Do the math.
by Marc Rosenberg, CPA
Author of The Rosenberg MAP Survey
Reading MAP surveys and analyzing the statistics they contain can be challenging, but when used properly these surveys can be valuable tools to improve firm performance. Here’s a list – in no particular order – of the 10 biggest mistakes partners make in reading and computing MAP statistics.
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Avoid these common pitfalls and you’re well on your way to improving your firm’s performance.
1. Over-reliance on partner income percentage as a measure of profitability: This metric is impacted as much by the firm’s staff/partner ratio as by innate profitability. Therefore, we caution firms to avoid making rash judgments about profitability based solely on partner income percentage. Many partners have a rule of thumb that 33% is the minimum acceptable partner income percentage, and that to be “truly profitable,” this metric must be 40% or more. But as the data below illustrates, one must take the staff/partner ratio into account before determining norms for partner income percentage. If a firm is leveraged heavily, partner income percentages in the 20s and low 30s are perfectly acceptable.The following statistics, from a recent Rosenberg MAP Survey, are based on firms with annual fees of Two to $10 million dollars:
- Firms with a staff/partner ratio in excess of eight to one had a robust income per partner (IPP) of $491,000, yet their partner income percentage was “only” 23%.
- Firms with a staff/partner ratio ranging from six to eight to one had IPP of $450,000, yet their partner income percentage was 30%.
- Firms with a staff/partner ratio of under four to one produced a much less impressive IPP of $260,000, yet they enjoyed a seemingly high partner income percentage of 39%.
2. Being content with “average:” Remember, when a MAP survey cites an average for a group of firms, it’s just that – an average. To illustrate this point, let’s examine annual billable hours for staff. If the national average is around 1,530 and your firm is at 1,530, you have little cause for celebration because your performance was perfectly average. One hundred seventy-five firms did better than your firm! Ideally, you would like to achieve results well above the average in as many categories as possible.
3. Average salary data: I’ve seen many MAP surveys that tabulate the average salary for various positions at firms throughout the country. Examples: A two-year tax person, a four-year audit person, a firm administrator. This is one of the most senseless pieces of information I’ve ever seen, yet surveys love to report on it. The problem is that personnel from firms in New York City are mixed in with personnel from Montrose, Colorado. Personnel from a $30M firm are combined with personnel from a three million dollar firm. The resulting averages are utterly meaningless. Compensation data is only relevant if it is taken from a market that is comparable to your own, which is something that most MAP surveys cannot possibly do. If your firm is in Memphis, only surveys of Memphis firms will produce valid results that you can use to set compensation levels for personnel at your firm.
4. Utilization percentage: This metric is the total billable hours of a firm divided by the total work hours of the firm, with all personnel included. Firms also track utilization percentage for departments, partners, managers, seniors, etc. I’ve never been a big fan of utilization percentage because it is easily manipulated by the total hours a person works and the extent to which people record all of their billable time. I’m more interested in knowing how realized, billable hours per person or by department compares to budget than I am in knowing the percentage of billable to total hours. You can’t take a percentage to the bank, but you can take hours.
5. Net firm billing rate: This is calculated by taking the total annual net fees of the firm and dividing it by the total firm-wide billable hours. This rate is dramatically impacted by the firm’s staff-to-partner ratio. Here’s a great example. A client of mine with long-standing profitability problems called me after reading our latest MAP survey. He commented that, as usual, his firm lagged almost every industry norm. But with great pride, he told me that his firm’s net firm billing rate was 20% higher than the industry norm. I had to puncture his balloon by telling him: “Yes, you did well in this category. But that’s because you have 10 partners and nine staff!” Net firm billing rates in MAP Surveys are only relevant if your firm has a reasonably normal staff/partner ratio.
6. Average compensation for firm administrators: The problem here is the definition of the position “firm administrator.” Some firm administrators function at a partner level and are very handsomely paid. Other firm administrators, though hard-working and extremely valuable to their firms, simply don’t function at a partner level, and their compensation is much lower. We used to have a question in The Rosenberg Survey on this statistic. But when we dug down into the responses, we found that many firms responding to the question had a lower-level office manager on board instead of a high-level firm administrator. We never used the data because the results were misleading, and we discontinued the question.
7. Treating non-equity partners like “partners.” The problem here is in the definition. Many non-equity partners at the Top 100 firms out-perform and out-earn equity partners at much smaller firms. But most non-equity partners at firms below the Top 100 function and perform more like managers than equity partners. Treating non-equity partners the same as equity partners for such metrics as fees per partner and ratio of staff to partner will usually distort these computations. So, it is critical to treat non-equity partners as professional staff for purposes of computing “partner” ratios.
8. Computing income per partner: As accountants, we certainly understand the difference between the accrual and cash basis methods of accounting. But firms often ignore this distinction when computing income per partner (IPP), and that plays havoc with the results. There are two ways that firms commonly compute IPP for MAP Surveys. The first method starts with the firm’s accrual basis net income, before any compensation to partners, and divides that by the number of partners in the firm. The second method takes the actual cash paid to each partner, adds it up and computes IPP. I’m sure I don’t have to tell you that the first method is correct and the second method is incorrect. The problem with using the second method stems from two factors: First, firms often decide to retain some of their income for internal operations and capital expenditures and for cushion; these amounts need to be included in IPP. Second, the fluctuation from year to year in A/R and WIP produces cash earnings for the firm that differ, sometimes substantially, from net income in the income statement.
9. Average fees per professional: Again, the problem here is one of definition. What is a professional? At some firms, paraprofessionals perform work very similar to that of CPAs. At other firms, paraprofessionals are seen as clerical staff. For this reason, we don’t place much importance in “average fees per professional.” We prefer “fees per person.”
10. Computing the average charge hours for any category of personnel, such as partners and professional staff: There are two main issues. Most firms make the mistake of computing the number of FTEs by adding up their total work hours and dividing by 2,080. This causes firms to count people with more than 2,080 hours as more than one FTE, which should never happen. This practice understates the average. The only proper way to compute average annual charge hours for a personnel grouping is to include only personnel who were with the firm for a full year AND were full time the entire year. So, in computing the average, one needs to omit part-time personnel and personnel who began working at the firm after the year began or who left the firm before the year was concluded. Average annual charge hours cannot be annualized because of the skewing effect of the tax season.
If you do the math, making the incorrect computations above can distort the true metric by as much as 20% to 25%.