Anaplan vs. Pigment: Feature, Pricing & Enterprise Readiness Comparison Guide 2026
The incumbent that has led its Gartner quadrant nine times, against the challenger that says more than half its new customers came from a legacy vendor. The question is whether modelling power or authoring speed decides your next five years.
The Short Answer
Anaplan is an enterprise connected planning platform built on Hyperblock, a patented in-memory calculation engine that combines spreadsheet-style cell flexibility with multidimensional OLAP scale. It plans finance, supply chain, sales and workforce on one model, serves more than 2,400 customers, and has been owned by Thoma Bravo since 2022.
Pigment is a business planning platform founded in 2019 with its own multidimensional engine and an AI layer that is central rather than added. It covers the same cross-functional ground and is most often bought by organisations that find enterprise modelling platforms too slow to change.
They are direct competitors at the top of the category, and the 2025 Gartner Magic Quadrant for Financial Planning Software places them in different quadrants — Anaplan a Leader for the ninth time, Pigment a Visionary for the second consecutive year. Neither publishes pricing. The decision usually comes down to modelling depth against the speed at which a model can be built and changed.
Every capability claim below is drawn from vendor documentation, vendor security pages, analyst reports or named third-party research, is dated, and is linked to its source at the point the claim is made rather than only in the list at the end. Where something is not published, the guide says so rather than guessing. Pricing that comes from procurement datasets rather than vendors is labelled as an estimate. Datarails publishes this guide and competes in the wider FP&A market; it is not one of the two products compared here, and appears only in one clearly labelled section at the end.
Why Finance Teams Compare Anaplan and Pigment
This is the clearest incumbent-versus-challenger comparison in enterprise planning, and the two companies describe the market in incompatible terms. Anaplan’s position is that planning at enterprise scale is genuinely hard, that Hyperblock solves it, and that nine consecutive Leader placements in Gartner’s Magic Quadrant reflect how few platforms can do it. Pigment’s position is that modelling power stopped being the constraint some time ago, and that the real constraint is how long it takes to build a model, change it, and get a non-finance stakeholder to use it.
Both claims can be true at once, which is why the comparison is harder than it looks. The useful question is not which platform is more capable in the abstract. It is which constraint is actually binding in your organisation — the size and complexity of the model, or the speed at which it can be authored and adapted.
The 2025 Gartner Magic Quadrant for Financial Planning Software, published 1 December 2025, evaluated 14 vendors and placed Anaplan in the Leaders quadrant alongside Oracle, OneStream, SAP and Workday. Pigment appears in Visionaries, with Planful, Board, Wolters Kluwer and Jedox. Gartner’s definitions matter here: Leaders are described as architected for enterprise-wide scale and high concurrency, while Visionary placement reflects completeness of vision ahead of current ability to execute at that scale.
Pigment’s own commercial numbers describe the same dynamic from the other side. In March 2026 it announced it was approaching $100 million in annual recurring revenue, having doubled for a third consecutive year, and stated that 56% of its new customers in 2025 migrated from a legacy planning vendor. Whatever you make of the framing, that is a market in active replacement rather than first-time purchase.
Where Enterprise Planning Evaluations Usually Go Wrong
Enterprise planning selections tend to be decided on a capability matrix and regretted on a maintenance calendar. The platform handles the model it was shown. Eighteen months later the business has reorganised, two entities have been acquired, and the question is no longer whether the engine can calculate it but whether anyone left in the team can safely change it.
The second failure is quieter and more common: the model gets built, it works, and then nobody outside finance ever opens it. Cross-functional planning only pays back if sales and HR actually own their inputs. If they are given a view-only dashboard and asked to email their numbers anyway, you have bought an expensive version of what you had.
- Who changes the model after go-live, and how long does a structural change take? Ask both vendors to make a real change to a demo model while you watch, not to describe the process.
- How many certified builders does the market have, and what do they cost? Modelling depth creates a dependency on scarce skills. Price that in.
- What does a non-finance contributor actually see? Have a sales or HR colleague sit in the demo and give an opinion.
- What does the renewal look like in year three? Ask for the uplift mechanism in writing, including any consumption or compute component.
None of these is answered by a feature table, and all four separate the two platforms on this page more reliably than any capability row.
What Is Anaplan?
Anaplan is a cloud platform for connected enterprise planning, founded in 2006 in Yorkshire, England, and now headquartered in Miami, Florida. It listed on the NYSE in 2018 and was taken private by Thoma Bravo in June 2022 in a deal that closed at $10.4 billion, renegotiated down from the $10.7 billion announced. It reports more than 2,400 customers worldwide.
