Support/Service Team Capacity

This use case explains how to model support and service team capacity, workload and cost for telecommunications and IT services businesses in Model Reef.

You will:

• Represent support and service functions by team, role and location.

• Build drivers for contact volumes, tickets and handling effort.

• Link workload to headcount, utilisation and service levels.

• Connect support economics to P&L, Cashflow and customer strategies.

Model Reef is not a ticketing or contact centre platform. It uses aggregated workload and staffing assumptions, not per contact data.

When to use this pattern

Use this pattern when:

• Support and service are major cost and experience drivers.

• You need to align headcount with subscriber and contract growth.

• You want to test service level and outsourcing strategies.

• You need to show how customer propositions affect support workload.

It ties directly into:

• Recurring Services Revenue Model

• Contract Renewal Forecasting

• Build a Staffing Cost Model

Architecture overview

Support and service capacity modelling uses:

1. Structure

   • Branches for regions, channels or support functions.

   • Staff variables for roles and teams.

2. Workload drivers

   • Contacts or tickets per customer per period.

   • Average handling time per contact.

   • Mix of channels (phone, chat, email, self service).

3. Capacity and staffing

   • FTEs per role and location.

   • Working hours and schedule patterns.

   • Target utilisation and occupancy.

4. Financial outputs

   • Staff cost and overhead.

   • Cost per contact or per customer.

   • Impact on EBITDA and cash.

1

Set up support and service branches

In the branch tree, create branches for your support structure, for example:

• Support and Service

  • Contact Centre - Country A

  • Contact Centre - Country B

  • Technical Support - Region Wide

  • Field Service Teams

Alternatively, if support is embedded within regions or product units, place support branches under each region or unit.

2

Build workload drivers from subscribers and contracts

From your Recurring Services Revenue and Contract Renewal models, derive drivers such as:

• Subscribers or active contracts per segment.

• Contact Rate per customer per period (for example contacts per customer per month).

• Ticket Rate per active device or service for technical support.

Calculate total workload per period, for example:

• Contacts = Active Customers × Contact Rate.

• Tickets = Active Services × Ticket Rate.

If you use multiple channels, split contacts across channels using mix drivers such as:

• Share of contacts via phone, chat, email, self service.

3

Convert workload into effort and FTE requirements

Create drivers for handling effort, such as:

• Average Handling Time per contact in minutes by channel.

• After call work or wrap time allowances.

• Shrinkage factors for training, breaks and other non contact time.

Compute total effort, for example:

• Total Handling Minutes = Contacts × Average Handling Time.

• Required FTEs = Total Handling Minutes divided by (Working Minutes per FTE × Target Utilisation).

Use these calculations as driver variables to inform staffing decisions.

4

Model staff headcount, cost and timing

Create Staff variables for each support role, for example:

• Staff - Contact Centre Advisors - Country A.

• Staff - Team Leaders - Country A.

• Staff - Technical Support Engineers.

• Staff - Field Technicians.

For each, specify:

• Headcount per period based on FTE requirements.

• Salary and on cost assumptions.

• Start dates for hires and any planned changes.

• Payment frequency and delay settings for cash timing.

Where you use outsourcers, represent them either as:

• Staff with different cost structures and flexibility, or

• Opex variables linked to volume and contracted unit rates.

5

Link service levels and self service to workload

Define drivers for:

• Target or actual service levels and first contact resolution.

• Proportion of queries handled by self service without agent involvement.

• Impact of product design or customer communication on contact rates.

Represent improvements in self service, product and process design as changes to:

• Contact Rate per customer.

• Channel mix toward lower cost channels.

• Average Handling Time.

Use scenarios to test investment in digital service and its payback in reduced contact volumes and staff cost.

6

Use scenarios for sourcing, quality and service strategy

Clone the base model into scenario models to explore:

• Increasing or decreasing service levels.

• Shifting work between internal teams and outsourcers.

• Moving work to lower cost locations.

• Changing product or policy to reduce contacts.

• Upskilling teams to improve first contact resolution.

In each scenario, adjust:

• Workload, handling time and self service drivers.

• FTE requirements and sourcing assumptions.

• Pay rates and on costs.

• Target utilisation and service levels.

Compare scenarios using:

• Total support cost and cost per contact.

• Support cost per customer or per unit of revenue.

• Service level and workload metrics.

• Customer retention and NPS metrics where you choose to add them as external inputs or qualitative indicators.

Check your work

• Workload and contact rates reconcile with historical support reports.

• Staffing and cost assumptions align with HR and finance data.

• Scenario outputs are understandable for operations, finance and product teams.

• The model supports decision making on service strategy rather than trying to replicate operational systems.

Troubleshooting

Required FTE numbers look too high or too low

Recheck handling time, shrinkage and utilisation assumptions and confirm that contact rates are on the correct basis (per active customer, per device, etc).

Support cost does not reconcile to P&L

Ensure that all support related costs (internal staff, outsourcers, tools) are mapped into the relevant Staff and Opex variables and categories.

Model is too granular for quick analysis

Aggregate roles, channels or regions where appropriate and use representative averages instead of detailed breakdowns when decisions do not require that level of detail.

Related guides

• Build a Rolling Forecast

• Build a Seasonality Adjusted Forecast

• Model Structure Principles

• Creating Scenarios