Hiring more people is the most intuitive response to a growing client load. It’s also, for many audit practices, the one that keeps the problem in place.
Here’s the pattern: a firm wins new clients, staffs up to handle the volume and finds itself right back where it started (behind on data collection, chasing clients for reports and watching senior reviewers clean up files before they even have the chance to review them). Headcount scales the symptoms rather than fixing the system.
The place where that friction consistently lives is the beginning of the engagement, specifically the steps between requesting client data and having something usable to work from.
The Starting Point Problem
Most audit engagements follow a deceptively simple sequence. Audit teams request the data, receive the data, execute procedures, then review results. The first two steps are where things tend to go wrong, and their effects compound across everything that follows.
Inconsistent or unclear PBC requests lead to misinterpreted responses. Clients send wrong reports, pull wrong date ranges or omit fields they didn’t realize were needed. In certain cases, the audit team is already two or three steps deep into workpapers before they realize the data their client sent is incomplete.
Reformatting is the next tax. Client data arrives in multiple Excel files, in PDFs, in direct ERP exports, each requiring its own cleanup before it can be loaded into audit software and included in workpapers. For heavy data engagements, training a new staff member on that cleanup process alone takes days. That’s not an edge case. It’s the norm.
And then there’s what happens at review. A lack of standard data formats means workpapers vary engagement by engagement, causing senior reviewers to spend time understanding and double-checking the reformatting steps and “chain of custody” of the data to ensure nothing was lost along the way. That time comes directly out of the hours available for more critical review components, like risk assessment.
A Process Problem That Affects Staff and Clients
These inefficiencies have consequences that go beyond budget overruns. Auditing is still a people-driven business, and the professionals doing this work have options. Younger staff in particular aren’t treating marathon hours as an acceptable trade-off for career development the way earlier generations did. Firms that rely on absorbing friction through overtime are competing for talent against firms that have reduced how much friction there is to absorb.
There’s also a client dimension that often gets framed as solely a relationship issue. It’s a perception issue, as well. Clients today interact with technology that moves quickly and requires little from them. When an audit engagement kicks off with a long request list, a series of follow-up emails and weeks of back-and-forth, the contrast is noticeable. A process that feels disorganized to the client becomes a signal about the firm.
The Compounding Value of Consistency
These inefficiencies have persisted in part because they’ve been managed through institutional knowledge. Detailed PBC lists are refined over years. The same staff is assigned to the same clients. Often, the same individuals at the client are tapped to fulfill audit requests. Binders are rolled forward each cycle.
Those practices help, but they concentrate process knowledge in people rather than in a system. When someone leaves, on the audit team or at the client, the knowledge goes with them. The true replacement is the time to rebuild context, the variability in output while someone gets up to speed and the quality exposure in between.
Standardization addresses that directly. When the intake process is consistent, the starting point of every engagement looks the same regardless of which staff member prepared the request or who is on the client’s accounting team. Trial balances, general ledgers and subledgers are captured the same way every time and are already reconciled before they reach the workpaper.
The downstream effects are significant. Training gets faster because there’s a defined process to follow. Reviewers can focus on judgment rather than reorientation. Staffing decisions get easier when capacity is predictable rather than dependent on when the client finally sends the correct, complete data.
There’s also an AI-readiness dimension worth flagging. AI tools in audit operate on the data they’re given. Feeding inconsistent, unvalidated inputs into analytical tools only amplifies existing errors. Structured, reconciled data at the intake stage is the prerequisite for future technology investments to deliver anything close to what they promise.
The Client Side of the Equation
The internal efficiency case for standardization is reasonably well understood. The client-facing case gets less attention. Fewer back-and-forth requests, faster turnarounds and more predictable timelines add up to a materially different engagement experience.
In a market where fee pressure is real, being able to point to a faster and less disruptive process is a concrete differentiator. Clients that experience a smooth, consistent engagement are also the ones most likely to stay and refer. That dynamic is hard to manufacture through other means.
Where to Start
Before changing anything at the firmwide level, map how client data arrives on several audit engagements. The goal is to establish a baseline. Track the steps between the initial request and a usable starting point. Count the cleanup hours. Note where the variability lives: which clients send clean data, which don’t and why. That baseline makes the internal case and gives you something concrete to measure against later.
Once you have that picture, define what “standard” means for your practice. At minimum, a standardized intake process should specify:
- Standardized request list items – clear descriptions of items with plain English explanations and format requirements for each. Note you may need to do this by industry group due to different types of requests.
- “How to Run the Report” instructions – step-by-step instructions on how to run the reports you are looking for in their accounting system. Build your own knowledge base that teams can pull from for each relevant system
- What “ready to use” looks like – explicit reconciliation checkpoints for the audit team between data sources to ensure it is validated before it reaches the workpaper, not after.
- Who owns the handoff – a defined step where a staff member confirms data completeness before the engagement advances.
With those standards defined, run one engagement differently using the above guidelines. One pilot is enough to see where time goes and where it doesn’t have to anymore. Measure what changes: hours from initial request to a usable starting point, number of follow-up requests to the client and review comments tied to data quality rather than substantive findings. Those metrics tell you whether you’ve actually moved the needle.
On the technology side, the options have improved. Template-driven PBC tools, standardized ERP connectors and purpose-built data extraction platforms can automate the normalization and reconciliation steps that currently consume the most staff time. None of them replace the need to define your standard first, but once you have one, the right tool can make it repeatable at scale without adding headcount.
Most firms that move toward standardized data intake start with one engagement, confirm what changes and expand from there. The goal isn’t to fix everything at once. It’s to stop repeating the same friction on every new client. The firms that get there don’t do it all at once. They simply decide to start.
ABOUT THE AUTHOR:
Justin Pulgrano, CPA, is the senior vice president of strategic growth at Crunchafi, with 15+ years of experience blending deep CPA expertise and software innovation to drive business growth.
Sign in to get access to this free resource, and all of our whitepapers and reports.
Download this content today!
Register Now Already registered? Click here to Log In
Tags: Accounting, audit, Automation, engagements, erp, pbc requests, workpapers
