Review of Anaplan, Cloud-Native Planning Software Vendor

By Léon Levinas-Ménard
Last updated: September, 2025

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Anaplan is a cloud-native, multi-tenant platform for building and operating multi-dimensional planning models across finance, sales, supply and workforce. Models are executed in memory by the Hyperblock® engines—Classic for dense datasets and Polaris™ for sparse, high-dimensional ones—while optional components add linear/mixed-integer optimization and time-series forecasting. Data flows in via REST APIs, a Java CLI (Anaplan Connect), and in-tenant no-code pipelines (CloudWorks/Data Orchestrator); changes are governed through Application Lifecycle Management (ALM) with tenant-level security controls. Incorporated in the late 2000s after being founded in the UK in 2006, Anaplan went public in 2018 and was taken private by Thoma Bravo in 2022; subsequent tuck-ins extended analytics (Mintigo), packaged applications (Vuealta apps), and financial close/consolidation (Fluence). Engineering signals point to a microservices stack (Java/Kotlin/Rust/Python, React) deployed to Kubernetes on public cloud. Delivery follows “The Anaplan Way,” an iterative model-builder-centric rollout approach.

Executive overview

Anaplan delivers a modeling environment (lists, line items, modules, formulas) executed by in-memory engines that recalculate only impacted dependency chains; Classic targets dense cubes, while Polaris is natively sparse for high-dimensional models123. Advanced compute is additive: an embedded LP/MIP Optimizer (Gurobi-backed) callable as an action within models (Classic only), and PlanIQ to orchestrate forecasting via Amazon Forecast and native algorithms, writing results back to modules45678. Integration and orchestration are provided through REST/ALM APIs, Anaplan Connect (Java CLI), and CloudWorks/Data Orchestrator for no-code pipelines91011. Governance includes ALM (revision tags, production lists, page-level ALM) and enterprise security (SSO/SAML, OAuth clients, IP allow lists, certificate management)121314. Corporate milestones include the 2018 IPO and the 2022 Thoma Bravo take-private; M&A has been selective (Vue Analytics 2013, Mintigo 2019, Vuealta applications 2022, Fluence 2024)151617181920212223242526.

Anaplan vs Lokad

Scope & framing. Anaplan is a general-purpose planning platform spanning finance, sales, supply, and workforce; it equips model builders to assemble planning applications and optionally bolt on optimization/forecasting inside the same tenant12748. Lokad is a supply-chain-specialized platform focused on probabilistic forecasting and decision optimization delivered through a domain-specific language (Envision) that produces ROI-ranked action lists for replenishment, allocation, scheduling, and pricing282930.

Forecasting. Anaplan’s PlanIQ integrates Amazon Forecast and vendor-native algorithms; forecasting is orchestrated as a service and results are fed back into modules78. Lokad’s forecasting is probabilistic by design (full demand distributions, quantile grids) and has been validated publicly (e.g., strong SKU-level accuracy in the M5 competition), feeding directly into downstream optimization29.

Optimization. Anaplan exposes LP/MIP via an embedded Gurobi solver, packaged as an “Optimizer” action; as of public docs, Optimizer is not available on Polaris, creating a trade-off for sparse models that also need MIP45. Lokad uses uncertainty-aware optimization (e.g., stochastic/discrete search, differentiable programming) to optimize economic objectives under distributions, without restricting users to classical LP/MIP formulations2930.

Architecture & transparency. Anaplan provides a low-code modeling layer with ALM, tenant security, and no-code orchestration; internals (engine specifics, solver APIs) are abstracted, with community guidance on performance patterns21112. Lokad exposes a white-box DSL (Envision) where every transformation and decision rule is explicit and versioned; the platform is engineered around an event-sourced store and a distributed VM for Envision execution30.

Deliverable. Anaplan typically delivers a governed, collaborative planning application (e.g., FP&A, S&OP, territory planning) whose outputs depend on how the customer configures models, formulas, and actions127. Lokad typically delivers ready-to-execute, financially optimized decision lists (e.g., purchase orders, transfers) prioritized by expected ROI under uncertainty2930.

Corporate history & financing

Founded in 2006 in Yorkshire, UK, by Michael Gould, Guy Haddleton, and Sue Haddleton; U.S. scale-up and Delaware reincorporation preceded the 2018 IPO15. Venture rounds included Series B ($11.4M, 2012), Series C ($33M, 2013), Series D ($100M, 2014), and Series E ($90M, 2016)31323334. Anaplan listed on NYSE in Oct 2018; Thoma Bravo announced a take-private in Mar 2022, amended to $63.75/share, and closed Jun 22, 2022 (~$10.4B EV)15161718.

