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Art of Accounting: How to end the self-created pipeline problem

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2 years ago

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I quit two jobs I liked because of poor raises. I resolved that when I had my own practice, I would not let this happen to my staff. And it never did because I paid the right salaries (and usually on the higher level). Of course there were exceptions. There are always exceptions. But as a rule, I never lost staff because of inadequate salary or a poor raise.

I do not think I was so imaginative, innovative or even too bright. I was using my early experiences as the role model to keep staff that wanted to stay and who I also wanted to stay. As things worked out, I pretty much made the right decisions when I quit since each future firm gave me added experience and opportunities, and the appropriate salaries.

I feel disgusted when I read interviews and articles about the pipeline “problem” when one of the causes cited is the low salaries being paid to entry-level and experienced staff who could earn much more in positions outside the profession.

I, along with my partners, came up with rationales for our higher salaries. I think these are just plain common sense. It was certainly good business for us, and here are some of the things we did and the reasons. This shares my pre-Withum experiences, but from what I hear from colleagues, everything we did is still valid. However, very few firms duplicate it, just as very few duplicated it 45 years ago when I started writing and speaking about this. This is not new stuff. 

  • For starters, we were a small practice and primarily hired people out of school. Generally, we weren’t competing with the larger firms that had higher starting salaries, so we paid a little lower than “market” to get staff on board. We had a great training program and our staff advanced quite rapidly. What we did was recognize the value they acquired and gave them a raise after six months and every six months thereafter for about two to two and a half years until their steep learning curve leveled off somewhat, and then moved them to an annual raise. We, in effect, paid them what they were worth at the end of every six-month period. 
  • Many colleagues pointed out to us that we were paying staff for what we taught them at our expense, and they thought we were foolish. The fallacy in this is that our staff owned what we taught them and if they left, we lost what they knew, the relationships they established with clients and the level they were performing at for us at that time. We did what we needed to do to keep them, and since money was a key issue we paid them what they were then worth in the market.
  • The result for us was a much lower turnover and greater longevity with us and with our clients. This cut our time recruiting and onboarding and training new staff. Instead, we had added time to bring our staff along to perform at higher levels … and for which we gladly paid them. Our colleagues got mired in a cycle of ongoing staff replacement recruiting and onboarding that we completely avoided. And this accelerated our growth.
  • Our accelerated growth also led us to innovate more and provide added services to clients, increasing client satisfaction and our income. Clients also appreciated that we did not have a revolving door of new staff. 
  • We actually had a revolving door, but it was for controlled growth for staff and more efficient client servicing, without disruption to clients. We realized staff could not grow if they remained on the same clients indefinitely. What we did was have someone who worked on a client start after two years to train a newbie for a year and then step back and become their supervisor. The newbie worked another year by themselves, and then they were ready to train the next newbie on that client. The clients saw continuity and because of our systems there was never a break in the services or deliverables. Depending on the dynamics, occasionally the supervisor remained on that client as the manager and performed many of the services a partner would have performed.  
  • We trained staff well in the technical areas and also on our systems, methods and culture. Further, because of our systemized approach to training, a one-year staff person was able to train an entry-level person, just as a two-year person was able to train the one-year person, and this worked all the way up the experience ladder. Our managers were trained by us and started their careers with us.
  • I recall reading a cartoon showing two older partners talking to each other. One said, “Why should we spend effort training staff who will then leave?” The other said, “Suppose we do not train them and they stay!”
  • We trained to have staff perform at the highest level they were capable of as long as they worked for us. If we only got an extra year out of them, it was well worth the effort and expense, but we usually got more than that extra year.
  • Another thing we did was pay for overtime hours in the next paycheck. They worked extra, they were paid for it! If we weren’t able to generate added revenue from their added work, we did not deserve to remain in business. Our staff never complained about working overtime, and I was told that some spouses encouraged it because of the added payment.
  • As for overtime, we only asked staff to work extra if there was work that needed to be done. This certainly was during the couple or three weeks before March and April 15, but not usually during other periods except if there were special circumstances.

There is a lot more, but the shallow reason that the pipeline is drying up because of low or inadequate salary could easily be remedied. We have it within our power to change this. When will you start?

I posted an earlier column with four reasons why staff remain with a firm. Money was one of them and the others were, growth, experience and flexibility.

Do not hesitate to contact me at [email protected] with your practice management questions or about engagements you might not be able to perform.

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Accounting

AI-Driven Automation and Continuous Accounting Frameworks

Published

4 days ago

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August 15, 2026

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The accounting profession is undergoing a fundamental structural transition as enterprise finance departments shift from periodic month-end closes toward automated continuous accounting models. By integrating specialized machine learning algorithms directly into enterprise resource planning (ERP) platforms, chief accounting officers are transforming financial reporting from a retrospective exercise into a real-time operational asset.

The Shift from Periodic Close to Continuous Financial Reporting
Traditional accounting workflows heavily relied on manual data reconciliation, spreadsheet calculations, and multi-week closing cycles at the end of each fiscal period. In contrast, continuous accounting frameworks utilize automated software agents to process, validate, and post transactional data in real time as business activities occur.

Automated bank reconciliation tools cross-reference incoming bank feeds, invoice records, and purchase orders automatically. By resolving transactional variances instantly throughout the month, corporate accounting teams eliminate the traditional workload spikes associated with quarterly and annual closes.

Machine Learning in Audit Trails and Anomaly Detection
Advanced natural language processing (NLP) and machine learning tools are redefining internal audit and financial control environments. Automated systems analyze 100% of general ledger entries, identifying anomalous transactions, duplicate payments, and unauthorized journal entries in real time.

