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 — not 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 — possible solutions become more accurate.

Every insight flows through the Jobs to Be Done framework, using the Desired Outcomes formula as a guide:

[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.

Note: We use JTBD and the Desired Outcomes formula as a helpful framing tool, not a rigid standard. Not every job or outcome will adhere perfectly to the formula due to practical limitations — we do our best to capture the intent clearly.

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: Bridge direct and indirect cash flow forecasts to explain variance drivers

Stage: Skateboard (Validate) | Domains: Bridging

Why now: Four sources validate the need (Euroports, Personio, Levi's, ON) — treasury teams manually reconcile direct cash forecasts to indirect budgets in Excel today. Euroports Apr 2026 prototype feedback validates the v0 direction: top-of-page variance flags, category mapping UI, and working capital drill-down. The wedge is explaining working capital variance drivers without a 'lengthy interview process' with local entities.

Focusing on: - Minimize the time required to identify deviations between direct cash flows and indirect budget - Reduce the frequency of having to ask local entities for variance explanations - Increase visibility into working capital movement drivers (AR vs AP breakdown) - Increase the ability to drill from consolidated variance down to entity and transaction level

→ 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

See total liquidity position including invested cash alongside operational cash — View

Upload forecast data from files without extensive reformatting — View

View all jobs →

Voice of the Customer

Last updated: 2026-04-30

Emerging Signals

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

Signal Source What We're Hearing Questions to Explore
FX exposure and risk management ON, Personio, Discogs (2026-03) ON building FX risk management from scratch (Yulia: four exposure categories). Personio wants FX policy triggers and automated notifications. Discogs tracking FX losses on Bound trades. Three customers in one period — wasn't on the roadmap but demand is real. Is this a standalone domain or a scenario building block? What's the minimum viable FX feature? How does it relate to the co-founder's FX Flow vision pillar?
Dynamic minimum cash threshold per entity ON (2026-03-04) Lucia wants a calculated minimum cash line (e.g., "2 weeks of upcoming payables") overlaid on forecast — moves with the forecast, not hardcoded. Used for CFO M&A guidance, regional buffer negotiations. "You keep telling me you need 200, but what we see is you'd be okay with 50." Is this a scenario building block or a distinct feature? How do other customers think about minimum cash?
Proactive data monitoring & alerts Discogs, ON, Personio (2026-03) Discogs missed a GBP account upload — caught manually through variance checking. ON has ~3,000 outliers from miscategorization. Personio wants counterparty risk updates, payment rail outage alerts. Customers catching data issues manually. How to avoid alert fatigue? Build into existing workflows vs new notification system? What triggers are valuable?
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?
Payment execution Highline Explicit dealbreaker — won't buy without it. ~250 monthly payments. Also evaluating Kyriba, GTreasury, Nihilus Build vs integrate? What's the market size for payment-first buyers?
Push reporting for regional teams ON Regional finance teams lack basic visibility. Scheduled PDF reports to APAC/Americas/EMEA hubs — not requiring Palm login. $8M IC payment from Canada went unnoticed Is this access control, or a distinct distribution model?
Forecast explainability at category level Personio, ON (2026-04-29 reinforces) Tom wants to see WHY a forecast value is what it is. ON's FC Validation deck built WMAPE methodology in Excel because Palm doesn't have it. Lucia (new ON Group Treasurer, 2026-04-29) escalates the bar: "I need visibility... I also need to see how you come to that number. You're never going to trust a black box." Trust is the gating constraint for FP&A adoption of Palm as the official cash translation source. What's the minimum viable explainability surface — assumptions + calculation path? Or full audit trail? Is "Gemini-style step-by-step reasoning" (Lucia's reference) the right pattern?
Replace rule-based bridge translation logic ON (2026-04-29) Lucia wants Palm to ingest P&L + balance sheet plans and produce direct cash flow itself, replacing the hand-maintained Anaplan tables (AR aging splits, VAT timing, inventory→COGS detour). "Replace rules by logic." She'd pitch this back to FP&A as the official source if Palm's logic is good enough. ON volunteered to pilot boundary testing (direct → indirect → raw P&L). Is this v2+ scope for the bridge, or a separate ambition? What level of explainability earns FP&A buy-in? Does this generalize beyond Anaplan-based shops?
Invoice discounting integration Nash Squared Nadim to send details. Non-standard financial instrument How common is this in the ICP?

Sales Pulse

What prospects are asking about in sales conversations.

