How I reduced 30 hours of reporting work every month

A business running blind on its own numbers

The company had data — but no system to turn it into decisions. Weekly reports showed total hours worked per employee and nothing else. No interpretation. No connection to revenue. No way to separate billable from unbillable time without significant manual effort.

Every two weeks, the owner was spending 12 to 15 hours manually calculating billable vs unbillable hours, cross-referencing job data, and trying to build a picture of how the business was actually performing. By the time the picture was clear, the week it described was already gone.

The owner was the reporting system — and it was always behind

The real problem wasn't just the time being lost. It was what the time loss was hiding. Without a reliable reporting structure, the business had no visibility into whether jobs were profitable, whether crews were performing, or whether the pipeline supported the season ahead.

Decisions were being made on instinct and memory. When things went wrong, there was no data trail to understand why — or to prevent it from happening again.

• Weekly reports showed hours worked — nothing more. No performance context, no revenue connection, no variance data.
• Determining billable vs unbillable hours required 12–15 hours of manual work every two weeks — primarily the owner's time.
• No visibility into budget vs actual, individual performance, or pipeline status in real time.
• Decisions were made on last week's data — by the time issues were visible, they had already cost money.
• The absence of data made it impossible to quantify how significantly jobs were overrunning — the problem existed but couldn't be measured.

It wasn't a data problem. It was a visibility problem.

The business had access to data through LMN and a CRM called Intrigue. The issue wasn't that the data didn't exist — it was that no system existed to extract it, structure it, and deliver it in a form anyone could act on.

Until a reporting infrastructure was built, the business couldn't even accurately measure how badly jobs were running over budget. The first thing the new system revealed was that jobs were routinely exceeding estimated hours by 15–30% — a figure that had been felt anecdotally but never confirmed. That confirmation, enabled by the budgeted vs actual data I built into the system, changed the conversation entirely.

A two-tier reporting architecture — from chaos to clarity

I designed and implemented a reporting system that pulled data from LMN and Intrigue, structured it into two purpose-built views, and eliminated manual calculation entirely. The system was built in Google Sheets — accessible, maintainable, and immediately usable without specialist knowledge.

I built two distinct tiers because the owner and the PM had fundamentally different information needs. Giving both the same report meant neither got what they actually needed.

One metric became six. Hindsight became foresight.

30 hours back. Better decisions daily. Real numbers for the first time.

The most immediate impact was time. The owner recovered 25 to 30 hours per month that had previously been consumed by manual reporting — time that went back into running the business rather than describing it.

But the more significant shift was structural. The reporting system I built didn't just save time — it created the financial nervous system the business had never had. For the first time, the owner could see what was actually happening inside the business, measure performance against expectations, and intervene before problems compounded.

The downstream effects were real. With pipeline visibility built into the system, the business was able to plan the season with data rather than instinct — contributing to a year in which seasonal staff turnover dropped from over 40% to 25%, and no field staff were laid off due to insufficient work for the first time in recent seasons.

• 25–30 hours per month recovered from manual reporting — primarily owner time, the most valuable and constrained resource in the business.
• Six reporting metrics introduced where only one existed — payable field hours, billable, unbillable, efficiency variance, daily expected vs actual, and pipeline breakdown.
• Jobs overrunning by 15–30% — previously felt but unmeasurable — identified, quantified, and addressable for the first time.
• Seasonal staff turnover dropped from over 40% to 25% in the engagement year, supported by pipeline visibility that enabled proactive workforce planning.
• Zero field staff laid off due to insufficient work — a direct result of pipeline clarity that had not been possible before the system existed.