Why monthly reporting takes so much manual work, step by step

46% of FP&A time goes to collecting and validating numbers, the highest in five years, and 59% where the data is poor. The hours are not in building the report. They are in making the numbers agree before anyone can build it, and that is a different problem with a different fix.

Your team spends days on the monthly pack and most of it is not analysis. That much is usually agreed. What is rarely agreed is which part of the process is eating the days, and the answer decides whether the fix costs 10 weeks or 26.

The FP&A Trends Survey 2025, published with OneStream across 459 finance professionals, puts 46% of FP&A time on data collection and validation, the highest figure in five years, against 31% on insight and action. Only 2% of teams describe themselves as optimised.

So the hours are real and measured. The question is where inside the cycle they sit.

Where the time goes, by how good the data is

Where FP&A time goes, by how good the data underneath is

The same team, the same tools. What moves the split is whether the inputs agree before anyone opens a report.

Only 17% of respondents report best-in-class or advanced data quality, down from a five-year peak of 23% in 2022. So the 59% row is closer to most teams' reality than the 35% one.

Source: FP&A Trends Survey 2025, published with OneStream, n=459 finance professionals across industries and regions, 38% Europe and 8% Asia.

The same survey splits that time allocation by data environment, and the split is the most useful number in the whole report. Teams with strong data spend 35% of their time collecting and validating and 42% on insight. Teams with poor data spend 59% and 19%.

That is a 24-point swing in how much of a finance team's week is recoverable, driven by whether the inputs agree before anyone opens a report. It is not driven by the reporting tool.

Worth knowing how many teams sit at each end. Just 17% report best-in-class or advanced data quality, down from a five-year peak of 23% in 2022. Low-quality environments fell from 40% in 2021 to 25% in 2025, and the middle ground grew from 39% to 58%. The survey describes that middle group as working with multiple sources that are mostly aligned but still require significant effort to consolidate, which is a precise description of where the manual hours come from.

The six steps, and which three are the problem

The six steps in a monthly pack, and what makes each one manual

Time the steps separately. Most teams assume the hours are in building the report, and they are almost never there.

Steps two, three and six are reconciliation. They are usually the majority of the elapsed time and the first thing left out of an automation business case.

Source: Thinklytics engagement pattern across the 14 automated executive reporting engagements in the case library.

A monthly pack has six steps. Time them separately for one cycle and the answer is usually obvious by the end of the week.

Pull the data. Four systems, four export formats, one person who knows which filters to apply. Annoying, and usually a morning.

Make the numbers agree. No written rule says which figure is right, so the difference gets investigated again every month. This is where the days start.

Chase the exceptions. A late journal, a missing cost centre, an acquisition still on its own chart of accounts. Each one is a conversation.

Assemble the pack. Copy into a deck, then reformat when a number changes upstream.

Write the commentary. The only step that is analysis. This is what the saved hours are for.

Rework after review. A reviewer finds one number wrong and four slides move.

Steps two, three and six are reconciliation and its consequences. They are usually the majority of the elapsed time, and they are the first thing left out of an automation business case because they do not look like a software problem.

Why buying a reporting platform leaves most of it behind

The clearest evidence on this comes from a company that sells planning software, which is what makes it worth reading.

Vena's 2026 FP&A Impact Report, administered in October 2025 with the research firm Benchmarkit across 431 finance professionals at organisations from under $50M to above $1B revenue, found 90% of teams still relying on Excel alongside their primary planning platform for at least some models and reports. That figure was 89% the year before, so it has not moved. Spreadsheets were the most-used tool for budgeting and forecasting, cited by 61%. A third ranked spreadsheet reliance as their number one technology challenge and 66% put it in their top three.

The same survey found 51% with only moderate or limited integration between their FP&A tools and their source systems, and 7% with no integration at all, depending on manual uploads. Nearly a quarter of respondents above $1B in annual revenue said they rely on Excel as their primary planning tool.

A separate survey, run by Centiment for Vena between 16 and 18 July 2026 across 364 finance professionals from Finance Manager to CFO at organisations above 200 employees in the US, Canada and the UK, found 92% of teams that already own planning software still using Excel at least weekly, and 53% of that group expecting their Excel reliance to increase rather than decrease.

Both are vendor-commissioned and should be read that way. The direction of the finding runs against the vendor's commercial interest, which is unusual enough to be worth the attention.

What the cycle looks like when the inputs get fixed

What the cycle looked like before and after, in nine engagements

Published delivery outcomes, not a vendor average. The pattern is that the cycle collapses once the inputs are settled, not once the reporting tool changes.

The insurer's 480 to 32 person-hours is the one worth copying into a business case, because it decomposes. Hours are checkable by the people who worked them; a percentage is not.

Source: Thinklytics case library, published delivery outcomes per engagement.

Nine engagements in our case library published a before and after cycle time. The pattern is consistent: the cycle collapses once the inputs are settled and the exception handling moves in front of the pack, rather than when the reporting tool changes.

A statutory NAIC filing went from six weeks and 480 person-hours a quarter to four days and 32. Federal reporting at a public university went from three months to two days. A quarterly call report at a regional bank went from three weeks to two days, which came from defining all 140 line items and automating extraction and calculation, with the platform left in place. A monthly close at a national telecom went from 18 days to three.

