FP&A & EPM Buyer's Guide

Most FP&A and EPM software evaluations fail before the first demo—not because the tools are bad, but because the process is broken. The vendor sets the agenda, teams chase feature checklists instead of testing architecture, and nobody models what year-3 costs actually look like.

The EPM market has fundamentally shifted. You're no longer choosing between a few on-prem OLAP cube tools and a couple of cloud platforms. Today's landscape includes:

• Gen-1: Legacy, cube-centric EPM systems (Hyperion, BPC) designed for static reporting, with OLAP architectures that struggle with complex relationships.
• Gen-2: Cloud EPM suites (Planful, Adaptive, Vena, Prophix) optimized for structured planning and consolidation.
• Gen-3: AI-enabled, in-memory planning engines (Pigment, Abacum, Vareto, Runway, Mosaic) focused on flexible modeling and real-time scenarios.

You can't evaluate these generations with the same lens. This guide provides a tech-first, process-first, vendor-neutral evaluation framework designed for mid-market and upper-mid-market companies serious about picking the right platform—not just the best demo.

0.1 Define the Executive Mandate

You need a crisp answer to: "Why are we doing this now?"

Common trigger events:

• Scaling rapidly and outgrowing Excel or first-gen FP&A tools
• Moving to or consolidating on a new ERP
• Increasing entity/currency complexity
• Board pressure for better scenario modeling and transparency
• Painful, error-prone close and forecast cycles

If you can't articulate the mandate in 2–3 bullet points that a CEO would nod at, you're not ready to meet vendors.

0.2 Form the Evaluation Committee

At minimum:

• Sponsor: CFO / VP Finance
• Owners: FP&A lead + Controller/Chief Accounting
• Architecture/Data: IT or data engineering
• Key stakeholders: 1–2 people from ops/sales/supply chain, depending on scope

Define who makes the final decision, who scores vendors, and who has veto power on architecture, data, and security. Write this down. Treat it like a RACI.

0.3 Define Success Metrics

Replace vague goals like "better forecasting" with testable metrics:

• Month-end close reduced by X days
• Forecast cycle time reduced by Y%
• Ability to produce N fully-baked scenarios in under Z hours
• Variance accuracy within ±A% at a given granularity
• Max acceptable time for a scenario recalc (e.g., < 5 seconds for typical user activity)

These become demo and POC test cases, not just project slogans.

0.4 Gather Cross-Functional Input Before Vendors

Talk to FP&A, Accounting/consolidation, Sales/revenue ops, Supply chain/operations, and HR (if workforce planning is in scope).

Prompt them with:

• "What do you do in Excel that you shouldn't have to?"
• "What recurring analysis takes you the longest?"
• "Where do we re-key the same data in multiple places?"

You're not asking for feature wishlists. You're extracting pain and constraints so the eventual solution doesn't create blind spots.

1.1 Map Your Current End-to-End Processes

Keep this simple but complete. Document how actuals get from ERP/CRM/HRIS → FP&A models, how consolidations are produced, how budgets/forecasts are built/reviewed/approved, and how reports and decks are generated and distributed.

Visuals help: one flow diagram for "data in," one for "planning & consolidation," one for "reporting & decisioning."

1.2 Identify Your Primary Bottleneck Class

Most organizations have one dominant bottleneck. Rank yours:

• Data ingestion/integration bottleneck: ETL is manual, brittle, or opaque; multiple ERPs/CRMs with inconsistent mappings; heavy Excel/CSV staging
• Modeling & calculation bottleneck: Scenario calcs are slow; adding drivers or dimensions is risky; "We can't touch that workbook; it might break"
• Consolidation logic bottleneck: Intercompany eliminations are manual; currency translation lives in Excel; ownership changes and matrix consolidation are hard; auditability is weak
• Reporting & distribution bottleneck: Too many manual decks and static exports; no self-service capabilities
• Collaboration/workflow bottleneck: Version chaos, copy-pasted templates; approvals tracked in email

The top one or two bottlenecks will drive your vendor shortlist.

1.3 Translate Pain Into Technical Statements

Make your pain measurable and technical:

❌ Bad: "Our forecasts are slow and painful."

✅ Good: "It currently takes three analysts three days to produce a new revenue scenario because we must manually update and reconcile five linked Excel models."

❌ Bad: "Consolidation is a mess."

✅ Good: "IC eliminations require 2–3 days of manual matching every month; currency translation is done in Excel using VLOOKUP-based rate tables and is not auditable."