Rather than relying on random statistical sampling, corporate internal auditors can focus their attention on high-risk flags automatically surfaced by algorithmic monitoring platforms. This continuous risk assessment strengthens internal controls over financial reporting (ICFR) and significantly reduces fraud risk.

Evolving Roles for Accounting Professionals
As routine data entry and manual reconciliation tasks become fully automated, the skill set required for accounting professionals is shifting toward data analysis, system design, and strategic business advisory.
– Systems Governance: Accountants are increasingly responsible for monitoring algorithmic accuracy and managing data integration pipelines.
– Business Partnership: Finance professionals leverage real-time financial dashboards to advise operational leaders on margin management and working capital allocation.
– Regulatory Compliance Management: Accounting teams utilize automated platforms to ensure compliance with dynamic tax codes and international accounting standards.

Core Implementation Recommendations
1. Deploy Automated Reconciliation Tools: Integrate continuous transaction processing modules into existing enterprise ERP architectures.
2. Establish Algorithmic Governance Controls: Implement strict internal testing protocols to ensure automated accounting rules comply with GAAP/IFRS standards.
3. Reskill Accounting Teams: Invest in training finance staff on data analytics, workflow automation, and predictive financial modeling.

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Accounting

Global ESG Reporting Standards and Double Materiality Compliance

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1 week ago

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August 9, 2026

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Corporate accounting departments face expanding reporting expectations as international sustainability disclosure standards achieve regulatory enforcement across major global jurisdictions. Chief Accounting Officers (CAOs) and corporate controllers are establishing rigorous internal accounting controls to treat Environmental, Social, and Governance (ESG) metrics with the same data precision, auditability, and governance as traditional financial statements.

Regulatory Harmonization Under Global Sustainability Frameworks
The implementation of standardized sustainability reporting frameworks—notably rules established by international sustainability accounting boards—has created unified expectations for public and large private enterprises. Corporations must report standardized metrics covering greenhouse gas emissions (Scope 1, 2, and material Scope 3), energy utilization, workforce demographics, and supply chain governance.

In Europe and other participating international jurisdictions, double materiality principles are mandatory. Under double materiality, organizations must report both how external sustainability risks impact corporate financial performance, and how internal corporate operations affect surrounding environmental and social structures.

Integrating Sustainability Metrics into Core ERP Systems
To provide auditable non-financial data, enterprise organizations are integrating specialized carbon accounting and ESG management platforms directly into core ERP systems. Automated data collectors capture energy utility invoices, logistics fuel consumption metrics, and vendor compliance records in real time.

Establishing automated, traceable data pipelines ensures that non-financial reporting is supported by clear audit trails. This structured approach allows external financial auditors to provide reasonable assurance on sustainability disclosures during annual corporate reporting cycles.

Financial Impacts and Capital Market Disclosure
Accurate ESG reporting directly influences corporate cost of capital and institutional credit ratings. Commercial lenders and institutional asset managers systematically incorporate sustainability metrics into risk pricing models. Companies that demonstrate transparent, verifiable progress in operational energy efficiency and climate risk mitigation benefit from expanded access to green bond markets and lower debt pricing.

Action Steps for Accounting Leadership
1. Implement Double Materiality Frameworks: Conduct comprehensive assessments to identify material financial and operational sustainability metrics.
2. Build Auditable Non-Financial Data Pipelines: Automate ESG data collection within core accounting software to ensure data integrity.
3. Align Sustainability with Annual Financial Filings: Prepare non-financial disclosures concurrently with financial statements to satisfy regulatory audit expectations.

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Accounting

Modernizing Internal Controls: Machine Learning and Continuous Monitoring in Auditing

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2 weeks ago

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August 5, 2026

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Internal audit departments and corporate risk managers are modernizing internal control frameworks by shifting from periodic sampling techniques to continuous monitoring and machine learning analytics. As operational data volumes increase across enterprise organizations, automated control testing ensures financial integrity, prevents corporate fraud, and streamlines annual audit engagements.

The Limitation of Periodic Audit Sampling
Historically, internal and external auditors evaluated internal controls by reviewing random samples of financial transactions—often analyzing less than five percent of total ledger entries. In complex enterprise environments, periodic sampling methods carry inherent risks of overlooking localized financial misstatements, unauthorized disbursements, or operational control breakdowns.

In 2026, progressive internal audit functions are utilizing automated continuous monitoring platforms that evaluate one hundred percent of financial transactions in real time. Continuous control auditing systems continuously monitor general ledger entries, procurement approvals, and expense reimbursements across all operating subsidiaries.

AI-Powered Fraud Detection and Anomaly Identification
Machine learning models trained on historical corporate financial data excel at identifying subtle transactional anomalies that indicate potential fraud or operational error. Automated systems instantly flag duplicate invoice payments, unapproved vendor creation, unusual journal entry timing, and unauthorized override of authority thresholds.

When an anomaly is detected, the automated auditing platform generates an instant risk alert, allowing internal audit teams to investigate root causes immediately. Early detection prevents minor operational errors from escalating into material weaknesses in financial reporting.

Streamlining External Audit Preparation
Continuous internal control monitoring delivers significant benefits during annual external financial audits. External audit firms can review continuous audit logs and automated control testing documentation, reducing the time required for manual field testing.

This integrated approach lowers overall audit compliance fees, reduces administrative burdens on corporate accounting staff, and provides senior management and audit committees with real-time visibility into the organization’s overall risk profile.

Core Implementation Guidelines
1. Transition to 100% Data Testing: Replace legacy sampling methods with automated continuous audit monitoring systems.
2. Deploy Anomaly Detection Algorithms: Implement machine learning models to identify unauthorized transactions and operational control overrides.
3. Align Internal and External Audit Workflows: Coordinate continuous control testing protocols with external auditors to optimize annual compliance cycles.

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