The 'A' in FP&A stands for analysis — but in most organisations, the analysis barely happens. McKinsey research shows that finance teams spend an average of 68% of their time gathering and validating data, leaving just 32% for the analysis, interpretation, and strategic recommendations that actually create business value. Here's how next-level FP&A teams are flipping that ratio.
McKinsey's title — 'Putting the A Back in FP&A' — captures the central problem with a single phrase. The 'A' stands for Analysis, but the data shows that analysis is what finance teams do least. The paper is a call to action grounded in operational data: 68% data gathering vs 32% analysis isn't a technology problem — it's a structural problem that technology can solve but only if organisations are willing to redesign their processes around it.
The Data Gathering Trap
The problem is structural. Most FP&A teams operate in environments where data lives in dozens of disconnected systems — ERP, CRM, HRIS, BI tools, spreadsheets — and reconciling it is manual, error-prone, and time-consuming. By the time the data is clean enough to analyse, the window for influencing the decision it was supposed to inform has often closed.
- Average FP&A team spends 68% of time on data gathering/validation (McKinsey survey)
- Only 32% of FP&A time is spent on analysis and strategic recommendations
- Finance teams typically work across 8-12 disconnected data sources
- Month-end close consumes 40% of finance bandwidth in most organisations
The Technology Layer That Changes Everything
The emergence of modern FP&A platforms — cloud-based, API-connected, with built-in ML — is enabling teams to automate the data gathering layer almost entirely. Platforms like Anaplan, Workday Adaptive Planning, and OneStream can ingest data from ERP and operational systems continuously, run automated consolidation, and surface exceptions — before a human even opens a spreadsheet.
The Process Redesign Required
Technology alone doesn't flip the 68/32 ratio. It requires deliberate process redesign: eliminating reports that no one reads, standardising definitions across business units, building self-service analytics for business partners, and ruthlessly prioritising which analyses actually drive decisions. McKinsey found that top-quartile FP&A teams have eliminated an average of 40% of their regular reporting outputs without any business impact.
The New FP&A Value Proposition
When finance teams are freed from data gathering, their value proposition shifts fundamentally. Instead of being 'the people who produce the numbers', they become 'the people who help us understand what the numbers mean and what to do about it'. This requires a different skill set — business judgment, communication, and the ability to structure complex decisions — but it's also where finance creates its highest value.
Building Toward Autonomous Finance
The endgame of this journey — what McKinsey calls 'autonomous finance' — is a state where routine financial processes run without human intervention, exceptions are surfaced automatically, and finance team time is almost entirely devoted to high-judgment activities. Few companies have achieved this today, but the path is clear and the technology now exists to walk it.
The CFO who asks 'how do I get my team to do more analysis?' is asking the wrong question. The right question is: 'how do I eliminate the data work that prevents them from doing analysis?'— McKinsey Operations (Putting the 'A' Back in FP&A, Mar 2022)
Practical Implementation Checklist
- Conduct a two-week time audit: have every finance team member log their time in 30-minute buckets across four categories — data gathering, data validation, report production, and analysis/advisory — then present the aggregate to leadership
- Identify your top 3 most painful data sources and set a 90-day target to automate or eliminate each one — prioritise by time consumed, not by strategic importance
- Run a 'report audit' this quarter: for each regular report, ask the recipient 'when did you last make a decision based on this report?' Eliminate any report where the answer is 'never' or 'I don't remember'
- Standardise data definitions across business units before investing in automation — automated consolidation of inconsistently defined data produces faster wrong answers, not faster right answers
- Build self-service analytics for your top 5 business-partner questions — when business unit leaders can answer their own data questions, they stop submitting requests that consume finance team time
- Define what 'autonomous finance' means for your organisation in 3 years: which routine processes should run without human initiation? This target shapes your technology investment roadmap
Putting the 'A' back in FP&A requires a two-front assault: technology automation of the data layer, and ruthless process redesign to eliminate reporting that no one uses. The organisations that have achieved the 80/20 reversal (80% analysis, 20% data work) did both simultaneously — technology without process redesign delivers faster data gathering but not less of it.
Key Takeaways
68% of FP&A time on data gathering is structural waste — not inevitable
Modern FP&A platforms can automate the data layer, freeing analysts for actual analysis
Process redesign is as important as technology: eliminate reports no one uses
Top teams have cut regular reporting output by 40% with no business impact
The goal is autonomous finance: routine processes run automatically, humans focus on judgment
A time audit (logging how finance time is actually spent) is the essential first step before any improvement program
Self-service analytics for business unit leaders reduces ad-hoc finance team requests, compounding the time savings from automation