The platform runs on Hyperblock, a patented in-memory calculation engine that combines spreadsheet-style cell-level flexibility with the scale of a multidimensional OLAP database, recalculating downstream impacts in real time across many concurrent users. A second engine, Polaris, addresses sparse large-scale models. Application areas span Anaplan for Finance, Supply Chain, Sales and Go-to-Market, and Workforce, with Merchandise Financial Planning for retail and Anaplan Data Orchestrator as the data management layer.
Anaplan’s AI portfolio is the most recently expanded part of the platform: PlanIQ and Optimizer for predictive and optimisation work, CoPlanner as a conversational assistant, CoModeler for natural-language model building, Forecaster, and a suite of role-based agents introduced in December 2025 alongside Agent Studio for building your own. The company acquired Fluence Technologies in 2024, adding financial consolidation.
What Is Pigment?
Pigment is a business planning and performance management platform founded in 2019 in Paris by Eléonore Crespo and Romain Niccoli. It is used for financial planning alongside sales, workforce and supply chain planning, with the stated aim of putting finance and operational teams on a single connected model.
Planning happens in Pigment’s own interface: users build dimensions, metrics, transaction lists and blocks in a multidimensional engine designed to keep large, sparse models performant, then publish boards and dashboards on top. The AI layer is central to current positioning — the Analyst Agent answers business questions and runs variance analysis, the Modeler Agent assists with building and adapting models, Predictions applies statistical and machine-learning forecasting, and a published MCP server lets external AI tools query Pigment data through a standard protocol.
Pigment raised a $145 million Series D led by ICONIQ Growth in April 2024 at a $1 billion valuation, has raised close to $400 million in total, and announced in March 2026 that it was approaching $100 million in ARR after doubling for a third consecutive year. Named customers include Unilever, Merck, Datadog, Uber, Anthropic and Siemens.
Anaplan vs. Pigment at a Glance
| Category | Anaplan | Pigment |
|---|---|---|
| Core category | Connected enterprise planning | Business planning and performance management |
| Founded / HQ | 2006 · Miami, Florida (founded in Yorkshire, England) | 2019 · Paris, France |
| Ownership | Thoma Bravo, take-private completed June 2022 at $10.4bn | Venture-backed; $1bn valuation at Series D, April 2024 |
| Calculation engine | Hyperblock in-memory engine, patented; Polaris for sparse models | Proprietary multidimensional engine built for sparse models |
| Customers | More than 2,400 | Not published; names Unilever, Merck, Datadog, Uber, Anthropic, Siemens |
| Planning scope | Finance, supply chain, sales and go-to-market, workforce, retail merchandise | Finance, sales, workforce, supply chain |
| Consolidation | Added through the Fluence Technologies acquisition in 2024 | Multi-entity modelling supported; positioned as planning, not a close suite |
| AI | PlanIQ, Optimizer, CoPlanner, CoModeler, Forecaster, role-based agents, Agent Studio | Analyst Agent, Modeler Agent, Predictions, Insights, Sequences, MCP server |
| 2025 Gartner MQ, Financial Planning Software | Leader, for the ninth time | Visionary, second consecutive year |
| Published pricing | No — quote-based | No — quote-based, no tier names published |
| Third-party contract estimates | Entry around $30,000–$50,000; averages reported near $200,000 (third-party estimates) | Median around $74,000 (Vendr, accessed September 2026) |
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Two rows carry most of the decision. The quadrant row records a genuine difference in how Gartner assesses enterprise-scale execution. The estimate row records that these platforms are not usually competing for the same budget — Anaplan’s reported averages sit well above Pigment’s median, though the customer mixes behind each figure differ and neither is a quote.
Anaplan vs. Pigment: Feature-by-Feature Comparison
Both platforms do cross-functional planning, so the rows below focus on where they diverge: engine architecture, model authoring, AI reach, consolidation and administration.
| Capability | Anaplan | Pigment |
|---|---|---|
| Multidimensional modelling engine | YesHyperblock, patented, plus Polaris | YesProprietary sparse engine |
| Real-time recalculation at high concurrency | YesThe platform’s defining characteristic | YesReal-time scenario comparison on the shared model |
| Budgeting and forecasting | YesAnaplan for Finance | YesNative budgeting applications |
| Scenario planning | YesMulti-dimensional scenario modelling | YesAlternate versions side by side on one model |
| Financial consolidation | YesVia the Fluence Technologies acquisition | PartialMulti-entity modelling, not a close suite |
| Supply chain planning | YesDemand, supply and S&OP applications | YesPublished use case |
| Sales and go-to-market planning | YesTerritory, quota and incentive compensation | YesA core published use case |
| Workforce planning | Yes | Yes |
| Retail merchandise planning | YesPurpose-built application | Not documented |
| Natural-language model building | YesCoModeler | YesModeler Agent |
| Conversational AI assistant | YesCoPlanner | YesAnalyst Agent |
| Build-your-own agents | YesAgent Studio | Not documentedAs a separate builder |
| Statistical / ML forecasting | YesPlanIQ and Forecaster | YesPredictions |
| MCP server for external AI tools | Not documented | YesPublished MCP server |
| Data orchestration layer | YesAnaplan Data Orchestrator | YesNative connectors to ERP, CRM, HRIS and warehouses |
| Excel connectivity | PartialAdd-in for data exchange; modelling stays in Anaplan | PartialOffice add-in pushes and pulls; modelling stays in Pigment |
| Google Sheets connector | Not documented | YesGoogle Workspace add-on |
| Guided experience for occasional users | Not documentedAs a named capability | YesSequences |
| SSO and provisioning | Yes | YesSAML 2.0 plus SCIM |
| Published pricing | No | No |
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Note that both platforms treat Excel the same way — as a connected endpoint rather than a planning interface. Teams for whom that is the deciding issue are comparing the wrong two products, and should look at Excel-native platforms instead.