The pattern: Excel is still the universal competitor — every prospect maintains parallel spreadsheet processes regardless of existing tooling. But the conversation is shifting. Prospects aren't asking "can you forecast?" — they're asking "can I trust it, can I stress-test it, and can my team use it?" Enterprise names are entering the pipeline (Mercedes-Benz, SSE, Morrisons, Anglian Water), all bringing multi-entity, multi-currency complexity. The PoC/sandbox motion is the deal accelerator: every advancing deal (Swiss Steel, Bio-Rad, Euroports, DAZN) is progressing through hands-on evaluation with their own data. The bridging prototype is now a deal-shaping artifact — Euroports' Matthias validated the v0 direction in a 2026-04-15 prototype review ("more than enough validation to keep going").

Key themes explained:

  • Excel is still the real competitor: Even with Kyriba, SAP TRM, or Oracle, treasurers maintain parallel Excel processes. Bio-Rad runs 20 different Excel reports daily despite Kyriba. Swiss Steel has 16 entities sending individual Excel forecasts since 2019. DAZN has a 2+ year custom Excel model with deep organizational trust.

  • Role-based access control: Euroports (critical for April close), Digital Realty, Nash Squared, and ON all need RBAC. Entity-level permissions are table stakes for enterprise deals and the gateway to multi-user expansion.

  • Scenario planning / stress testing: DAZN (acquisition what-ifs, 10% EUR shock), Swiss Steel, Euroports all asking for what-if modelling. Validates our #1 roadmap bet. ON and Personio have both validated the prototype from the customer side.

  • Direct/indirect bridging as differentiator: Matthias (Euroports, 2026-04-15) walked through his current Excel bridge and validated Palm's v0 direction — top-of-page variance flags, category mapping, drill-down from consolidated → entity → transaction. Key asks: entity drill-down with group hierarchy, commentary capture, board-ready report output. The prototype reframes the bridge from "future feature" to "in-progress build with active customer feedback loop." Working capital deviation is the analytical core.

  • Data agnostic connectivity: Palm's ability to ingest via API, SFTP, MT940, BAI, CSV, and email is consistently called out as a differentiator. Nash Squared (15 banks), Dr.Max (900 accounts), Swiss Steel (30+ entities) all see this as a key advantage vs competitors requiring specific integrations.

  • Multi-entity complexity at scale: Swiss Steel (30+ entities), Dr.Max (550 entities, 900 accounts), BRF (global treasury with complex SAP) — the bigger the company, the worse the consolidation problem. This is our sweet spot.

  • AI categorization resonates: Nash Squared responded strongly to ~90% accuracy vs rules. Foot Locker's daily manual review of 3-4 transactions out of 1,000-2,000 validates the pain point.

Theme Frequency Recent Example Date
Manual Excel forecasting Very High 16 entities sending individual forecasts since 2019 — Swiss Steel 2026-03
Role-based access control High Entity-level permissions blocking purchase — Euroports, Digital Realty, Nash Squared 2026-03
Scenario planning / stress testing High Acquisition what-ifs, currency shocks — DAZN, Swiss Steel, Euroports 2026-03
Direct/indirect bridging High Euroports prototype review validated v0 direction; v0 in active build 2026-04
Data agnostic connectivity High MT940, BAI, SFTP, API, CSV, email flexibility — multiple prospects 2026-03
Multi-entity complexity High 550 entities, 900 accounts, one person in Excel — Dr.Max 2026-03
AI categorization Medium ~90% accuracy vs manual rules — Nash Squared, Foot Locker pain 2026-03
Payment execution Low Explicit dealbreaker for Highline (~250 monthly payments) 2026-03

Pipeline snapshot: 23 active deals, 13 new in 2 weeks, £500k weighted pipeline. Dunelm most advanced (S4, close target Apr 30). Bio-Rad PoC kicking off. Swiss Steel largest deal (£70k). Euroports down to Palm vs one other vendor.

View latest sales signals →

CS Pulse

What current customers are struggling with or asking for.

The pattern: The customer base is shifting from "adopting Palm" to "building on Palm." All three active customers showed strong engagement this period — Discogs building dashboards live in sessions, ON expanding into BigQuery integration and FX risk management, Personio planning full daily process migration by end of 2026. Pulse AI landed well across all three (Discogs: $60k investment calculation demo, ON: wants newsletter, Personio: wants market-intelligence digest). The new cross-customer theme is FX: ON building FX risk management from scratch, Personio wants policy automation, Discogs tracking FX losses — none of this was on the roadmap. In late April, Lucia (newly appointed Group Treasurer at ON, Apr 2026) entered the bridging conversation with the most ambitious customer ask yet: replace Anaplan's rule-based P&L→cash translation with Palm's model-driven inference, and pitch the result back to FP&A as the official source.