The 480 to 32 is the number worth copying, because it decomposes. Person-hours are checkable by the people who worked them. A percentage saving is not.

What it costs while it stays manual

Two costs, and the second one is larger.

The direct cost is labour, and it is countable. $2.8M a year of reporting labour automated at a public university across 42 certified metrics. $1.9M a year across 67 school districts. $1.1M a year of compliance labour at an insurer. $680K at a regional bank.

The second cost is the decision that arrived late. Intuit's Future of Finance 2026 report, fielded in May 2026 by CatalystMR across 2,000 US CFOs, controllers and VPs of Finance at businesses above $2.5M revenue, found 57% had missed a time-sensitive strategic action in the previous six months because financial visibility arrived too late, and only 14% had same-day data for their most recent major business decision. That is a vendor-commissioned, US-only, self-reported survey, and the shape of it matches the independent work: EY's 2026 Global DNA of the CFO survey, fielded 16 February to 30 March 2026 across 1,610 finance leaders at organisations above $1B revenue in 28 countries, found 47% of CFO capacity going to operational tasks and only 27% saying finance is perceived as a strategic value partner.

The FP&A Trends figures land in the same place from the other direction: 45% of FP&A teams are recognised by senior management as a business partner, and just 9% act as true strategic partners.

What we would do first

Two measurements, one reporting cycle, no software decisions.

Time the six steps separately. Not the total, the six. Most teams discover the split is not what they assumed, and the split is the entire basis for what to fix.

Then count the distinct numbers in the pack and how many have one named person who can state the definition and the source without opening a spreadsheet. That ratio tells you how much of the pack is automatable today and how much would simply be published faster and wrong.

With those two numbers you know which problem you have. If the hours are in reconciliation, the route is in automate management reporting without new systems. If the disagreement itself is the issue, start at why sales and finance report different revenue. If the pack is already clean and the assembly is the bottleneck, AI reporting automation and analytics and BI are the delivery surfaces, with decision support systems for the executive layer above them. The full set of work in this area sits under reporting takes too much work.

Frequently asked questions

Why does monthly reporting take so much manual work?

Because most of the elapsed time is spent making numbers agree, not building the report. The FP&A Trends Survey 2025, published with OneStream across 459 finance professionals, found 46% of FP&A time going to data collection and validation, the highest figure in five years, against 31% on insight and action. Where data quality is poor that first figure rises to 59%. Reporting tools make the assembly step faster. The assembly step is rarely where the hours are.

Which step in the cycle actually holds the hours?

Reconciliation, exception chasing and post-review rework, which are steps two, three and six of six. Pulling the data is usually a morning. Writing the commentary is the actual analysis and should take as long as it takes. The three steps in between exist because no written rule says which number is right, so the same difference gets investigated again every month. Time the six steps separately for one cycle and the answer is usually obvious within a day.

Will a new reporting tool fix it?

It fixes the assembly step and leaves the rest. The clearest evidence comes from a company that sells planning software: Vena's 2026 FP&A Impact Report, administered October 2025 with Benchmarkit across 431 finance professionals, found 90% of teams still relying on Excel alongside their planning platform, 61% naming spreadsheets as the most-used tool for budgeting and forecasting, and 33% ranking spreadsheet reliance as their number one technology challenge. The platform arrived and the manual work stayed.

Is this a data quality problem or a process problem?

Both, and the data side is the larger lever. The same FP&A Trends survey splits time allocation by data environment: teams with strong data spend 35% of their time collecting and validating and 42% on insight, while teams with poor data spend 59% and 19%. Only 17% of respondents report best-in-class or advanced data quality, down from a five-year peak of 23% in 2022, so the 59% row describes more teams than the 35% one does.

How long should the monthly pack take?

APQC benchmarking published in June 2026 puts top-quartile performers at six calendar days from the initial business-entity trial balance to the completed period-end management report, with a median of 10 and bottom quartile at 15. Those are calendar days including weekends. APQC publishes no fieldwork date for that quartile split, so treat it as a 2026 publication rather than 2026 fieldwork, and compare your own measured number against it rather than against a vendor claim.

How much of the time is rework?

More than most process maps show, because rework is invisible until someone counts it. A reviewer finds one number wrong, four slides move, and the hours get logged against assembly rather than against the disagreement that caused it. Counting how often the pack comes back, and for what, is the cheapest measurement in this whole exercise and frequently the one that changes the scope of the fix.

What does the manual work actually cost?

Count it in person-hours before converting it to money, because hours are checkable by the people who worked them. One insurer was spending 480 person-hours a quarter preparing a statutory filing and ended at 32. A public university was automating $2.8M a year of reporting labour across 42 certified metrics. A group of 67 school districts was spending $1.9M a year on a submission that had been manual. The second cost is larger and harder to measure: the decisions that arrived late because the pack did.

Where should we start?

Time the six steps separately for one cycle, then count how many distinct numbers are in the pack and how many have one named owner who can state the definition and source without opening a spreadsheet. Those two measurements take a single reporting cycle and they tell you whether you have a reconciliation problem, an assembly problem or a platform problem. Doing them before shortlisting software is what stops a tool being bought for a problem sitting two steps upstream.

The work behind this

Fourteen engagements in the case library carry automated executive reporting. Nine of them published a before and after cycle time, from a six-week statutory filing cut to four days to an 18-day monthly close cut to three.

Automated executive reporting, 14 engagements.