Deep Feature Analysis: Anaplan vs. Pigment
Modelling Engine and Scale
Hyperblock is the platform’s claim to the category. It combines cell-level flexibility with multidimensional scale and recalculates downstream impacts in real time across many concurrent users. Polaris addresses sparse models where dimensionality is high and population is low. This is the deepest modelling capability in the comparison, and it is the reason enterprises with genuinely complex planning problems shortlist Anaplan first.
Pigment’s engine is built for sparse multidimensional models and is designed around keeping large models performant while remaining editable. The emphasis in its positioning is less on maximum theoretical scale and more on the model staying comprehensible and changeable as the business changes.
Engine benchmarks are the least useful part of this comparison, because both will handle a demo and neither will be tested properly until month six. What separates them in practice is what happens at the edge of the envelope. Bring your largest real model — the one with the dimension nobody wants to talk about — and ask both vendors to load it, not a representative sample. If your planning problem genuinely sits at the top of the market, Anaplan’s engine depth is not marketing. If it does not, you are paying for headroom you will never use.
Model Authoring and the Speed of Change
Models are built by certified model builders, and the licence structure reflects that with a distinct Model Builder tier. The flexibility that makes Hyperblock powerful also makes a model something that must be designed, and reviewers consistently note that the breadth of the platform carries a steeper learning curve than single-purpose tools. CoModeler is Anaplan’s answer: natural-language model building, introduced as part of a multi-year AI investment.
Authoring speed is Pigment’s central pitch. The Modeler Agent assists with building and adapting models from intent rather than specification, and the broader claim is that a finance team should be able to change its own model without a specialist. This is the capability the company has been investing in most visibly.
This is the decision underneath the decision, and it is a question about your organisation rather than about the software. If you have or can hire certified builders and your planning problem justifies them, model depth is an asset. If every change has to go through two people who are already fully committed, depth becomes a queue. Ask each vendor to make a structural change to a model while you watch — adding a dimension, not editing a number — and time it.
AI Architecture
The portfolio is wide: PlanIQ and Optimizer for prediction and optimisation, CoPlanner for conversational work, CoModeler for model building, Forecaster, role-based agents introduced in December 2025, and Agent Studio for building custom agents. It is backed by a multi-year AI roadmap reported at roughly $500 million. Several components are recent, and third-party reviews describe parts of the agent suite as early-stage.
Pigment positions AI as foundational rather than added, and its distinguishing architectural choice is openness: a published MCP server lets external AI tools query Pigment data through a standard protocol. Dresner Advisory Services ranked Pigment first for agentic AI in enterprise performance management.
Anaplan is building more AI surface area inside its own platform; Pigment is betting that finance data will be queried by tools the vendor did not build. Which matters depends on whether you intend to run your own AI toolchain. One third-party review notes that Anaplan’s AI outputs are tightly integrated into its models and harder to export — worth testing directly if portability matters to you. The question for both: what exactly can the agent see, and what stops it answering confidently from a partial dataset?
Consolidation and the Finance Close
Anaplan acquired Fluence Technologies in 2024, adding financial consolidation to a platform that had been planning-led. That makes it viable for groups that want planning and consolidation from one vendor, with the caveat that acquired capability takes time to integrate fully.
Pigment supports multi-entity modelling but does not position itself as a consolidation or close platform. Organisations with statutory consolidation requirements typically run a separate tool alongside it.
If statutory consolidation is in scope, this row narrows the shortlist immediately and may well bring OneStream or CCH Tagetik into the comparison instead. If it is not, Anaplan’s consolidation capability is scope you are not buying. Ask Anaplan specifically which Fluence capabilities are generally available today and which remain on the roadmap — a fair question for any acquirer.
