Progressive business case builder. Each step adds depth — results available at any point.
↓ Click any row in the table below to add or edit your own estimate.
Each subprocess uses a specific mix of AI technologies (Document AI, RPA, ML, etc.). Each technology creates value in different ways. This shows where the value comes from across the 15 subprocesses shown on the left, weighted by confidence-adjusted savings potential.
T1 = direct cost impact · T2 = operational (quantifiable, indirect)
Both T1 and T2 flow through to all financial calculations. These are directional estimates — each organization should apply their own realization assumptions based on this breakdown.
| # | Code | Subprocess | BA | Range | Benchmark | Confidence | Spread |
|---|---|---|---|---|---|---|---|
| 1 | CM01 | Credit Evaluation & Scoring | Sales | 55–75% | 65.0% | Strong | ±10% |
| 2 | PD01 | Condition Monitoring & Anomaly Detection | Asset Management | 50–70% | 60.0% | Strong | ±10% |
| 3 | RC01 | Resume Screening & Shortlisting | Human Resources | 45–65% | 55.0% | Strong | ±10% |
| 4 | CT01 | Inbound Call Routing & Triage | Service | 50–70% | 54.0% | Solid | ±10% |
| 5 | IS01 | Incident Classification & Routing | Information Technology* | 50–65% | 51.8% | Solid | ±8% |
| 6 | AP01 | Invoice Processing & Capture | Finance | 45–65% | 49.5% | Solid | ±10% |
| 7 | QI01 | Incoming Quality Inspection | Manufacturing | 45–65% | 49.5% | Solid | ±10% |
| 8 | TL01 | Route Planning & Optimization | Supply Chain | 55–75% | 48.8% | Moderate | ±10% |
| 9 | PR01 | Purchase Requisition Processing | Sourcing & Procurement | 35–55% | 45.0% | Strong | ±10% |
| 10 | OM01 | Sales Order Entry & Validation | Sales | 40–60% | 45.0% | Solid | ±10% |
| 11 | IM01 | Goods Receipt & Putaway | Supply Chain | 40–55% | 42.8% | Solid | ±8% |
| 12 | DP01 | Statistical Forecasting | Manufacturing | 35–50% | 42.5% | Strong | ±8% |
| 13 | AG01 | User Access Review & Certification | Governance, Risk & Compliance* | 40–60% | 37.5% | Moderate | ±10% |
| 14 | FS01 | Dispatch & Scheduling | Service | 35–55% | 33.8% | Moderate | ±10% |
| 15 | PY01 | Payroll Calculation & Validation | Human Resources | 30–45% | 33.8% | Solid | ±8% |
The Executive Value Cockpit is a progressive AI business case builder that transforms research-backed benchmarks into actionable financial analysis. It guides you through five steps — each adding a layer of depth to your AI investment decision. You can stop at any step and still have a useful output.
Start with a confidence-weighted ranking of AI savings potential across 127 enterprise subprocesses. Each benchmark is derived from 280+ data points across 120+ research organizations (McKinsey, Deloitte, Everest Group, and others), weighted by source credibility. You can override any benchmark with your own estimate based on internal data, vendor claims, or pilot results.
Classify implementation complexity for each subprocess as Small, Medium, Large, or Extra Large. Default sizing is derived from the dominant AI technology type — Document AI and simple RPA projects default to Small, while complex ML ensembles or multi-step Agentic AI workflows default to Extra Large. Combined with savings potential, this identifies Quick Wins (high opportunity, low effort) versus Strategic Bets (high opportunity, high effort).
Layer risk ratings (High, Medium, Low) that capture operational, compliance, and regulatory potential disruption along with financial uncertainty. Default risk ratings are mapped against EU AI Act Annex III classifications, SOX Section 404 controls, and EEOC/Title VII employment law. The Risk × Effort matrix gives you a go/no-go signal for each subprocess.
Enter your annual operating cost base by business area or individual subprocess to convert percentage savings into dollar opportunity. The cockpit calculates implementation cost estimates based on effort sizing, simple ROI, and payback period for each subprocess. A dollar opportunity chart shows which business areas hold the most value.
Set your discount rate and time horizon to generate a full discounted cash flow analysis. The cockpit calculates Net Present Value (NPV), Internal Rate of Return (IRR), payback period, and portfolio ROI. Three scenario comparisons (conservative, base, optimistic) show sensitivity to implementation risk and adoption speed. A portfolio optimizer helps you maximize returns within a budget constraint.
The Executive Value Cockpit is a free, interactive AI business case builder. It helps you quantify the financial impact of AI adoption across enterprise processes using research-backed benchmarks from McKinsey, Deloitte, Everest Group, and 120+ other organizations.
Each savings benchmark is derived from 280+ data points across published research. Sources are weighted by credibility — peer-reviewed studies and large-sample surveys carry more weight than vendor white papers. The result is a confidence-weighted savings range (min–max) for each of the 127 enterprise subprocesses.
Confidence weighting adjusts the raw savings midpoint based on how well-supported the benchmark is by research. Strong confidence (many high-quality sources) applies a 1.0× multiplier. Thin confidence (few or low-quality sources) applies a 0.5× multiplier. This prevents poorly-evidenced benchmarks from inflating your business case.
Yes. Click any row in the table to enter your own savings estimate, confidence level, and source. Your custom values override the research benchmarks for your session. You can base your estimates on internal pilot results, vendor claims, consultant reports, or professional judgment.
The cockpit calculates Net Present Value (NPV), Internal Rate of Return (IRR), payback period (in months), and portfolio ROI. It uses a discounted cash flow (DCF) model with configurable discount rate, time horizon, project duration, and three scenario comparisons (conservative, base, optimistic).
The cockpit supports six major enterprise platforms: SAP (ECC, S/4HANA, Cloud), Oracle (EBS, Cloud, JDE), NetSuite, Workday, Salesforce, and ServiceNow. Assessment results from any supported platform carry directly into the cockpit for financial modeling.
Yes. Your custom benchmarks and cost inputs are tied to your browser session and are not visible to other users. If you create an account, your data is associated with your user profile. An anonymized, aggregated copy of savings estimates (without company details, notes, or source URLs) contributes to community benchmarks.
Effort sizing (S/M/L/XL) is derived from the dominant AI technology type and number of integration points — Document AI projects default to Small, while complex ML ensembles default to Extra Large. Risk ratings (H/M/L) are mapped against EU AI Act Annex III classifications, SOX Section 404 controls, and EEOC/Title VII employment law.
Yes. Both effort sizing and risk ratings are fully customizable. On Step 2, use the Effort dropdown for each subprocess to override the default sizing. On Step 3, use the Risk dropdown to set your own risk level. Your overrides immediately update the quadrant classification (Quick Win, Strategic Bet, etc.), dollar calculations, and all financial metrics.