M&A ledger (acquirer)

  • Vue Analytics (UK/Ireland reseller), Feb 19, 20131920.
  • Mintigo (predictive marketing/sales analytics), announced Aug 27, 2019; closed Oct 3, 2019 (~$36.2M)2221.
  • Vuealta Applications Division, Dec 18, 202223.
  • Fluence Technologies (financial close, consolidation & disclosure), agreement Apr 26, 2024; closed May 9, 2024242526.

Platform architecture & engines

Modeling & execution. Models are composed of lists (dimensions), line items (measures/formulas), and modules (tables). The Hyperblock engines execute dependency DAGs and recalc only impacted blocks; functions like RANK are single-threaded; performance guidance (Planual) targets block counts and summaries12. Classic favors dense storage; Polaris introduces native sparsity to scale high-dimensional, sparse models (GA by 2023 per Statement of Direction)3. Future calc innovation is said to focus on Polaris3.

Optimization & forecasting

Optimizer. Exposes LP/MIP through an action that compiles decision variables/constraints/objective from model data; the embedded solver is Gurobi (per vendor whitepapers/community), and Optimizer is not available on Polaris456. Solver logs and gap/timeout handling are surfaced in execution threads and imports6.

PlanIQ. Orchestrates time-series training/inference using Amazon Forecast (e.g., DeepAR+, ARIMA/ETS) and Anaplan-native algorithms (e.g., MVLR), returning forecasts to modules; supports ad-hoc runs from UX pages78.

Integration & governance

APIs & pipelines. REST/ALM APIs, Anaplan Connect (Java CLI), and CloudWorks/Data Orchestrator deliver scripted and no-code pipelines (connections, transforms, scheduling) inside the tenant91011.

ALM & security. Revision tags, production lists, and page-level ALM promote structures from dev/test to prod; enterprise controls include SSO/SAML, OAuth 2.0 clients, IP allow lists, and certificate management; security briefs document controls and architecture121413.

Technology stack signals (roles & artifacts)

Job posts indicate Java/Kotlin/Rust/Python services, React front-end, Kubernetes/Docker, AWS/GCP, and CI/CD-owned platform/IAM; AI-enablement roles mention “operationalizing models” and integrations with data lakes/event stores353637.

Delivery methodology & timelines

The Anaplan Way prescribes iterative, model-builder-centric delivery; ALM governs promotion; vendor case stories claim rapid core builds or cycle-time reductions (treat as anecdotes, not SLAs)38123915.

Discrepancies & gray areas (as of public docs)

  • Founding year. Some third-party writeups cite 2008; multiple primary/secondary sources record 2006 (UK founding) with later U.S. incorporation15.
  • Optimizer on Polaris. Public docs state not supported; workarounds require Classic engine for MIP steps4.
  • “AI” breadth. Beyond PlanIQ’s time-series scope and job-post language, there is no detailed, reproducible public documentation of generative-AI-style features in core calc/UX as of cited sources836.

Skeptical state-of-the-art assessment

  • Engine & modeling. Mature in-memory dependency execution with a credible sparsity design in Polaris; absence of independent benchmarks means “best-in-class” claims remain unproven publicly13.
  • Optimization. Industrial-grade via Gurobi; packaging as an action is pragmatic, but Classic-only support limits sparse high-dimensional MIP use in Polaris-first models45.
  • Forecasting. Sensible leverage of Amazon Forecast plus vendor-native models; integration-first rather than proprietary deep-learning breakthroughs78.
  • Integration & governance. REST/CLI/no-code orchestration and ALM/security are comprehensive and standard for enterprise SaaS91113.

Conclusion

Anaplan is best characterized as a governed, programmable planning platform: in-memory calc engines (Classic/Polaris), optional LP/MIP and time-series capabilities, and robust ALM/security around a low-code modeling experience. The technical choices (Gurobi for MIP, Amazon Forecast integration, Kubernetes microservices) are industrial and credible. Claims of broader “AI” beyond forecasting are not evidenced by public, reproducible documentation. For buyers: validate Optimizer requirements against the Polaris limitation; pilot forecast accuracy/latency with PlanIQ on your series; and test data orchestration and ALM against your SDLC/compliance. Compared with Lokad, which centers on probabilistic, decision-centric optimization in a white-box DSL for supply chain, Anaplan’s strength is breadth and governance across enterprise planning; its supply-chain efficacy will reflect the specificity and rigor of the models you build on top.