Key themes explained:

  • Pulse AI momentum across all customers: ON wants Pulse newsletter for seasonality insights. Discogs responded strongly to the demo ($60k investment calculation example, historical balance queries, FX trade support). Personio wants daily digest combining internal data + market events. All three exposed to Pulse this period with positive reception.

  • FX emerging as cross-customer theme: ON building FX risk management from scratch with Yulia (four exposure categories, CHF reporting currency needed). Personio wants FX policy triggers and automated notifications. Discogs tracking FX losses on Bound trades. This wasn't on the roadmap but demand is real from 3/3 customers.

  • Self-serve adoption inflection: Discogs building dashboards live in session (Jamie and Stephanie). ON getting self-serve dashboard simplification. Personio planning sprint-based module adoption. Cash analysis report described as "most popular report in Palm across all customers." Customers moving from "show me" to "let me do it."

  • AP/AR integration crystallizing: ON's BigQuery integration for AP/AR data is the first concrete implementation (~1 week Palm-side setup, Q2 target). New stakeholder Andrew Vendittelli (tech lead/PM) engaged. If successful, becomes the template for other customers. Reinforced 2026-04-29: Lucia confirmed AR/AP table is the first; long-term FP&A plan is the next BigQuery table she wants Palm to ingest.

  • Bridging prototype validated by ON's new Group Treasurer: Lucia (2026-04-29) validated the v0 direction and offered ON as a pilot to test tool boundaries (direct → indirect → raw P&L). She frames the bridge as the automated "plausibility check" — replacing the manual Excel/Anaplan side-by-side treasury does today before acting on Palm's forecast. Strategic ambition: replace Anaplan's hand-maintained translation rules entirely. Explainability is the gating constraint for FP&A buy-in: "you're never going to trust a black box."

  • Time-horizon split is the new mental model: Lucia is explicit that ≤13 weeks Palm wins (operational, treasury-driven, ignore long-term plan to avoid biasing the bottom-up forecast); >13 weeks (especially >6–7 months) FP&A long-term plan wins. "It just creates friction in the conversation with controlling when they say, you're not taking our numbers." Implication for product: the bridge view needs to weight the two forecasts differently across the horizon, not blend indiscriminately.

  • Proactive monitoring gap: Discogs missed a GBP account upload — caught through manual variance checking. ON has ~3,000 outliers from miscategorization. Personio still cross-checking Palm against legacy files. Customers catching data issues manually. Automated monitoring would increase trust.

  • Scenario planning expanding in scope: ON wants scenarios for growing categories. Discogs wants currency appreciation/depreciation modeling and stress testing. Personio wants worst-case from historical extremes. The need goes beyond simple percentage adjustments into currency-specific and timing-based scenarios.

Theme Customer(s) Severity Recent Example Date
Direct/indirect bridging validated by customer ON Positive Lucia (new Group Treasurer): v0 direction validated; ON volunteered as pilot for boundary testing (direct → indirect → P&L) 2026-04
Replace rule-based bridge logic with model-driven ON High Lucia wants Palm to replace Anaplan's hand-maintained translation tables and pitch back to FP&A as the official source 2026-04
Forecast explainability as FP&A adoption gate ON High "You're never going to trust a black box" — Gemini-style step-by-step reasoning is the reference 2026-04
FX exposure / risk management ON, Personio, Discogs High Yulia building FX risk from scratch (4 exposure types), Personio wants policy automation, Discogs tracking Bound losses 2026-03
AP/AR data integration ON High BQ integration in progress; long-term FP&A plan as next requested table 2026-04
Proactive data monitoring Discogs, ON High GBP account upload gap undetected; ~3,000 outliers from miscategorization 2026-03
Scenario planning ON, Personio, Discogs High ON: growing categories. Discogs: currency stress testing. Personio: worst-case from historicals 2026-03
Pulse AI adoption ON, Personio, Discogs Positive All 3 customers demo'd, Discogs $60k investment calc example landed well 2026-03
Self-serve dashboard adoption Discogs, ON Positive Jamie/Stephanie building dashboards live, cash analysis "most popular report" 2026-03
Personio full migration planned Personio Positive Tom planning full daily process migration to Palm by end of 2026 2026-03
CHF reporting currency ON Medium Yulia needs CHF (defaults to USD functional), balance sheet vs transaction exposure 2026-03
Filter/chart issues ON (Yulia) Medium Amount <0 filter not working, Y-axis showing "time", line chart not enabled 2026-03

View latest CS signals →

Product Observations

Patterns and insights from the product team.

