Multi-Client Profitability
This use case explains how to analyse profitability across multiple clients, studios and work types for media, agencies and creative studios in Model Reef.
You will:
Attribute revenue and costs to clients and studios using branches and categories.
Combine retainers, projects, production and overhead structures into client P&L views.
Build dashboards to compare client and portfolio performance.
Use scenarios to test pricing, scope and portfolio mix changes.
Model Reef is not a CRM or case management system. It provides a financial view of client profitability based on the revenue and cost structures you define.
When to use this pattern
Use this pattern when:
You serve many clients across multiple studios or locations.
You want to understand which clients and portfolios drive profit or loss.
You need to support decisions on pricing, investment, scope or disengagement.
You want to link client strategies to staffing and production plans.
It builds on:
Retainer and Project Pipeline Forecast
Staffing and Creative Resource Planning
Production Budgeting and Delivery Models
Architecture overview
Multi client profitability modelling uses:
Branch and category structure
Branches for studios, offices or large clients.
Categories to separate revenue, direct costs and overheads.
Revenue and cost attribution
Mapping of retainer and project revenue to clients.
Mapping of production and staffing costs to clients or client groups.
Allocation of shared overheads by driver.
Client P&L views
Direct contribution margin by client.
Fully loaded margin including allocated overhead.
Portfolio and studio level summaries.
Scenario and portfolio analysis
Client mix and scope changes.
Pricing and rate changes.
Growth or contraction in specific segments.
Decide how to represent clients in the model
There are three main patterns:
Branch per key client
For a small number of large clients.
Enables full client level P&L and dashboards.
Categories or tags for client segments
For large numbers of smaller clients.
Groups clients into meaningful segments, for example sector or size.
Hybrid
Branches for strategic or very large clients.
Segments for the remainder.
Choose a pattern that matches your management reporting, and implement branches and categories accordingly.
Attribute revenue to clients and studios
From the Retainer and Project Pipeline Forecast:
Map retainer revenue to client branches or client categories.
Map project revenue to specific clients or client segments.
Distinguish between fee revenue and pass through or media revenue if you want to analyse gross income separately.
Ensure that each Revenue variable clearly identifies:
Client or segment.
Studio or office responsible.
Work type (retainer, project, production, media).
This supports flexible reporting by client, studio and work type.
Attribute direct costs to clients and work types
From Staffing and Creative Resource Planning and Production Budgeting and Delivery Models:
Map staff cost where possible to the clients or client sets they primarily serve.
Map production costs to the clients whose projects they relate to.
Keep shared or pooled costs in studio or central branches to be allocated later.
Create Opex and Staff variables such as:
Staff - Account Team - Client X.
Staff - Dedicated Studio Team - Client Y.
Production Cost - Campaign Z - Client X.
Pooled Production Cost - Studio Brand.
This enables clear separation of direct client costs from shared overhead.
Allocate shared overheads
For overheads that are not directly attributable to a single client, such as:
Studio management and leadership.
Shared creative or production pools.
Office and facility costs.
Central functions such as finance, HR or marketing.
Define allocation drivers in the Data Library, for example:
Share of Revenue per client.
Share of Direct Costs per client.
Share of Staff Headcount or time per client.
Manually set allocation percentages for key clients and segments.
Then create allocation variables that push a portion of total overhead into each client or segment P&L. This can be done via formulas that reference total overhead and allocation percentages.
Build client and portfolio P&L views
Using reports and dashboards, construct views that show for each client or segment:
Fee revenue and pass through revenue.
Direct production and staff costs.
Contribution margin.
Allocated overhead.
Fully loaded margin and EBITDA contribution.
At portfolio level, create views by:
Studio or location.
Sector or client type.
Work type, for example retainer versus project.
Size tier, for example strategic, core and long tail clients.
These views help you see which parts of the book of business drive profit and which consume disproportionate capacity or overhead.
Use scenarios for pricing, scope and portfolio strategy
Clone the base model into scenario models to explore:
Price increases or discount reductions for specific clients or segments.
Scope expansion or reduction for individual clients.
Focusing on higher margin sectors or work types.
Discontinuing or reshaping unprofitable relationships.
Shifting work between studios or locations.
In each scenario, adjust:
Revenue rates and volumes.
Direct costs and sourcing mix.
Overhead allocation assumptions.
Client mix and onboarding or offboarding timelines.
Compare scenarios using:
Client and portfolio level profitability.
Studio capacity and utilisation impacts.
Cash and working capital implications.
Valuation impacts where you choose to extend client cases into cashflow and valuation logic.
Calibrate against historical client reports
To build confidence:
Import historical revenue and cost by client or segment where available.
Rebuild last year or last twelve months in the model to match reported client profitability.
Calibrate allocation drivers and sourcing assumptions until model outputs align with management views.
Use this calibrated baseline as the starting point for forward looking portfolio scenarios.
Check your work
Client level P&Ls are consistent with internal reporting for key clients.
Overhead allocations are reasonable and clearly documented.
Scenario outputs support concrete portfolio and pricing decisions.
Stakeholders can trace from high level client metrics down to underlying assumptions.
Troubleshooting
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