actuals (bars) vs Quota (line) · click for month detail
Attainment % by Month
Bookings ÷ Quota · 100% line = on-plan · click for month detail
Quota Attainment by Region
Worst attainment first · click row for detail
RegionPersonaBookingsQuotaAtt%Gap to Quota
Total Bookings
Actuals revenue
Total Cost
Expected cost
Net Income
Bookings − Cost
Net Margin
Net ÷ Bookings
P&L Bridge — Bookings → Cost → Net Income
How expected cost converts bookings to net income · sorted by region
Monthly Bookings vs Cost vs Net Income
All values in $M · click bar for month detail
Monthly Margin % Trend
Net Income ÷ Bookings · 0% line · click for month detail
Net Income by Region
Bookings − Expected Cost · click for detail
Profitability by Region
Bookings, Cost, Net Income, Margin · click row for detail
RegionBookingsCostNet IncomeMargin%Plan CostCost Variance
Actuals
2025 Plan (PoR)
2026 Plan (PoR)
2026 MYR
Annual Bookings — All Versions Compared
Grouped bars: Actuals · 2025 Plan · 2026 Plan · MYR · click for detail
Bookings vs Plan — Gap Analysis
Positive = above plan · Negative = below plan · click for detail
Target Comparison (Targets/Top-Down)
Plan 2025 vs Plan 2026 vs MYR 2026 · click for detail
ASP by Version
Average Selling Price comparison · click for detail
Scenario Summary Table
Annual totals by version and year · click row for detail
ScenarioBookingsTargetCostNet Incomevs Target%Quota Att%
Why This Dashboard Wins
Built directly on Workday Adaptive Planning live data — no exports, no connectors, no lag.
vs Workday Adaptive Planning (Built-in Reporting)
✓ THIS DASHBOARD
Cross-filtered drill-down
Click any region → monthly chart instantly filters to that region's data. AP reports are static grids.
✓ THIS DASHBOARD
Regional contribution waterfall
See exactly how each region builds to the WW total. AP can't produce this view from its own data.
✓ THIS DASHBOARD
AI Analyst with full AP context
Ask questions in plain English. The AI knows your account codes, version logic, and region structure. AP has no AI layer.
✓ THIS DASHBOARD
Click-through everywhere
Every tile, chart, and row opens a detail panel. AP reports require separate report runs to drill down.
vs PowerBI + AP Connector
✓ THIS DASHBOARD
Zero setup — live SOAP API
No connector, no data model, no scheduled refresh. Data pulls directly from AP v33 at page load. PowerBI requires days of setup and ETL.
✓ THIS DASHBOARD
AI that understands AP semantics
PowerBI Copilot is generic. This AI knows that bookings = quota_att, understands completedThru, and knows your 11 leaf regions by name.
✓ THIS DASHBOARD
Single workflow — no tool switching
Analyze data and ask the AI in the same tab. With PowerBI you switch between the report and a separate AI tool manually.
✓ THIS DASHBOARD
Multi-version comparison native
Actuals vs 2025 PoR vs 2026 PoR vs MYR in one chart. PowerBI would need manual version management in the AP connector.
Only Possible Here
Streaming AI answers
Responses stream token-by-token like a conversation. No waiting for a report to run.
🎯
Purpose-built layout
Designed for this exact planning structure — Exec, Regional, Quota, Cost, Scenarios in one flow.
🔄
No stale data
Pulls live from AP at every page load. No scheduled refresh, no export lag, no version drift.