Adoption Outside Finance
Connected planning across finance, supply chain, sales and workforce is the founding premise, and the application portfolio reflects it, including purpose-built retail merchandise planning. Breadth is a genuine differentiator at enterprise scale, though the same breadth is what reviewers cite when describing the learning curve.
Pigment’s answer to the same problem is Sequences — a guided experience so an occasional or non-expert user can contribute without learning the modelling interface. The design assumption is that cross-functional planning fails on contributor adoption rather than on model capability.
Cross-functional planning only pays back if other functions actually participate. Both platforms can model sales and workforce; the difference is what a regional sales director sees when they open it in budget season. Put a non-finance colleague in both demos and listen to which one they complain about less — that reaction predicts year-two adoption better than any capability row.
Vendor Trajectory and Ownership
Owned by Thoma Bravo since June 2022, following a public listing in 2018. Private-equity ownership typically brings a focus on operating leverage, and some third-party analysis of the category has linked that to pricing pressure at renewal. Against that, the company has committed to a multi-year AI roadmap reported at roughly $500 million.
Venture-backed, with close to $400 million raised and a $1 billion valuation at its April 2024 Series D. It reported approaching $100 million ARR in March 2026 after doubling for a third consecutive year, with 74% growth in its enterprise customer base and 57% of new revenue coming from enterprise customers.
For a platform you will run for five years, the vendor’s stage matters as much as the roadmap. A private-equity-owned incumbent offers stability and a known quantity, with renewal economics worth negotiating carefully up front. A fast-growing challenger offers roadmap pace, with the ordinary risks of scale — account team turnover, support stretched by growth. Ask both for the renewal uplift mechanism in writing and for a reference customer who has been through one.
Anaplan vs. Pigment Pricing
Neither vendor publishes list pricing. Both quote per organisation and both sit at the top of the FP&A market. Figures circulating publicly are third-party estimates from procurement datasets and user communities, and they vary widely — treat them as negotiating context, not budget.
| Pricing factor | Anaplan | Pigment |
|---|---|---|
| Public pricing | Not disclosed | Not disclosed |
| Pricing model | Annual subscription; base platform fee plus licensed applications, with user tiers including Model Builder; workspace and model size are factors | Annual subscription; platform fee plus seats and licensed use cases |
| Third-party estimates | Entry reported at $30,000–$50,000; averages reported near $200,000; complex enterprise implementations reported far higher | Median around $74,000 (Vendr, accessed September 2026) |
| Cost drivers | User count and licence type, applications switched on, workspace and model size, data volume | Seats, licensed use cases, scope of functions covered |
| Implementation | Priced separately; professional implementation generally required, often partner-delivered | Priced separately; partners include Deloitte, with an alliance across the US, UK, France and Belgium |
| Free trial | No | No; demo and proof-of-concept instead |
| Contract | Annual, custom-quoted; multi-year common | Annual, custom-quoted |
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What Each Vendor Claims About Return on Investment
Pigment commissioned Forrester Consulting to produce a Total Economic Impact study, published December 2023, reporting a 306% ROI over three years for a composite organisation with payback in under six months — benefits of $8.13 million against costs of $2.00 million. Read the methodology before the headline: the composite is built from interviews with four Pigment customers, and Forrester states in the study that it is commissioned and not meant to be used as a competitive analysis. A commissioned TEI is a framework for building your own business case, not a result you should expect to repeat.
Three cost questions matter more than the licence line for both platforms: what implementation actually costs in year one, what sits behind a higher tier or an additional application, and what the uplift mechanism is at renewal — including any consumption or compute component. Ask for all three in writing before comparing totals.
Enterprise Readiness: Anaplan vs. Pigment
Only attestations each vendor publishes or documents are listed. Request current reports directly, since attestation periods lapse.
| Control | Anaplan | Pigment |
|---|---|---|
| SOC 1 | YesType 2 | YesType II |
| SOC 2 | YesType 2 | YesType II |
| ISO 27001 | Yes | YesCertified, announced 29 April 2026 |
| ISO 27017 (cloud security) | Yes | Not documented |
| ISO 27018 (cloud privacy) | Yes | Not documented |
| ISO 27701 (privacy management) | Yes | Not documented |
| CSA STAR | YesLevel 1 | YesLevel 1 |
| Cyber Essentials | Yes | Not documented |
| Data Privacy Framework | YesEU-US and Swiss-US participant | Not documented |
| GDPR | Yes | YesAlongside CCPA and CPRA |
| Self-service trust centre | Not documentedAs self-service | YesReports, ISO certificate and penetration-test summary |
| SSO / SCIM / MFA | Yes | YesSAML 2.0, SCIM, MFA, domain allowlisting |
| Access control granularity | Yes | YesRBAC plus attribute-based data access rights |
| Multi-entity / multi-currency | Yes | Yes |
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Anaplan carries the broader certification set, which matters to procurement functions that score certifications as a checklist — ISO 27017, 27018 and 27701, Cyber Essentials and Data Privacy Framework participation are all documented. Pigment’s advantage is disclosure style rather than posture: a security reviewer can pull the SOC reports, the ISO certificate and a penetration-test summary from its trust centre without a sales conversation, which shortens vendor review. If your security team is the critical path, raise that difference early.