1.4 Define 5–10 Non-Negotiables

Examples:

• Intercompany elimination must be fully automated, including plug accounts and support for complex hierarchies
• Scenario calculation must complete in under 5 seconds for common use cases at your current and expected data volumes
• Daily (or more frequent) actuals refresh must be automated and auditable
• Multi-currency translation must align with your accounting policies and be traceable
• No mission-critical process should rely on a single analyst's Excel voodoo

These become go/no-go checks in demos and POCs.

1.5 Evaluate Your Internal Skill Set

Ask honestly:

• Do we have (or plan to have) someone who thinks like a modeling engineer?
• How much appetite do we have for low-level model building vs configuration?
• Are we comfortable learning a more technical tool if it gives us flexibility?

If you don't have people who can think in terms of data models, dependency graphs, and calc chains, a highly flexible engine like Pigment or a deeply configurable platform like OneStream may require more partner reliance. This is not a bad thing—it just needs to be explicit.

2.1 Functional Requirements

Split by domain:

• Planning & Forecasting: Budgeting, driver-based planning, scenario modeling, long-range planning
• Consolidation: Legal and management consolidation, intercompany matching & elimination, multi-currency translation, ownership changes and minority interest, matrix or segment reporting
• Reporting & Analytics: Standard financial statements, management packs, operational reporting, dashboards, commentary capture
• Workflow: Submission & approvals, task orchestration, audit logs and data lineage

Don't write a 600-line requirement sheet. Capture the 30–40 that actually matter to your business.

2.2 Technical Requirements

This is where your evaluation becomes truly differentiated. Focus on:

• Data architecture: OLAP cube, relational warehouse, or hybrid semantic layer. OLAP cubes are fast for financial reporting but can struggle with complex relationships and changing dimensionality.
• Calc engine and scenario handling: In-memory vs disk-bound; how scenarios are represented (copies vs pointers/inheritance); performance characteristics; benchmark expectations per data volume
• Integration style: Native connectors vs generic ETL vs APIs
• Security & governance: Row/column level security, SSO, audit trails
• AI/ML usage: Are "AI" features actual models or just rules? Verify transparency and controllability.

2.3 Business & Industry Requirements

Encode your edge cases:

• Manufacturing: BOMs, production planning, inventory and COGS allocations, plant/line level P&L
• SaaS: ARR waterfall, cohorts, NRR, CAC payback, multi-product/multi-region metrics
• Multi-entity: Complex ownership and rollup structures, joint ventures, regional reporting

Your architecture needs to support these patterns natively, not as spreadsheet hacks glued on later.

2.4 Internal Capability Requirements (Admin Model)

Decide what you want your day-2 operating model to be:

• Business-admin model: FP&A owns most changes and can safely evolve models
• IT-owned model: Central data/IT team controls structures and changes
• Hybrid: Business designs logic, IT maintains infrastructure

Map tools to these realities. Some Gen-3 FP&A platforms emphasize intuitive UX so finance can self-serve, while others assume a heavier implementer/admin layer.

2.5 Build a Weighted Scoring Framework

Weights can shift slightly by company, but this keeps you anchored in engine and architecture, not UI sparkle.

2.6 Write the Demo Script Now

Before you talk to vendors, draft a demo script built on your core planning workflow, consolidation requirements (if applicable), reporting process (e.g., monthly board pack), and 2–3 high-value scenarios to test.

You'll give this script to every vendor and insist they follow it. This flips the power dynamic: they're now performing your process, not their theater.

2.7 Future-Proofing: Design for 24–36 Months Out

Explicitly list future requirements:

• Entities you plan to add
• Acquisitions or divestitures likely
• New regions/currencies
• Deeper SKU or customer-level planning
• Upcoming needs like tax reporting or statutory reporting
• Likely data volume growth (orders of magnitude, not exact numbers)

This prevents you from picking a tool that fits your current shape but collapses the moment you grow—a common risk with simpler Gen-3 tools or Excel-anchored platforms.

3.1 Understand the Generational Landscape

Without getting religious about it, it's helpful to categorize:

• Gen-1 EPM: Heavy, on-prem, cube-centric, powerful consolidation, slower innovation
• Gen-2 cloud EPM: SaaS, standardized workflows, strong connectors, solid consolidation and planning, more rigid modeling
• Gen-3 FP&A/planning tools: Cloud-native, in-memory engines, flexible modeling, sophisticated UX, AI-assisted workflows; consolidation often emerging or lighter

This matters because your bottlenecks and non-negotiables often line up with a generation as much as a vendor.

