Skip to content

Palm Product Knowledge

A knowledge management system that ensures every product, design, and engineering decision at Palm is grounded in real customer problems and desired outcomes — never internal assumptions.

Philosophy

The core belief behind this system: deep problem understanding beats solution suggestions. When you truly understand how treasury teams work, what they're trying to accomplish, and where they struggle — product decisions become obvious.

Every insight flows through the Jobs to Be Done framework using the Desired Outcomes formula:

[Direction] + [Performance metric] + [Object of control] + [Context]

Example: - Job: "Reconcile bank transactions daily before 3 PM" - Outcome: "Minimize time required to match transactions across systems"

All extracted knowledge uses two-tier validation: - Confirmed Outcomes — 2+ independent sources corroborate - Emerging Signals — single source, needs corroboration before driving decisions

This keeps the knowledge base honest about what we actually know vs. what we've heard once.

Product Roadmap

Stack-ranked by priority. Each item is a job to be done — not a feature. The focus outcomes below each job are what we're actively investing in.

#1: See total liquidity position including invested cash alongside operational cash

Stage: Bicycle (Deliver) | Domains: Investments & Debt, Cash Visibility

Why now: Customers (Personio, ON) and prospects both requesting investment visibility alongside cash. Key differentiator vs spreadsheet workflows.

Focusing on: - Reduce effort to distinguish operational cash from invested cash - Minimize confusion about total available liquidity - Increase visibility into cash + cash equivalents in one view - Minimize the uncertainty when deciding investment duration

Already addressed: Investment tracking (⚠️ Partial), Cash position (✅)

→ View job page

#2: Apply percentage-based assumptions to forecasts while preserving underlying patterns

Stage: Skateboard (Validate) | Domains: Scenario Modelling, Cash Forecasting

Why now: Every customer and prospect does scenario modelling in Excel. Simple percentage-based adjustments that preserve underlying patterns are more valuable than complex scenario trees.

Focusing on: - Minimize the risk of overestimating collections or underestimating outflows - Increase the ability to model scenarios quickly (e.g., -5% on collections) - Reduce manual effort in creating multiple forecast scenarios - Minimize the loss of weekly/daily patterns when adjusting forecast totals

→ View job page

#3: Configure forecasting models based on data quality and account characteristics

Stage: Skateboard (Validate) | Domains: Cash Forecasting

Why now: Customers with 100+ accounts need control over which models run where. Current one-size-fits-all approach doesn't scale.

Focusing on: - Minimize forecast errors caused by poor data sources (e.g., unreliable ARP data) - Reduce time spent correcting forecasts that could have been configured better

Already addressed: ML on/off toggle (✅)

→ View job page

Delivered

Upload forecast data from files without extensive reformatting — View

View all jobs →

Voice of the Customer

Last updated: 2026-02-04

Emerging Signals

Not yet validated as jobs, but worth watching. Need more data points.

Signal Source What We're Hearing Questions to Explore
Debt management is a nightmare Avramar (expert) Complex loan structures, multiple tranches, floating rates, securities tracking all in spreadsheets How common is this? Enterprise only?
Proactive "don't forget" reminders Personio ML should remind about recurring items not yet in system Would this create alert fatigue?
Daily bank reconciliation ON Currently monthly, want daily. Identifying unposted transactions. Is this treasury's job or accounting's?
IC forecasting (paired) ON Entity-level variance looks wrong without IC How hard is the zero-sum constraint?
Percentage-based forecast adjustments Levi's Apply % flex for disruptors (tariffs, COVID) with explanation fields How to layer on ML without breaking patterns?
Regional team access & enablement ON Want to share Palm with 3 regional hubs; need entity-level permissions. Palm "way more intuitive" than Kyriba. What's the right permission model?

Sales Pulse

What prospects are asking about in sales conversations.

The pattern: Nearly every prospect we talk to is drowning in Excel. They've bought enterprise tools (Kyriba, SAP TRM, Oracle) but still run 20+ manual processes. The bigger the company, the worse the multi-entity problem - local teams doing things differently, no one trusts the consolidated view. Prospects aren't asking for "AI forecasting" - they're asking for relief from manual work and confidence they can trust the numbers.

Key themes explained:

  • Manual Excel forecasting: The universal pain. Even with TMS/ERP systems, treasurers maintain parallel Excel processes because the systems don't give them what they need. Bio-Rad runs 20 different Excel reports daily. CRCE spends 3 days/week on manual consolidation.

  • Kyriba/TMS limitations: Companies have Kyriba but describe it as "scratching the surface." Ocado has 30-40% uncoded transactions. Bio-Rad did extensive tagging but still can't get accurate forecasts. The tools exist but don't deliver.

  • Multi-entity complexity: Decentralized operations where each entity forecasts differently. TI Fluid has 58 entities with inconsistent execution. When local staff handle multiple roles, quality varies wildly.

  • 13-week horizon insufficient: Standard forecast window, but treasurers say it's not enough for strategic decisions (debt refinancing, investment planning). They want 6-12 month visibility.

  • ERP integration needs: Prospects want live AP/AR data flowing in, not manual uploads. Checkr moving to Oracle Fusion, Levi's pulling from multiple systems. The dream is "push-button forecasting."

  • Direct ↔ indirect bridging: Treasury forecasts (bank transactions) don't reconcile with FP&A budgets (P&L). CFOs ask "why is cash different from budget?" and treasurers can't easily explain.