  • The trust chain is sequential: Data quality → categorization → forecast accuracy → scenario analysis → decision-making. Each link broken undermines everything above it. Connectivity failures erode trust even when long-term forecasting performs well. As Gurjit put it: "Until someone trusts the outcomes hand over fist, there's no execution happening."

  • Short-term vs long-term forecast are two different products: ML is valuable for weeks 5-13+ (strategic: investments, FX hedging), but treasurers' magnifying glass is on the next 2 weeks (operational funding decisions). Short-term needs deterministic data (AP/AR, payroll), not probabilistic ML. We may not be aggressive enough on the deterministic layer. ON's validation deck confirms: Palm at 4.5% WMAP at 2 weeks vs Kyriba at 12.5% — short-term is where we win hardest.

  • Forecast validation as a sales weapon: ON's head-to-head vs Kyriba (8% vs 16% WMAP) is now a formal deck presented to leadership. Federico/Giannis built the methodology (snapshot vs horizon WMAPE, bias tracking, category-level KPIs) — this is the kind of proof point that closes deals. We should make it easy for every customer to run this comparison and productize the validation workflow.

  • FX is the next cross-cutting domain: Three customers independently raised FX in one period. ON is building risk management from scratch, Personio wants policy automation, Discogs is tracking losses. This aligns with the co-founder's FX Flow vision pillar but emerged from customer pull, not top-down strategy. The question is whether to tackle FX as a standalone domain or weave it into scenarios (currency stress testing) and reporting (exposure dashboards).

  • Pulse AI landed — now it needs direction: All three customers responded positively to Pulse, but each wants something different: Discogs wants ad-hoc Q&A ($60k investment calculations), ON wants scheduled newsletters (seasonality insights), Personio wants a market-intelligence-enhanced daily digest. The product question is which mode to double down on first.

  • The spreadsheet gravity well: Even companies with enterprise TMS revert to Excel. Bio-Rad runs 20 Excel processes despite Kyriba. DAZN has a 2+ year Excel model with deep organizational trust. Personio is in "quasi-process" state using Palm + legacy files for cross-checking. The transition from parallel running to full adoption is the key CS challenge.

  • PoC/sandbox is the deal accelerator: Swiss Steel, Bio-Rad, BRF, DAZN, Euroports — every advancing deal is progressing through hands-on evaluation. The faster we can spin up a sandbox with their data, the faster we close.

  • 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. Federico (ON): "More about building trust... methodology is a draft that we can improve over time."

  • Proactive > Reactive for AI: The highest-value AI use case isn't chat — it's scheduled analysis that surfaces things users didn't know to ask about. Giannis ran CapEx categorization analysis for Amanda (precision improved 90→96%); she didn't know to request it. Meanwhile, Discogs's missed GBP upload and ON's 3,000 outliers show that proactive data monitoring — upload verification, outlier alerting, freshness checks — would compound trust. Lower-effort than new features, high-impact for adoption.

  • IC is a multi-layer problem: The Feb IC sync mapped three layers: (1) Is it intercompany? (2) What type — cost plus, dividend, loan? (3) What's the operational implication? ZBAs are solvable, but cost-plus settlements — large, AP-driven, treasury lacks visibility — are the high-value target. ON's scenario session added FX dimension: failed IC payments create open currency exposure.

  • Scenario analysis has four building blocks, not two: Percentages (what-ifs), composable named events, timing shifts ("delay IC payments by 30 days"), and dynamic calculated thresholds. Plus Discogs wants currency-specific scenarios (appreciation/depreciation modeling). The building blocks are: amount, percentage, timing, dates, calculated thresholds, and currency.

  • Regional enablement unlocks enterprise scale: ON wants 3 regional hubs, Euroports needs entity-level access for local CFOs, Nash Squared has global locations. RBAC + push reporting is the path to $200-400k ACVs. ON's scenario session validated entity-level scenarios as key to regional buffer negotiations.

  • Connectivity is a trust investment, not an execution investment: Strategic reframe from the product bets discussion. We don't build connectivity because it enables features — we build it because it enables trust.

  • The bridge has two scopes, not one: Lucia (ON, 2026-04-29) sharpened a distinction the team had been blurring. Scope A = visualize and explain variance between an ingested plan and the cash actuals (the v0 prototype, validated by Matthias and Lucia). Scope B = replace the ingested-plan-production logic itself — Palm produces the direct cash forecast from P&L + balance sheet, displacing rule-based Anaplan tables. Scope A is current build. Scope B is a much larger arc but matters for product positioning: are we a viewer of the bridge or the production source? Lucia explicitly wants the latter and would pitch Palm's logic back to FP&A as official.