3.2 Map Vendors to Your Bottleneck Profile

Examples:

• Consolidation-heavy: Complex IC, multi-currency, statutory + management views → Look at platforms with proven consolidation modules and automated elimination engines, like OneStream or other consolidation-focused EPM suites
• Planning/modeling-heavy: Scenarios, driver-based models, granular slices → Lean toward in-memory modeling platforms like Pigment, Vareto, Runway, Abacum, etc., built for flexible models with fast scenario recalculation
• Process-heavy and Excel-embedded: Excel is deeply entrenched, mainly need control and governance → Vena-type solutions can be pragmatic choices

The goal is to avoid shortlisting tools that are structurally misaligned with your primary pain.

3.3 Pre-Eliminate on Architecture, Not Vibe

Before you fall in love with a logo, ask:

• Does the architecture support our data volumes and dimensionality?
• Does the scenario engine align with how often and how deeply we model?
• Can it support consolidation patterns we actually need (IC, ownership, segment)?
• Will integration to our core ERP/CRM stack be native, or a science project?

If the answer to any of those is a hard "no", eliminate early. Don't waste time on demos that are doomed.

3.4 Form a Shortlist of 2–5 Vendors

Ideal number is 3:

• Too many: Decision fatigue and diluted focus
• Too few: Artificially constrained options

3.5 Vendor Briefing & Expectations

Before demo scheduling:

• Share your demo script and context
• Clarify which workflows must be shown
• Share high-level data structures (not full exports yet)
• Explain that technical deep-dives and live changes are part of the evaluation

Vendors who balk at this are telling you something.

3.6 Evaluate Vendor Tech Dependencies

This is your "what else do they secretly depend on?" step:

• Do they rely on a particular warehouse (Snowflake, BigQuery) as a pre-req?
• Are key "platform features" really just embedded third-party tools?
• Is their AI dependent on external models you can't control?
• Is the integration layer actually a separate ETL product they don't own?

You're not looking for "pure" tools—you're looking for transparent, stable ones.

4.1 Vendor Kickoff & Rules of Engagement

Set ground rules clearly:

• Every demo must be driven by your script
• Slides limited (or banned)
• Realistic data and workflows only
• Technical owner present for architecture Q&A
• You will ask for live changes

4.2 Architecture Deep Dive

Ask vendors to show, not just talk:

• High-level architecture diagram
• Where data is stored (and how)
• How they handle dimensions and hierarchies
• How calculations are executed (batch vs on-demand, in-memory vs disk)
• How scenarios are represented (clones vs parameterized structures)
• How they log and audit changes

You don't need to be a database engineer, but you do need to hear answers that make sense and align with your needs.

4.3 Scripted Workflow Demo

Have each vendor walk through:

• A simplified version of your month-end close
• A full forecast cycle (data load → driver update → scenario → report)
• A management reporting cycle (e.g., monthly business review pack)
• Any industry-specific flows (SKU planning, ARR waterfall, etc.)

Force them to stick to the same flow so your side can compare apples to apples.

4.4 Live Stress Test (10–15 Minutes)

This is the part vendors hate but you'll love. Ask them, live:

• "Add a new product and driver."
• "Increase volume for Region X by 5% and show the P&L impact."
• "Create a new scenario branching from current forecast."
• "Change an FX rate and show consolidation impact (if relevant)."
• "Add a simple allocation rule and recalc."

Watch:

• How long it takes
• How complex the steps are
• Whether they need to "call an admin" or drop into code
• How the UI responds under pressure

If simple changes feel like surgery, your admin life will be rough.

4.5 Immediate Post-Demo Scoring

Right after each session, everyone on the evaluation team logs scores for:

• Architecture confidence
• Fit against bottlenecks
• Scenario handling
• Consolidation (if relevant)
• UX and adoption risk
• Overall performance

Do not let impressions decay or rely on memory.

4.6 Hands-On Lite POC (You Build Something)

For your top 1–2 vendors, do a small, time-boxed hands-on:

• Vendor sets up a sandbox with example or masked data
• Your FP&A/IT team builds a small model or report, supported but not hand-held
• You measure how intuitive and resilient the admin experience is

You'll learn:

• How steep the learning curve really is
• Whether your team can own this day-to-day
• How much partner dependence you'd have

5.1 Structured Reference Calls

Ask existing customers:

• What actually went well—and badly—in implementation?
• How long did it really take to get to "live and trusted"?
• How has model complexity/performance changed over time?
• How much do they still rely on Excel?
• How many internal people can administer the tool confidently?

Good references will talk candidly about trade-offs.

5.2 Architecture & Integration Proof

Request:

• High-level architecture whitepapers
• Integration documentation for your specific ERP/CRM/HRIS stack
• Any performance benchmarks they can share for comparable customers

This isn't about catching them out—it's about ensuring your IT/data teams are not flying blind.