WW Pipeline
2026 Plan pipeline $
WW Gap to Target
Balance to book YTD
Coverage Ratio
Pipeline ÷ Gap (3x = healthy)
Regions At Risk
Coverage below 3x
Pipeline vs Gap to Target by Region
2026 Plan YTD · Blue = Pipeline · Red = Balance to Book
Coverage Ratio by Region
Pipeline ÷ Gap · dashed line = 3× target threshold
Region Pipeline Detail
RegionSegPipelineGap to TargetCoverageStatus
Total HC (Ramped)
Currently fully ramped reps
New Reps Fully Ramped
New hires completing ramp
Still Ramping
New hires in ramp period
Regions Tracked
Regions with HC data
Monthly Headcount Trajectory
Stacked: Existing Ramped (blue) · New Ramped (green) · New Ramping (amber)
Ramped vs Ramping by Region
Latest month snapshot · green = productive · amber = still ramping
WW MQLs (YTD)
Marketing qualified leads
MQL → SQL Rate
Conversion to sales qualified
SQL → Demo Rate
Demos booked per SQL
BDR Bookings Target
2026 YTD BDR-sourced
Demand Gen Funnel — YTD Totals
WW cumulative Jan–Jun 2026 · Plan · each stage shows count and conversion to next
Monthly Funnel Volume
MQL, SQL, Demos, Proposals — WW monthly trend
BDR Bookings Target by Region
YTD 2026 Plan · BDR-sourced booking target
2025 Actuals
vs Plan
2026 YTD Actuals
Jan–Jun actual
FY26 Plan Target
Plan of Record
Mid-Year Revisit
Revised target
Forecast Fan — Actuals vs All Plan Versions
Solid = Actuals through Jun 2026 · Dashed lines = Plan divergence paths · Shaded band = scenario uncertainty range
▲ Jun 2026 — actuals end here, plans diverge
2025: Actuals vs Plan of Record
Monthly bookings vs 2025 PoR target
2026 YTD: Actuals vs Competing Plans
Jan–Jun 2026 actuals vs FY26 PoR and MYR monthly targets
Regions on Map
11 sales territories
Best Territory
Highest bookings
Avg Attainment
WW quota att%
At-Risk Regions
Below 80% att
Territory Bubble Map — 2025 Actuals
Circle size = bookings volume · Color = quota attainment (green ≥100% · amber 80–100% · red <80%)
Bookings
Quota
Attainment
Segment
≥100% attainment
80–100%
<80%
Larger = more bookings
Territory Performance Detail
2025 actuals · sorted by bookings
TerritorySegGeoBookingsQuotaAtt%vs Plan%Net Income
Performance Scorecard — AP Style
Key metrics across all versions · green = beat plan · red = missed
Metric 2024 Actuals 2025 Plan 2025 Actuals 2025 Variance 2025 Var% 2026 Plan 2026 MYR 2026 YTD Trend
Bookings — 3-Year Trend
Annual actuals 2021–2026 YTD
Quota Attainment by Year
Bookings ÷ quota · 100% line = on-plan
Net Income Trend
Bookings minus cost · actuals vs plan
WW Quota Att
Bookings / Quota
Regions ≥100%
On or above quota
Regions 80–100%
Near quota
Regions <80%
Underperforming
FY26 Plan Target
2026 Plan of Record
Total Headcount
Curr + new hires
Avg Selling Price
ASP from plan
Productivity / Rep
Target ÷ headcount
⧖ Drag the sliders below to model different capacity scenarios. Output updates in real time.
Average Selling Price (ASP)
Base: $—
Productivity / Rep ($K ARR)
Base: $—
Total Headcount (reps)
Base: — reps
Projected Bookings
HC × Productivity
vs FY26 Plan
Implied Deals
Bookings ÷ ASP
Sales Efficiency
Bookings ÷ Cost
Sensitivity Analysis
Impact of each lever on projected bookings (vs base plan)
Scenario Comparison
Your model vs Plan2026, MYR, and Actuals run-rate
Region Capacity Allocation
2026 Plan targets and cost by region
RegionSegFY26 TargetFY26 CostMargin% of WW

Ask anything about ABC Corp — bookings, quota, cost, scenarios, regional performance.

Okorio AI Analyst
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Region Detail
2025 performance
Monthly Bookings vs Quota
Key Metrics
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Model Overview
Live tenant metadata and loaded version registry
Version KeyAP IDLabelRegions LoadedPeriod RangeTotal Rows
Region Manifest
CodeAP NameAP IDSegmentGeoPersona
API Health & Latency
Live connectivity test against the AP SOAP endpoint
Raw Data Inspector
Fetch raw monthly values for any version / field / region directly from the AP model cache
Data Completeness Audit
Row counts per region × version × field — zeros shown in red
Account Catalogue
All AP account codes and field aliases known to the model
Cache Inspector & Refresh
In-memory DATA state and full AP re-pull
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