Customer Current State

Configure your baseline operating environment

Controls
Channels in Scope
Annual Volume
Inbound Voice
Outbound Voice
Email
Chat
Agent AHT (minutes)
Inbound Voice
Outbound Voice
Email
Chat
Delivery Locations *
Agent Performance
%
%
Current Spend Enter any one
Headcount —
Total Volume —
Est. Cost/Call —

Transformation Inputs

Configure to-be delivery model, automation, AHT reduction and deflection

IT Requirements
Volume
%
%
To-Be Delivery Locations Post-transformation target model
Automation (Agentic AI)
ChannelAutomation %Ramp Up (months)
Inbound Voice
%
Outbound Voice
%
Email
%
Chat
%
AHT Reduction
ChannelReduction %Ramp Up (months)
Inbound Voice
%
Outbound Voice
%
Email
%
Chat
%
Target Agent Performance
%
%
%
Deflection
%
%
%

Pricing & Margins

BPO and IT cost parameters

BPO Pricing
%
%
%
IT Asset Pricing
%
CaaS Pricing
Agent Assist Pricing

Use Cases

Industry-specific AI use cases — auto-populated from selected industry

Select an industry in Customer Inputs to load use cases

No industry selected yet. Go to Customer Inputs and choose an industry.

Generic AI Use Cases — All Industries
Analyse customer sentiment across multiple customers
Analyse customer sentiment for individual customer records
Answer simple, generic, frequently asked questions (self-service)
Generate dialog for conversational AI
Generate test cases for training conversational AI
Increase personalisation of customer interactions
Proactive push notifications & outbound engagement
Contact analytics and root cause analysis
Predict a customer's next interaction
Review and quality-score conversational AI interactions
Summarise and categorise complaints
Summarise contacts at scale (inbound contacts by type)
Support human agent training with AI-generated scenarios
Support human agents responding to customers (Agent Assist)
Translate content into different languages in real-time

Business Case

5-Year Value Summary

⚙ Backend Configuration

Edit market rates, IT asset pricing, inflation, and default assumptions.

5-Yr As-Is Spend ($m)
—
Status quo trajectory
5-Yr To-Be Spend ($m)
—
Post transformation
Total Savings ($m)
—
5-year cumulative
HC Productivity Gain
—
Y5 To-Be vs Y5 As-Is
Y5 As-Is HC
—
Status quo at Year 5
Y5 To-Be HC
—
Post transformation Year 5
Savings %
—
(As-Is − To-Be) ÷ As-Is
Year-by-Year Summary
As-Is Y1 Y2 Y3 Y4 Y5 5-Year Total
Savings vs Spend ($m)
Headcount Journey
Savings Waterfall
Assumptions Summary

Transaction Pricing

5-year unit economics — As-Is, Digital (Agentic AI) and Human channels

Savings %
—
(As-Is − To-Be) ÷ As-Is spend
As-Is Price / Transaction
—
5yr As-Is spend ÷ 5yr As-Is volume
Digital (AI) Price / Transaction
—
5yr IT cost ÷ 5yr Agentic AI volume
Human Price / Transaction
—
5yr BPO cost ÷ 5yr Human volume
Transaction Pricing — 5-Year Summary
Metric 5-Yr Spend ($m) 5-Yr Volume Cost Driver Price / Transaction
Run the Business Case first to populate transaction pricing.
Methodology

As-Is Price / Transaction = Total 5-year As-Is spend ÷ Total 5-year As-Is contact volume (all channels, growing at YoY rate).

Digital (Agentic AI) Price / Transaction = Total 5-year IT cost ÷ Total volume deflected to Agentic AI over 5 years. Digital volume is calculated by applying the month-on-month containment ramp (automation % × ramp period) to post-call-avoidance volume each year.

Human Price / Transaction = Total 5-year BPO cost ÷ Total volume handled by human agents over 5 years. Human volume = post-call-avoidance volume minus digital volume (i.e. contacts not deflected to digital).

Savings % = (5-Year As-Is Spend − 5-Year To-Be Spend) ÷ 5-Year As-Is Spend.

⚙ Backend Configuration

Market Rates — Annual Fully-Loaded Cost per Agent ($)
Global Assumptions
IT Asset Pricing
Margin Defaults