Commercial Momentum
Both companies are at different points in their lifecycle, and the public numbers describe that clearly.
Anaplan reports more than 2,400 customers, including a substantial share of the largest global enterprises, and has held a Leader position in Gartner’s Magic Quadrant for Financial Planning Software nine times. As a private company under Thoma Bravo it does not publish revenue. Its most visible recent commitment is a multi-year AI roadmap reported at approximately $500 million.
Pigment announced in March 2026 that it was approaching $100 million in ARR, having doubled for a third consecutive year, with a 74% increase in its enterprise customer base and 57% of new revenue coming from enterprise customers. It also stated that 56% of its new customers in 2025 migrated from a legacy planning vendor. These are company-reported figures rather than audited accounts, which is normal for a private company and worth stating plainly.
The asymmetry is the point. Anaplan is defending an installed base measured in thousands of enterprises; Pigment is growing from a much smaller base at a rate that would be unremarkable for a startup and is notable at approaching $100 million. Neither fact tells you which platform fits your model.
Implementation and Time to Value
Neither vendor publishes standard implementation timelines, and this guide will not invent one. Forrester’s Total Economic Impact study of Anaplan declined to give a point estimate at all, describing implementation as anywhere between twelve weeks and two years. That is not evasion — it reflects how much the answer depends on scope.
| Dimension | Anaplan | Pigment |
|---|---|---|
| Delivery model | Professional implementation generally required; large partner ecosystem | Pigment services or partners, including a Deloitte alliance |
| Who builds the model | Certified model builders, often external initially | Often the finance team itself, assisted by the Modeler Agent |
| Ongoing ownership | Usually requires certified builder capability in-house or on retainer | Concentrated in a smaller group of model owners |
| Contributor change management | Significant — a new interface for every function involved | Significant, mitigated by Sequences for occasional users |
| Switching cost once embedded | High; third-party analysis describes migration as costly and disruptive | Not independently documented |
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Five questions produce a better estimate than any published range: how many functions are in phase one; who writes the model, the vendor or your team; what the certified-builder market looks like for your region; whether consolidation is in scope on day one; and who owns changes in month eighteen. Ask both vendors for a reference customer of similar size and complexity, and ask that customer how long phase one actually took against the original plan.
Anaplan vs. Pigment Use Cases
| Use case | Anaplan | Pigment | Key difference |
|---|---|---|---|
| Very large, high-concurrency models | Strong | Good | Hyperblock is the deepest engine in the comparison |
| Frequent structural model change | Good, with builder capability | Strong | Authoring speed is Pigment’s central pitch |
| Cross-functional planning | Strong — finance, supply chain, sales, workforce, retail | Strong — finance, sales, workforce, supply chain | Anaplan’s application portfolio is broader; Pigment’s contributor experience is more guided |
| Statutory consolidation | Supported via Fluence | Not positioned for it | A decisive scope difference if consolidation is in scope |
| Retail merchandise planning | Purpose-built application | Not documented | Relevant only to retail |
| Adoption by non-finance contributors | Good | Strong — Sequences | What a regional manager sees in budget season |
| Connecting external AI tools | Not documented | Published MCP server | Relevant if you run your own AI toolchain |
| Procurement checklists scoring certifications | Strong — broadest certification set here | Good — core attestations plus self-service evidence | Breadth against ease of access |
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When Each Platform May Be the Better Fit
When Anaplan May Be a Better Fit
- Your planning problem is genuinely at enterprise scale. Hyperblock’s real-time recalculation across many concurrent users is the deepest modelling capability in this comparison.
- You plan across many functions including supply chain and retail. The application portfolio is broader, with purpose-built merchandise financial planning.
- Statutory consolidation is in scope. Fluence added it; Pigment does not position for it.
- You have or can hire certified model builders. Depth pays back only with the capability to use it.
- Procurement scores certifications as a checklist. ISO 27017, 27018, 27701, Cyber Essentials and Data Privacy Framework participation are all documented.
- A nine-time Leader placement carries weight in your process. Formal selection committees often require it.
When Pigment May Be a Better Fit
- The binding constraint is speed of change, not model size. If your model is months behind the business, authoring speed is the thing to buy.
- Non-finance stakeholders must contribute directly. Sequences exists specifically for occasional users who will never learn a modelling interface.
- AI reach matters to your architecture. A published MCP server makes Pigment easier to connect to a wider AI toolchain.
