A driver-based operating expense model connects forecast costs to the business activity that causes them. During a Pigment implementation, finance teams can build this connection into planning dimensions, assumptions, workflows, and review steps instead of relying on disconnected spreadsheet inputs. The result should be a forecast that is easier to update and explain—not a model that adds complexity for its own sake.

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What does a driver-based operating expense model do?

A traditional expense forecast often starts with last year’s actuals and applies a percentage change. That approach can be useful for stable costs, but it can hide what is changing. A driver-based model makes the underlying assumptions explicit. It might forecast recruiting expense from planned hires, software spend from licensed users, or travel from expected trips and an average cost per trip.

The goal is not to force every general-ledger account into a formula. It is to choose a level of detail that improves decisions. A useful model helps finance answer questions such as: Which teams are driving the increase? What happens if hiring is delayed? Which costs are committed, and which can still be adjusted? Those answers should be traceable to assumptions that budget owners recognize, not just to calculations that only the model builder can explain.

In Pigment, the design can connect operating expenses to organizational structures, time periods, scenarios, and other planning areas. That makes the model part of an integrated planning process rather than a separate spreadsheet exercise. For context on broader finance work, see Amvent’s guide to FP&A transformation and its overview of what an EPM system is.

Which expenses should be driven by operating assumptions?

Start by grouping costs according to how they behave, not simply by copying the chart of accounts. Finance and budget owners can then agree on a forecasting method for each group. Some expenses are driven by operational volume; some are tied to headcount; others are contractual, discretionary, or best handled as a direct input. A model may combine methods, provided users understand which lines use drivers and which rely on reviewed assumptions.

These are design examples, not universal accounting rules. Keep forecast categories aligned with the company’s chart of accounts and financial reporting needs. Where a modeling choice could affect accounting treatment or reporting, confirm it with the finance team and applicable accounting guidance; the Financial Accounting Standards Board is a source for U.S. accounting standards. The operating model should support management planning without replacing the organization’s accounting records.

How should finance choose the right cost drivers?

A useful driver has a clear relationship to the cost, an owner who can explain it, and a source the team can update. The relationship does not need to be perfectly linear. It does need to be understandable enough that a budget owner can challenge the assumption and finance can show its impact. Before adding a driver, ask whether it improves the forecast or simply creates another input to maintain.

1. Find the material cost pools. Review actuals and the current forecast to identify categories with meaningful value, volatility, or decision impact. Do not spend equal design effort on every account.

2. Ask what changes the cost. Interview budget owners about headcount, contracts, usage, volume, timing, and one-off events. Distinguish a genuine driver from a convenient proxy.

3. Check whether the driver can be maintained. Confirm who owns the assumption, where source data comes from, how often it changes, and whether teams can provide it at the needed level of detail.

4. Test the relationship with prior periods. Compare driver movement with historical expense patterns. Treat this as a reasonableness check, not proof that the same relationship will hold in the future.

5. Choose a fallback for uncertainty. If reliable operational data is unavailable, use a transparent manual assumption or a simpler trend method rather than implying false precision.

For example, a software expense line may include a fixed annual commitment and usage-based licenses. A single percentage uplift would obscure the distinction. Modeling the contract as a committed amount and additional seats as a separate driver makes the forecast easier to review. If the available data cannot support seat-level forecasts, a team-level assumption may be a better first release. The model should make the boundary between known commitment and forecast assumption visible.

This is a practical scoping question as much as a modeling question. Amvent’s EPM requirements-gathering guide can help teams document needs before translating them into a model. For broader evaluation questions, see EPM selection criteria.

How should the model be structured in Pigment?

Model structure should reflect the decisions and ownership the planning process requires. A common starting point is to plan by account, organizational unit, period, scenario, and version, then add relevant drivers or operational dimensions where they create value. A dimension should earn its place: it should support a real view, calculation, input, or control. Avoid adding detail solely because a source system contains it.

Clarify the relationship between the operating structure and the account structure. A manager may plan at department level while finance needs consolidated views by account. Define how those views reconcile, who owns mappings, and how reorganizations will be handled. Also decide whether the model needs employee-level detail, role-level planning, or only summarized headcount assumptions. More granular detail can improve analysis, but it increases the data and process burden. The appropriate level depends on the questions finance needs to answer and the capacity of teams to keep inputs current.

Keep assumptions distinguishable from calculated results. Users should be able to identify which values they enter, which come from integrated data, and which the model calculates. Document calculation logic in language budget owners understand. Amvent’s articles on Pigment model design and model dimensionality offer related design context.

Plan for scenario comparisons from the outset. Finance may need to compare a baseline with a hiring delay, a discretionary-spend reduction, or a change in software usage. The model should make the assumption change clear and show where its effect flows. Avoid creating a separate copy of the model for every scenario; define a controlled way to compare versions and understand which assumptions changed. Agree on how users will label and review scenarios so the comparison remains meaningful after the planning cycle closes.

How do workflows make the forecast usable?

A model is only one part of the process. Budget owners need to know what to review, when to submit, and how finance will resolve questions. Define the workflow around actual planning responsibilities rather than a generic sequence of approvals. Make the request clear enough that an owner can submit a useful plan without needing finance to interpret every field.

• Set ownership: Assign each input area to a role or team, and define who can edit assumptions versus review them.

• Make the request specific: Explain the planning period, required detail, source expectations, and treatment of known commitments.

• Use clear statuses: Distinguish work that is not started, in progress, submitted, under review, and approved, using statuses that fit the organization’s process.

• Build review into the cycle: Give finance a way to flag outliers, ask questions, and return inputs for correction without losing context.

• Record decisions: Preserve the rationale for significant assumption changes so the next forecast does not depend on institutional memory.