Theme Frequency Recent Example Date
Manual Excel forecasting Very High "20 different Excel processes to determine end-of-day balances" - Bio-Rad 2026-01
Kyriba/TMS limitations High "Scratching the surface" with Kyriba, 30-40% uncoded flows - Ocado 2026-01
Multi-entity complexity High 58 entities with inconsistent local execution - TI Fluid Systems 2026-01
13-week horizon insufficient Medium "3 months insufficient for strategic decisions" - TI Fluid Systems 2026-01
ERP integration needs Medium Oracle Fusion, SAP migrations, want live AP/AR data - Checkr, Levi's 2026-01
Direct ↔ indirect bridging Medium Want granular direct cash flows for indirect comparison - Euroports 2026-01
FP&A misalignment Medium Budget forecasts vs actual bank positions don't reconcile - Checkr 2026-01

CS Pulse

What current customers are struggling with or asking for.

The pattern: Our customers want Palm to replace their Excel workflows entirely, not just supplement them. ON is tracking forecast accuracy (WMAPE) in Excel because Palm doesn't show it. Personio wants forecast-vs-forecast comparison we don't have yet. The common thread: they're bought in on Palm's value but frustrated that key workflows still require leaving the platform.

Key themes explained:

  • Category-level forecast accuracy: ON wants to see which categories (payroll, AP, AR, etc.) are forecasting well vs. poorly. When the CFO asks "why was the forecast off?", they need to point to specific drivers, not just a total number.

  • Forecast version comparison: Both ON and Personio track how forecasts change over time. Federico at ON built an Excel model to calculate WMAPE (weighted mean absolute percentage error). They want to see "what did we predict 4 weeks ago vs. what actually happened" inside Palm.

  • Investment data integration: ON manages investments outside Palm in spreadsheets. They want one view showing operational cash + investments + maturities. Current investment data in Palm is partially incorrect and creates more work than it saves.

  • Report Creator stability: Personio is testing our new Report Creator but hitting bugs - "Problem loading data" errors, sorting options appearing where they shouldn't. Needs polish before broader rollout.

  • Renewal risk - cost justification: Discogs is a smaller customer questioning whether Palm's cost is justified. They need Treasury Spring integration and cash forecasting working before April renewal. Clear signal that smaller customers need faster time-to-value.

  • Platform instability during changes: When ON did a major recategorization, dashboard numbers fluctuated unpredictably. Makes it hard to trust the platform during data cleanup exercises.

Theme Customer(s) Severity Recent Example Date
Category-level forecast accuracy ON High Want to see which categories drive variance 2026-01
Forecast version comparison ON, Personio High Tracking WMAPE in Excel, want forecast vs forecast with variance columns 2026-01
Investment data integration ON High Manual tracking creates maintenance burden, data partially incorrect 2026-01
Report Creator stability Personio Medium "Problem loading data" errors, sorting issues on single KPIs 2026-01
Renewal risk - cost justification Discogs High Need Treasury Spring integration + cash forecasting before April renewal 2026-01
Platform instability during changes ON Medium Recategorization caused fluctuating dashboard numbers 2026-01

Product Observations

Patterns and insights from the product team.

  • The spreadsheet gravity well: Even companies with enterprise TMS (Kyriba, SAP TRM) revert to Excel. Why? Flexibility. Bio-Rad runs 20 Excel processes despite having both SAP and Kyriba. We need to match spreadsheet flexibility with system reliability.

  • Confidence > Accuracy: Treasurers will accept a less accurate forecast if they understand and trust how it was generated. "Can I trust it?" is the universal question (ON, HelloFresh, Ferguson all ask it). Explainability is table stakes.

  • The 150-account problem: ON has 150+ accounts. No one can manually review them all daily. The job isn't "show me everything" - it's "show me what needs attention." Anomaly detection beats comprehensive dashboards.

  • IC is the elephant in the room: Everyone excludes IC from forecasts because it's hard. But entity-level variance is meaningless without it. First to crack paired IC forecasting wins.

  • The "push button" dream: Every treasurer we talk to wants to push a button and get a weekly forecast instantly. Dette at Levi's: "My treasurer just wants a button... push a button... it spits out everything for the week." Data gathering is the enemy; analysis is the value.

  • Variance analysis is "the most critical": David Watt at Sonder: "Just taking actuals and overwriting your forecast is not smart." The real value is understanding why the forecast was wrong, not just knowing it was wrong. Learning from variance enables better future forecasts.

  • Regional enablement unlocks enterprise scale: ON wants to share Palm with regional finance teams (APAC, Americas, EMEA) but needs access control first. They contrasted Palm favorably vs Kyriba: "With Kyriba, we feel like we had so many training sessions... every two weeks. Palm is way more intuitive." This is the path to $200-400k ACVs - more users per customer, feature tiers, and enterprise-grade permissions.

12-Month Product Vision

Where Palm needs to be to win.

The shift: From "forecasting tool" → "treasury decision platform"

Must-Solve Problems

Problem Why It's Hard Customer Evidence Status
Scenarios & Assumptions Layer user assumptions on ML without breaking it Personio, ON, Instacart, Levi's, Treasury Dragons Not started
Investments & Liquidity Data from many sources, maturity modeling ON, Personio, Avramar, Levi's In progress
Debt Management Complex structures, floating rates, covenants Avramar Not started
Forecast Explainability Make ML transparent without overwhelming users ON, Sonder, Ferguson Limited
Intercompany Forecasting Paired transactions, zero-sum constraint ON, Personio, Live Events Not started
Proactive Reminders "Late" vs "not happening", avoid alert fatigue Personio, Volvo Not started
Direct/Indirect Bridge Category mapping, working capital effects Personio, Euroports, Levi's Not started
AP/AR Integration Every ERP is different, data quality varies ON, Levi's Not started
Access & Entitlements Granular permissions without complexity, clean feature gating ON Not started

Read full vision document →

This page is the product team's homepage. Keep it current.