- Your security review is the bottleneck. A self-service trust centre with SOC reports, the ISO certificate and a penetration-test summary shortens that cycle.
- Your budget sits below enterprise-incumbent levels. Third-party estimates put Pigment’s median materially below Anaplan’s reported averages.
- You are replacing a legacy planning platform. Pigment states this is where most of its new business comes from, so the migration path is well travelled.
Where Both Platforms Have Limitations
Shared Limitations
- No published pricing from either vendor. Both require a full sales cycle before a comparable number exists, and third-party estimates disagree widely.
- Neither offers a self-serve trial. You cannot test either against your own data without engaging sales.
- Both are implementation projects, not switch-ons. Model design, data integration and contributor onboarding all take real time.
- Neither is Excel-native. Both connect to Excel; neither plans in it. Teams for whom that is decisive are comparing the wrong pair.
- AI claims on both sides are moving faster than they can be verified. Reproduce anything you are shown on your own data before it counts.
- Neither replaces the ERP or fixes the quality of what upstream systems send them.
Anaplan-Specific Considerations
- Modelling depth creates a dependency on certified builders; reviewers consistently cite a steeper learning curve than single-purpose tools, and losing key builders is a real operational risk.
- Switching cost once embedded is high, with third-party analysis describing migration as costly and disruptive.
- Several AI components, including CoModeler and the role-based agents, are recent, and third-party reviews describe parts of the suite as early-stage.
- Third-party reviews note that AI outputs are tightly integrated into Anaplan models and harder to export or use elsewhere.
- Consolidation arrived through acquisition in 2024, so it is worth asking which Fluence capabilities are generally available today versus roadmap.
- Private-equity ownership since 2022 means renewal economics are worth negotiating carefully up front.
Pigment-Specific Considerations
- Gartner placed Pigment in Visionaries rather than Leaders in the 2025 Magic Quadrant, which reflects completeness of vision ahead of demonstrated enterprise-scale execution. Formal selection processes may raise it.
- Statutory consolidation and close are not product areas, so a separate tool is still required.
- Retail merchandise planning and several of Anaplan’s specialised applications have no documented equivalent.
- Several certifications Anaplan documents — ISO 27017, 27018, 27701, Cyber Essentials, Data Privacy Framework — are not published by Pigment.
- The company is scaling very quickly, which brings the ordinary risks of growth: account team turnover and support capacity stretched by new business.
Where Datarails Fits
Datarails publishes this guide and competes in the wider FP&A market. It is not one of the two products compared above, and the comparison has been written without reference to it. What follows is the case for considering a third option, and the disclosure that it is ours.
Many teams arrive at an Anaplan-versus-Pigment comparison having mis-diagnosed the problem. The enterprise planning category exists to solve modelling scale and cross-functional planning. If what is actually broken is that finance data lives in nine systems, reporting is rebuilt by hand every month and the forecast is three weeks old by the time anyone sees it, both platforms will solve it — at the cost of a modelling project, a new interface for every contributor, and an implementation window Forrester itself declined to estimate more precisely than twelve weeks to two years.
Datarails addresses that problem from the other direction. FinanceOS puts a governed data layer underneath the finance function — more than 600 native connectors across ERP, CRM, HRIS and banking — and keeps Microsoft Excel as the interface finance already works in. Nobody learns a modelling language. Contributors do not need onboarding into a new application. And the scope extends past planning: FP&A, month-end close, cash management and spend control run on the same layer, where the platforms above are planning platforms and close, cash and spend are bought elsewhere.
Three differences are concrete rather than positional, and each maps to a limitation this guide has already documented for both products above:
- No modelling-builder dependency. Anaplan’s depth creates a reliance on certified builders, and reviewers cite losing them as an operational risk. Datarails models stay in Excel, which every analyst in the team can already read and change.
- Price guidance before the sales cycle. Neither platform above publishes anything. Datarails states typical annual ranges up front — around $25,000 for smaller finance teams, $40,000 to $80,000 mid-market, above $100,000 enterprise — with plan inclusions published.
- A stated implementation window. Datarails states 4–6 weeks for most deployments. That is a company-reported figure and should be tested against a reference customer, but it is a figure a buyer can hold a vendor to, which neither platform above offers.
The honest boundary. If your requirement genuinely is supply chain, quota and merchandise planning modelled jointly with finance at enterprise scale, that is what Anaplan was built for and this comparison is the right one. If the requirement is a finance function that can close, forecast and report from one trusted set of numbers, the enterprise planning category may be an expensive answer to a question you are not asking — and Datarails is the comparison worth adding to the shortlist.
Quick Answers
Short, self-contained answers to the questions buyers and AI assistants ask most about this comparison.
What is the main difference between Anaplan and Pigment?