Reviewers should be able to trace a material change from input to calculated expense and understand its effect on the total. That is especially important when department-level submissions feed a consolidated forecast. For workflow design principles, see Amvent’s guide to building reviewable planning cycles and its advice on stakeholder alignment.

What should implementation testing cover?

Testing should confirm more than whether the model opens and calculations run. Finance and representative budget owners should test realistic planning tasks from start to finish. Use a small set of test cases that includes ordinary updates, exceptions, and scenario changes.

• Enter and revise a driver, then confirm the expected expense calculation and roll-up.

• Change a hiring date or planned volume and confirm that the impact appears in the right periods and organizational views.

• Test a fixed commitment alongside a variable component to ensure the two do not double count.

• Submit, review, return, and approve an input to confirm the workflow and access behave as intended.

• Compare scenarios and verify that reviewers can identify the assumptions responsible for the difference.

• Reconcile model outputs to agreed source totals and explain any expected timing or classification differences.

Include users who will enter and review the plan, not only the project team. Ask them to complete real tasks without step-by-step coaching, then note where labels, instructions, or process steps cause hesitation. Amvent’s guide to EPM implementation testing covers the role of structured user acceptance testing in a finance project.

Set simple acceptance criteria before the build is considered ready. For example, finance might require that all in-scope departments can submit their plan, material assumptions have an owner, key totals reconcile to an agreed source, and scenario differences can be explained. Criteria should describe observable tasks and outputs, not just that a feature exists. They help the project team distinguish a defect from a request for a future enhancement. Keep a short decision log for unresolved questions, record the chosen treatment, and assign an owner and review date for anything deferred. This gives finance a practical way to revisit trade-offs without delaying the initial release indefinitely.

How can teams scope a useful first release?

A first release should solve a visible planning problem while establishing patterns that can be reused. Agree on the forecast horizon, planning cadence, organizational level, and expense groups in scope. Then list what the model must produce: for example, a department forecast by account, a view of committed spend, or a way to compare the effect of a hiring change. Those outputs help prevent the project from expanding into every possible planning request before the core workflow works.

Map each planned input to an owner and a source. That source might be an approved operating plan, a contract schedule, an HR data set, or a reviewed assumption supplied by the budget owner. Identify how often it changes and who resolves a mismatch. If a source is not ready for integration, decide whether a controlled file upload or manual input is acceptable for the initial scope. Record that as a known dependency rather than quietly treating the assumption as a permanent solution.

Set an explicit boundary between the first release and later enhancements. A team might launch with department-level expense plans and a small number of important drivers, then add more detailed operational inputs after owners have a stable process. Prioritize additions by decision value and maintenance effort. This protects finance from building a detailed model that budget owners cannot keep current, while leaving a clear path to extend it.

Before build begins, align on how forecast changes will be reviewed. Define a small number of checks such as period-to-period movement, comparison with actuals, variance against budget, and confirmation of material commitments. The exact checks depend on the company’s process; agree what reviewers should investigate and who closes each question. For finance leaders considering how planning areas connect, Amvent’s connected planning evaluation guide offers a related perspective.

What commonly makes an operating expense model harder to use?

Too many drivers. Modeling every expense with a bespoke formula can create a maintenance problem. Start with material categories and add detail when it supports a decision or improves forecast quality.

Unclear ownership. A driver with no accountable owner quickly becomes stale. Assign an owner and define the refresh point, including what to do when source data is unavailable.

False precision. A detailed formula can look authoritative even when its inputs are weak. Label assumptions, show their source, and use a simpler method when the evidence does not justify more granularity.

Mixing committed and discretionary costs. A single forecast line can make it difficult to see what can change. Where the distinction matters to decisions, model the components separately and identify the contract or owner behind them.

Building around a one-time cycle. A process optimized only for annual budgeting may not support monthly forecasts or mid-cycle changes. Confirm which cycles the first release must serve, then design a foundation that can be extended without overbuilding at launch.

Ignoring adoption and handover. A model that only its builders can maintain is fragile. Include documentation, role-based training, and a clear support path. Amvent’s guidance on EPM go-live handover explains why ownership after launch should be planned before the project closes.

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Frequently Asked Questions

Does every operating expense need a driver?

No. Use drivers where they clarify what causes a cost or help leaders make a decision. Stable, immaterial, or poorly understood expenses may be better handled with a direct input or a simpler trend assumption.

Should the model forecast expenses by account or department?

Usually it needs to support both views, but the right input level depends on ownership and use. Define how department plans map to accounts, then make sure the model can roll up to the views finance and leadership need.

Can a team start without complete operational data?

Yes. Begin with the data that is reliable, make assumptions visible, and assign owners to improve the inputs. A transparent interim assumption is more useful than a complex calculation based on data that cannot be maintained.

How should finance handle costs that are partly fixed and partly variable?

Separate the components when the distinction affects decisions or forecast accuracy. For example, show a contract commitment separately from usage-driven seats, and document how each component is updated.

How does a driver-based model fit into a Pigment implementation?

It is one part of the planning design. The implementation also needs agreed requirements, model structures, data connections where needed, workflows, testing, user enablement, and a handover plan. Teams should confirm scope and sequence against their own planning priorities.

Build the model around the decisions finance needs to make

A strong driver-based operating expense plan links material costs to understandable assumptions, gives budget owners a practical way to contribute, and lets finance review changes with confidence. Begin with a focused use case, test it with real users, and expand the model as the planning process matures.

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Amvent is a Toronto-based boutique EPM consulting firm and official Pigment Delivery Partner. Its customer-to-consultant perspective includes having led a 250+ user Anaplan-to-Pigment migration as an end-customer. If you are shaping a Pigment implementation, discuss your priorities with the team.

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A well-scoped first release can give finance a clearer forecast today and a sound foundation for connected planning over time.