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Platform Comparison

Pigment vs IBM Planning Analytics: Honest Comparison

The modern challenger meets the enterprise incumbent. Different eras, different architectures, both capable of serious planning.

Different generations, different strengths

Pigment represents the new generation of planning platforms. Cloud-native, intuitive interface, fast implementation, native AI. Designed for finance teams who want modern tools that don't require IT involvement. Strong with SaaS companies and growth businesses.

IBM Planning Analytics (powered by TM1) has three decades of enterprise refinement. Exceptional calculation speed, deep Excel integration, deployment flexibility, and the ability to handle complexity that pushes younger platforms to their limits.

This comparison often comes down to trade-offs: modern UX and speed vs. proven depth and flexibility. We've seen both deliver excellent outcomes - in different contexts.

Side-by-side comparison

Pigment IBM Planning Analytics
Platform age Founded 2019 TM1 since 1990s
Deployment Cloud only Cloud, on-premise, hybrid
User interface Modern, intuitive PAW or Excel
Implementation time 6-12 weeks typical 3-9 months typical
Excel integration Export/import Deep, native PAx
Complex modelling Strong, improving Exceptional depth
Enterprise scale Growing references Decades proven
AI capabilities Native agentic AI IBM watsonx integration

How each platform approaches AI

Both platforms are investing in AI, though from different starting points.

Pigment Agentic AI

Native AI designed for the platform from the start. Natural language queries generate insights instantly. Auto-detection of significant changes. Full explainability. Feels like AI was built into the product, not bolted on.

IBM Planning Analytics AI

AI-powered forecasting integrated into the TM1 engine. Scenario modelling with predictive insights. Leverages IBM's broader watsonx AI portfolio. Natural language querying available in Planning Analytics Workspace.

Pigment's AI feels more conversational and integrated into daily workflows. IBM's leverages their enterprise AI heritage. Both continue developing rapidly. Base selection on core planning needs, not AI alone.

Choose Pigment when...

User adoption is your biggest risk

If you've seen planning tools fail because people wouldn't use them, Pigment's interface changes the dynamic. Finance teams genuinely enjoy using it - not something you hear often about EPM platforms.

You need fast time to value

8-12 week implementations are realistic with Pigment. If you're under time pressure - PE deadline, board requirements, budget cycle - speed matters.

You want cloud simplicity

No infrastructure decisions, no upgrade projects, no IT involvement. If your strategy is cloud-first and you want finance to own their tools, Pigment fits.

You're a modern finance function

SaaS company, growth business, or traditional enterprise modernising finance. 30+ integrations, real-time collaboration, mobile access. Contemporary architecture for contemporary teams.

Choose IBM Planning Analytics when...

You need deployment flexibility

On-premise for data sovereignty, cloud for convenience, or hybrid for transition. Some industries and geographies require options that cloud-only platforms can't provide.

Excel is how your team works

Planning Analytics for Excel (PAx) provides deep, native Excel integration. Users work in familiar spreadsheets with live TM1 data. For Excel-centric teams, this isn't a limitation - it's the point.

You have extreme modelling requirements

Multi-step allocations, complex transfer pricing, sophisticated profitability analysis. TM1's rules engine handles scenarios that would require workarounds elsewhere. The platform has three decades of edge case handling.

You value proven scale

Large data volumes, thousands of users, mission-critical processes. IBM has decades of enterprise references. For risk-averse procurement decisions, track record matters.

Trade-offs to consider

Pigment's enterprise track record is shorter

Growing fast with customers like Unilever, Figma, and Gong - but fewer years of enterprise deployments than IBM. Risk-averse enterprises may find this relevant.

TM1 expertise is specialised

The TM1 talent pool is smaller than it once was. Deep TM1 skills take years to develop. Plan for how you'll resource ongoing maintenance - internal team or managed service.

Implementation approaches differ

Pigment projects tend to be shorter and more iterative. IBM implementations often involve more upfront design. Different project management styles suit different organisations.

Cost structures vary

Pigment's faster implementation often means lower total project cost. IBM's licensing can be more flexible for organisations with enterprise agreements. Compare total cost of ownership, not just license fees.

What about cost?

Neither vendor publishes pricing, and both vary significantly based on scope and negotiation.

Pigment's faster implementation typically means lower professional services spend. IBM's enterprise licensing agreements can provide significant discounts for existing IBM customers.

The total cost comparison depends heavily on implementation complexity, existing vendor relationships, and ongoing support requirements. Get specific quotes for your situation rather than relying on market positioning.

When neither platform is right

Sometimes the answer is neither Pigment nor IBM Planning Analytics.

You need connected enterprise planning. Anaplan might be the better choice for organisations needing deep integration across finance, sales, supply chain, and workforce - with a larger implementation ecosystem.

Your primary need is consolidation. Planful or Oracle EPM might be more appropriate if financial close and statutory consolidation dominate your requirements.

Your requirements are straightforward. Well-structured Excel, or simpler tools, might be sufficient for smaller teams without complex planning needs.

Practical next steps

Clarify deployment requirements

Cloud-only acceptable? Data sovereignty requirements? This often narrows the choice immediately. If on-premise is required, Pigment isn't an option.

Assess your user base

Excel power users who want to stay in Excel? Modern finance team wanting contemporary tools? User preferences should factor into the decision.

Test your hardest scenarios

Both platforms handle simple budgeting easily. Bring your complex allocation rules, your edge cases, your messiest data. That's where differences emerge.

Plan for ongoing support

How will you maintain and enhance the platform long-term? Internal team, managed service provider, or implementation partner? The answer affects both platforms differently.

Pigment vs IBM Planning Analytics FAQs

Is Pigment powerful enough to replace TM1?
For most standard FP&A use cases, yes. Pigment handles budgeting, forecasting, and scenario planning well. Where TM1 has an edge is extreme complexity: very large multi-dimensional models, sophisticated allocation rules, and scenarios that have been refined over decades of enterprise use. If your TM1 implementation is straightforward, Pigment could replace it. If it's highly customised and complex, evaluate carefully.
Should I migrate from TM1 to Pigment?
Migration means rebuilding, not transferring. If your TM1 environment works well, upgrading to Planning Analytics Workspace might be lower risk. If TM1 isn't meeting your needs - particularly around UX, adoption, or cloud strategy - then Pigment is worth considering. Budget for a full implementation, not a "migration."
Which is better for large enterprises?
IBM Planning Analytics has more enterprise references and longer track record. Pigment is growing in enterprise with customers like Unilever. For risk-averse enterprise procurement, IBM's history matters. For enterprises prioritising modern UX and fast deployment, Pigment is increasingly competitive. "Large enterprise" alone doesn't determine the choice.
How do the AI capabilities compare?
Both platforms have meaningful AI capabilities. Pigment's feels more native and conversational - built into the platform from the start. IBM's leverages their broader enterprise AI portfolio (watsonx) and integrates into Planning Analytics Workspace. Neither should be the primary selection factor; core planning functionality matters more. Both will continue evolving rapidly.

Need help deciding?

We've worked with both platforms and can provide objective guidance. Whether you're evaluating a new implementation or considering a migration, let's discuss your specific situation.