  • Two-tier forecast confidence is the canonical mental model now: ON treasury (via Lucia) names two legs of forecast trust: (1) variance analysis vs past actuals (looking back, increasingly automated by Palm), (2) plausibility check vs controlling's long-term plan (looking forward, manual today, what the bridge automates). Treasury hesitates to act on a forecast without both legs. Implication: the bridge isn't a separate analytical surface — it's the second pillar of "can I trust this forecast?" alongside variance analysis. Position the two together in product framing.

  • Time-horizon weighting is a real product question: Lucia is explicit that the binding source of truth changes with the horizon — Palm's bottom-up wins ≤13 weeks, FP&A's top-down wins >13 weeks (especially >6–7 months). The longer the horizon, the heavier controlling's plan should weigh. The bridge UI shouldn't blend indiscriminately. Open question for design: single weighted view, two stacked views, or a user-controlled slider?

  • No-touch ≠ no-override: Lucia's "low-touch treasury" vision isn't about removing user agency — it's about removing routine work while preserving the override path for special-knowledge cases. "On a regular day, I would love forecast to be more science than art... But I always want to have the option to go in and say, nah, let me type in five instead of two." Both must coexist. Product implication: don't design no-touch and override as opposites.

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 ON (8/10 on prototype; dedicated session validated timing shifts, dynamic min cash thresholds, entity-level scenarios), Personio (worst-case from historicals), Discogs (currency stress testing), DAZN, Swiss Steel, Euroports Assumptions backend shipped, timing shifts + min cash planned
Investments & Liquidity Data from many sources, maturity modeling ON (dashboard near-production, MMCs missing), Personio (migrating, Treasury Spring parser shipped, BlackRock issues), Discogs ($60k investment calculation via Pulse) In progress — Treasury Spring ingestion shipped, investment data in all datasets
Debt Management Complex structures, floating rates, covenants Avramar (syndicated loans, 6+ tranches), Personio (debt covenant reporting consuming Tom's focus until April) Not started
Forecast Explainability Make ML transparent without overwhelming users ON (formal validation deck: Palm 8% vs Kyriba 16% WMAP — "definitively the superior model", presented to leadership; Lucia 2026-04-29: "you're never going to trust a black box" — explainability is the gating constraint for FP&A adoption of Palm as the official cash translation source), Personio (wants category-level model explanations) Limited — WMAPE methodology built by customer, needs productizing; Lucia raises the bar to "Gemini-style step-by-step reasoning"
FX Exposure & Risk Multiple exposure types, policy rules, hedging workflows ON (Yulia building from scratch, 4 exposure types, CHF reporting currency needed), Personio (FX policy triggers, interest rate sensitivity), Discogs (tracking Bound trade losses) Not started — strong emerging signal from 3/3 customers
Intercompany Forecasting Paired transactions, zero-sum constraint ON (ZBA live, $8M missed payment, capex IC distinct from operational, failed IC payments create FX exposure), Personio (monthly sweep logic) ZBA in progress, full IC not started
Proactive Intelligence "Late" vs "not happening", surface unknown unknowns, avoid alert fatigue Pulse demo well-received by all 3 customers. Discogs: missed upload caught manually. ON: wants Pulse newsletter. Personio: wants market intelligence digest Pulse shipped (chat + digest), proactive monitoring not started
Direct/Indirect Bridge Category mapping, working capital effects, time-horizon weighting (Palm ≤13wk vs FP&A >13wk) Euroports (Matthias 2026-04-15 prototype review: v0 direction validated, working capital deviation as analytical core, board-ready output required), ON (Lucia 2026-04-29 prototype review: validated as automated "plausibility check"; ON volunteered as pilot for boundary testing direct→indirect→P&L; strategic ambition to replace Anaplan's rule-based translation logic), DAZN (budget vs forecast + EBITDA overlay), Personio Skateboard — v0 prototype validated by 2 customers; #1 active roadmap job; capability scope sharpened by ON into two arcs (visualize variance vs replace translation logic)
AP/AR Integration Every ERP is different, data quality varies ON (BQ integration planned Q2, Andrew Vendittelli engaged, ~1 week setup), Bio-Rad (Kyriba API issues) Not started — ON BQ integration is first concrete implementation
Access & Entitlements Granular permissions without complexity, clean feature gating ON (3 regional hubs, entity-level scenarios for regional buffer negotiations), Euroports (April deadline), Digital Realty, Nash Squared Roles & permissions design complete, entity management page shipped

Read full strategy →

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