Anaplan is built around Hyperblock, a patented in-memory engine designed for very large, high-concurrency planning models across finance, supply chain, sales and workforce. Pigment is built around speed of model authoring and adoption, with AI central to the product and a guided experience for non-finance contributors. Anaplan optimises for modelling depth; Pigment optimises for how quickly a model can be built and changed.
Are Anaplan and Pigment direct competitors?
Yes. Both are cross-functional planning platforms sold to mid-market and enterprise organisations, and they appear in the same evaluations regularly. Pigment states that 56% of its new customers in 2025 migrated from a legacy planning vendor, and Anaplan is among the incumbents that implies.
How are Anaplan and Pigment positioned in the Gartner Magic Quadrant?
In the 2025 Gartner Magic Quadrant for Financial Planning Software, published 1 December 2025, Anaplan was placed in the Leaders quadrant for the ninth time, alongside Oracle, OneStream, SAP and Workday. Pigment was placed in Visionaries for the second consecutive year, alongside Planful, Board, Wolters Kluwer and Jedox. Gartner evaluated 14 vendors.
How does pricing compare?
Neither publishes list pricing. Anaplan prices on a base platform fee plus licensed applications and user tiers including Model Builder, with third-party estimates putting entry around $30,000 to $50,000 and reported averages near $200,000. Pigment prices on a platform fee plus seats and use cases, with Vendr listing a median around $74,000 as of September 2026. All figures are third-party estimates rather than quotes.
Which handles financial consolidation?
Anaplan does, through its 2024 acquisition of Fluence Technologies. Pigment supports multi-entity modelling but does not position itself as a consolidation or close platform, so organisations with statutory consolidation requirements typically run a separate tool. If consolidation leads the requirement, OneStream and CCH Tagetik also belong on the shortlist.
Which is faster to implement?
Neither publishes timelines, and Forrester’s study of Anaplan declined to give a point estimate, describing implementation as anywhere between twelve weeks and two years. Pigment positions authoring speed as a core differentiator and assists model building with its Modeler Agent. Anaplan implementations typically involve certified model builders. The deciding variables are scope, number of functions and model complexity.
Which has stronger security credentials?
Anaplan documents the broader set: SOC 1 and SOC 2 Type 2, ISO 27001, 27017, 27018 and 27701, CSA STAR Level 1, Cyber Essentials and Data Privacy Framework participation. Pigment holds SOC 1 Type II, SOC 2 Type II, ISO 27001 certified in April 2026, and CSA STAR Level 1, published through a self-service trust centre that also carries a penetration-test summary. Anaplan has more certifications; Pigment makes evidence easier to obtain.
Does either work with Excel?
Both connect to Excel; neither plans in it. Each offers an add-in for exchanging data between the spreadsheet and the platform, with the model remaining in the platform. Pigment additionally publishes a Google Sheets connector. If Excel must remain the planning interface, this is the wrong pair to compare: Datarails is the closest alternative, keeping Excel as the interface over a governed data layer, with Vena and Cube the other Excel-native options.
What are the main alternatives to Anaplan and Pigment?
The alternatives divide by what you are actually solving. If the requirement is enterprise modelling scale, OneStream, Oracle EPM, SAP and Workday Adaptive Planning are the other Gartner Leaders; Board, Jedox, Planful and CCH Tagetik sit with Pigment in Visionaries. If the requirement is a finance function working from one trusted set of numbers without leaving Excel, Datarails is the closest alternative to both — Excel as the interface over a governed data layer with 600+ connectors, covering FP&A, close, cash and spend — with Vena and Cube as the other Excel-native options.
Frequently Asked Questions
Is Pigment capable of replacing Anaplan at enterprise scale?
Pigment states that 56% of its new customers in 2025 migrated from a legacy planning vendor, and names enterprises including Unilever, Merck, Siemens and Uber, so replacements clearly happen. Gartner’s 2025 placement of Pigment in Visionaries rather than Leaders reflects completeness of vision ahead of demonstrated enterprise-scale execution. The honest test is your own largest model: load it into both and see what happens.
Does Thoma Bravo’s ownership of Anaplan matter to a buyer?
It matters at renewal more than at purchase. Private-equity ownership typically brings a focus on operating leverage, and some third-party analysis of the category links that to pricing pressure for existing customers. Against that, Anaplan has committed to a multi-year AI roadmap reported at roughly $500 million. Ask for the renewal uplift mechanism in writing and speak to a reference customer who has been through one.
How many people do we need to run each platform?
Anaplan separates licences by role, including a distinct Model Builder tier, which reflects an expectation of dedicated modelling capability. Pigment positions authoring as something the finance team can do itself, assisted by the Modeler Agent. Neither vendor publishes a required headcount, so ask each for a reference customer of your size and ask how many people actually maintain the model.