5.3 Formal POC (Optional but Powerful)

For complex use cases (heavy consolidation, multi-ERP, multi-currency, or extreme scenario modeling), consider a limited-scope POC:

• One critical use case
• Limited timeframe (e.g., 3–6 weeks)
• Clear success criteria

POCs cost money and time, but they can prevent six-figure mistakes.

5.4 Evaluate Implementation Partners

You're not just buying a platform—you're implicitly choosing an ecosystem. Evaluate:

• Depth of the partner network for that tool
• Experience in your industry
• How many projects they've done with that vendor
• Onshore vs offshore composition
• Bench strength vs reliance on a few "unicorn" consultants

A world-class engine with a weak partner ecosystem is a risk.

5.5 Evaluate Vendor Ecosystem

Check:

• How many certified consultants exist globally/regionally
• Community resources (forums, user groups, Slack communities, etc.)
• Third-party content (blogs, courses, podcasts) discussing real experiences

You're trying to answer: "Are we joining a vibrant ecosystem or an isolated island?"

6.1 Build a Real TCO Model

Include, by year:

• Subscription licenses (with seat and module breakdown)
• Implementation services (vendor/partner + internal time)
• Integration work (initial + ongoing)
• Admin headcount (partial FTEs are still cost)
• Enhancements and change requests
• Training and onboarding costs
• Potential expansion (new entities, new modules)

Anchor this over a 3–5 year horizon.

6.2 Build An Honest ROI Model

ROI in FP&A/EPM projects typically comes from:

• Cycle-time reduction: Faster close and forecast cycles
• Efficiency gains: Fewer manual reconciliations and data prep hours
• Headcount avoidance: Not having to hire that extra analyst or accountant next year
• Decision quality: Better scenario analysis, fewer bad bets

Use conservative assumptions. If ROI still clears your hurdle rate under conservative assumptions, you're in good shape.

6.3 Pricing Benchmarking

Use whatever sources you can: peer conversations, advisors, public references where they exist.

You're looking for ballpark ranges: are you in the same universe as similar-sized companies with similar complexity?

6.4 Negotiation Strategy

Key levers:

• Contract term and renewal structure
• Year-over-year uplift caps
• Price locks for additional named users or capacity
• SLAs for performance and uptime
• Termination rights if certain milestones are not met
• Commercials around implementation overruns (who eats the risk?)

6.5 Model Commercial Recurrence & Escalation

Explicitly model:

• Storage and data overage fees
• API call or integration volume limits
• Incremental price bands when you add entities/regions
• Mandatory support or add-on modules that are effectively required

This is where many SaaS projects go sideways—the year-2 bill is a shock.

7.1 Build the Decision Narrative

Your output should look like a board-ready document or deck that answers:

• Why now, and what's broken?
• What options did we consider?
• How did each vendor perform across the evaluation framework?
• How do they compare on architecture, modeling, data, consolidation, and TCO?
• What's the business case (TCO + ROI)?
• What are the key risks and how will we mitigate them?
• Which vendor do we recommend, and why did the others lose?

This is where your earlier rigor pays off—you're no longer saying "we liked Vendor X more"—you're presenting a defensible, structured decision.

7.2 Final Selection & Close-Out

• Communicate decisions and rationale to all vendors (professionalism matters)
• Lock commercial terms and SOWs
• Get IT, security, and legal sign-offs as needed

7.3 Implementation Readiness Plan

Before project kickoff:

• Confirm internal roles and time commitments
• Align with partners on methodology, milestones, and deliverables
• Define data migration and integration workstreams
• Plan change management and training

Implementation timelines for mid-market FP&A use cases are often 8–14 weeks for a focused scope, but consolidation and multi-country rollouts can extend beyond that. Complexity, not just vendor, drives the true timeline.

7.4 Centralize the Evaluation Artefacts

Store in one shared location:

• Requirements docs
• Demo scripts and recordings
• Scores and comments
• Architecture and commercial docs
• POC outputs
• Final recommendation and approvals

This avoids losing context as people move roles, re-running the same conversations, and forcing vendors to re-educate new stakeholders. It also becomes your playbook when you revisit the platform landscape 5–7 years down the road.

A good FP&A/EPM evaluation is not:

• The flashiest demo
• The vendor with the nicest logo
• The longest feature checklist

It's a process where:

• Architecture, modeling engine, and data handling are front and center
• Your actual workflows drive the demos
• Internal capabilities and future needs are explicitly considered
• You test the path to the result, not just the polished end state
• Total cost and long-term fit are modeled, not guessed

If you run this A→Z process, it almost doesn't matter which vendor is shouting the loudest. You'll make a decision that you can defend to your board, your finance team can live with, your IT team can support, and your business can grow into.

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