Sources

  1. Anapedia — Calculation engines (Classic & Polaris) overview — Jun 2, 2025 ↩︎ ↩︎ ↩︎ ↩︎ ↩︎

  2. Community — Inside the Hyperblock (best practice) — 2022–2025 ↩︎ ↩︎ ↩︎

  3. Community — Statement of Direction for calculation engines (Polaris GA & focus) — 2025 ↩︎ ↩︎ ↩︎ ↩︎

  4. Anapedia — Optimizer (scope; not available on Polaris) — Mar 19, 2025 ↩︎ ↩︎ ↩︎ ↩︎ ↩︎ ↩︎

  5. Anaplan whitepaper — Inventory optimization (Gurobi reference) — Aug 2018 ↩︎ ↩︎ ↩︎ ↩︎

  6. Community — Start here: Anaplan Optimizer — n.d ↩︎ ↩︎ ↩︎

  7. Anaplan News — PlanIQ announcement — Sep 15, 2020 ↩︎ ↩︎ ↩︎ ↩︎

  8. Anapedia — PlanIQ overview (native algorithms, AWS Forecast) — 2022 ↩︎ ↩︎ ↩︎ ↩︎ ↩︎ ↩︎

  9. Anapedia — Application Lifecycle Management (ALM) API — n.d ↩︎ ↩︎ ↩︎

  10. Anapedia — Anaplan Connect — n.d ↩︎ ↩︎

  11. Anapedia — Anaplan Data Orchestrator (CloudWorks) — Oct 2, 2024 ↩︎ ↩︎ ↩︎ ↩︎

  12. Anapedia — ALM overview & stages — Apr 2025 ↩︎ ↩︎ ↩︎ ↩︎

  13. Anaplan Security Overview — Solution brief (PDF) — 2024 ↩︎ ↩︎ ↩︎

  14. Anapedia — Security & tenant administration — 2024–2025 ↩︎ ↩︎

  15. SEC S-1/A (Anaplan) — Oct 5, 2018 ↩︎ ↩︎ ↩︎ ↩︎ ↩︎

  16. Anaplan News — Thoma Bravo completes acquisition — Jun 22, 2022 ↩︎ ↩︎

  17. Thoma Bravo press release — completes acquisition of Anaplan — Jun 22, 2022 ↩︎ ↩︎

  18. Axios — Thoma Bravo’s big tech repricing: Anaplan — Jun 22, 2022 ↩︎ ↩︎

  19. TechCrunch — Anaplan snaps up Vue Analytics — Feb 19, 2013 ↩︎ ↩︎

  20. PEHub — Vue Analytics acquisition — Feb 19, 2013 ↩︎ ↩︎

  21. MarketScreener — Mintigo acquisition completed (~$36.2M) — Oct 3, 2019 ↩︎ ↩︎

  22. Forrester Blog — doubles down on predictive with Mintigo — Aug 28, 2019 ↩︎ ↩︎

  23. Anaplan News — acquires applications division from Vuealta — Dec 18, 2022 ↩︎ ↩︎

  24. Anaplan News — agreement to acquire Fluence Technologies — Apr 26, 2024 ↩︎ ↩︎

  25. Thoma Bravo — Fluence acquisition announcement — Apr 26, 2024 ↩︎ ↩︎

  26. Gowling WLG — cross-border acquisition of Fluence completed — May 9, 2024 ↩︎ ↩︎

  27. Anaplan Platform Overview — Solution brief (PDF) — Apr 2025 ↩︎ ↩︎

  28. Lokad — About / Company & approach — retrieved 2025 ↩︎

  29. Lokad — Technology & probabilistic forecasting / optimization — retrieved 2025 ↩︎ ↩︎ ↩︎ ↩︎

  30. Lokad — Envision DSL (platform & architecture) — retrieved 2025 ↩︎ ↩︎ ↩︎ ↩︎

  31. PRNewswire — Series B $11.4M — Jan 19, 2012 ↩︎

  32. TechCrunch — Series C $33M — Mar 5, 2013 ↩︎

  33. Yahoo Finance — Series D $100M — May 13, 2014 ↩︎

  34. BusinessWire — Series E $90M — Jan 14, 2016 ↩︎

  35. Greenhouse — Senior Software Engineer (Java/Kotlin/Rust/K8s) — 2025 ↩︎

  36. Greenhouse — Platform & AI Enablement (React/Java/Python; data lakes/event stores) — 2025 ↩︎ ↩︎

  37. Greenhouse — IAM Engineer (AWS/GCP; Kubernetes; CI/CD) — 2025 ↩︎

  38. The Anaplan Way (methodology guide, PDF) — current ↩︎

  39. Anaplan Customers — Del Monte (speed claim) — n.d ↩︎