Which is better for supply chain planning?
Anaplan has the deeper portfolio, with dedicated demand, supply and sales-and-operations planning applications built on Hyperblock, plus purpose-built merchandise financial planning for retail. Pigment publishes supply chain planning as a use case on its platform. If supply chain is the primary driver rather than an adjacent requirement, Anaplan’s specialisation is material.
Can either platform’s AI be used with our own tools?
Pigment publishes an MCP server, which lets external AI tools query Pigment data through a standard protocol. Anaplan has not publicly documented an equivalent, and third-party reviews note that its AI outputs are tightly integrated into Anaplan models and harder to export. If you intend to run your own AI toolchain over planning data, test portability directly rather than relying on either vendor’s positioning.
How should we run a fair evaluation of the two?
Use your largest real model, not a representative sample. Give both vendors the same source extract and the same model requirement, then ask each to make a structural change — adding a dimension, not editing a number — while you watch, and time it. Put a non-finance colleague in both demos. Finally, ask each for a reference customer of similar size who has been through at least one renewal.
What happens if we outgrow Pigment or want to leave Anaplan?
Switching enterprise planning platforms is expensive in both directions, and third-party analysis describes migrating off Anaplan as costly and disruptive given the modelling investment involved. Ask both vendors during evaluation about data and model export formats. The answer is far more revealing at the start of a contract than at the end of one.
Sources
All sources accessed and verified 29 September 2026. Vendor claims are attributed to the vendor; third-party estimates are labelled.
- Vendor — Anaplan. Announcement of Leader placement in the 2025 Gartner Magic Quadrant for Financial Planning Software, 4 December 2025, including the full quadrant composition and the note that Gartner evaluated 14 vendors. anaplan.com
- Third party — ERP Research. Anaplan profile, updated August 2026: Hyperblock in-memory engine, quote-based pricing by workspace and model size, users and applications licensed, and certification list covering SOC 1 and SOC 2 Type 2, ISO 27001, 27017, 27018 and 27701, CSA STAR Level 1, Cyber Essentials and Data Privacy Framework participation. erpresearch.com
- Third party — Wikipedia. Anaplan corporate history: founded 2006, NYSE listing 2018, Thoma Bravo acquisition announced at $10.7bn and renegotiated to $10.4bn, completed June 2022; Hyperblock patent. en.wikipedia.org
- Third party — CFO Shortlist. Anaplan review, 2026: Hyperblock scale characteristics, AI portfolio including Forecaster, CoModeler and role-based agents introduced December 2025, reported AI investment, migration cost and AI output portability. cfoshortlist.com
- Vendor — Pigment. Press release, 4 March 2026: approaching $100m ARR, doubled ARR for a third consecutive year, 56% of 2025 new customers migrated from a legacy vendor, 57% of new revenue from enterprise customers, 74% enterprise customer growth. prnewswire.com
- Third party — Fortune. Report of 4 March 2026 on Pigment’s ARR milestone, enterprise growth, named customers and total funding. fortune.com
- Vendor — Pigment. Security page and Trust Center: SOC 1 Type II, SOC 2 Type II, ISO 27001 announced 29 April 2026, CSA STAR Level 1, GDPR and CCPA/CPRA, SAML 2.0, SCIM, MFA, RBAC and attribute-based data access rights, penetration-test summary. Pigment, “Security” (pigment.com) and Trust Center (trust.pigment.com), accessed 29 September 2026.
- Vendor — Pigment. 2025 Gartner Magic Quadrant Visionary placement, and product detail covering the Analyst Agent, Modeler Agent, Predictions, Insights, Sequences and the published MCP server. Pigment (pigment.com), accessed 29 September 2026.
- Third party — Forrester Consulting. The Total Economic Impact™ Of Pigment, a commissioned study, December 2023: 306% ROI over three years, $8.13m benefits against $2.00m costs, payback under six months, composite built from four customer interviews, and Forrester’s statement that the study is not meant to be used as a competitive analysis. tei.forrester.com
- Third party — Vendr. Procurement marketplace profile for Pigment: median annual contract value from observed transactions, accessed September 2026. vendr.com
- Third party — Deloitte. Deloitte and Pigment alliance across the US, UK, France and Belgium. deloitte.com
Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organisation and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. GARTNER is a registered trademark and service mark and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates in the US and internationally, and are used herein with permission. All rights reserved. Reference: Gartner, Magic Quadrant for Financial Planning Software, Regina Crowder, Sid Sahoo, Mike Lashinsky, 1 December 2025.
Product names, logos and trademarks referenced in this guide are the property of their respective owners. Datarails is not affiliated with, endorsed by or sponsored by Anaplan or Pigment. Capabilities, pricing and certifications change; verify current details with each vendor before making a purchasing decision.