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Overhead rate is a poor measure of efficiency

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There is no financial metric more scrutinized in the not-for-profit world than overhead percentage. As a result I am always hesitant to write on the topic because any article on overhead tends to be perceived as one of two messages: “Overhead rates are too high, and not-for-profits are not to be trusted” or “Overheads don’t really mean anything, so stop trying to compare organizations and just give us money anyway”. The truth is that organizations should welcome comparisons to peers. Such comparisons allow donors to make wise decisions, which results in funds flowing to the best managed not-for-profits. But, is overhead the best measure of quality management?

 
I like to point out that the effectiveness (not efficiency) is usually a donor’s primary concern when giving. At least this is true for me. Of course I would like the organizations to which I give money to be both effective and efficient. However, if you made me choose, I’d rather an organization make an inefficient but real change, than operate efficiently but fail to make a substantive change with their programs. The problem is that effectiveness is difficult to measure and much harder to compare across organizations. How do you compare teaching a child to read, saving a forest, and preventing a disease through immunization? In which case does a dollar achieve the most good? And even more challenging; how do you compare program quality across these categories? Absent comparable effectiveness measurements, donors and not-for-profits turn to overhead as a measurement of quality management. Overhead doesn’t measure effectiveness, but at least it measures efficiency . . . or does it?

 
I am participating in a project to measure the efficiency of the finance function across many of our organization’s ministry national offices. To do so, we’ve defined some efficiency metrics which allow us to compare our offices. These metrics include items such as cost per paycheck generated, cost per invoice paid, cost per employee expense report, etc. The common theme in these efficiency ratios is that the cost is divided by the outcome achieved. This allows for meaningful comparisons across offices, and useful evaluations of potential process improvements.

 
In doing this work I was struck by how different an overhead rate is from the efficiency metrics we are using. Overhead is not the measurement of cost against an outcome (cost per life transformed, cost per tree saved, cost per beneficiary trained), rather it is a ratio between types of costs (percentage of costs which are general and administrative, as compared to costs which are directly related to programs). This ratio among costs fails to capture actual efficiency and can lead to some surprising results. Consider a food shelter that is able to replace hired food servers with volunteers. The food servers are directly related to program activities, thus when they were paid the costs were programmatic. Removing these program costs increases the shelter’s overhead ratio. This works in reverse as well. Imagine a charity finds three vendor bids for a product needed for distribution in its programs. The organization could reduce overhead by intentionally purchasing from the more expensive vendor.

 
Now, these examples may be a bit of a stretch. However, I think you see my point. The overhead ratio rewards inefficiency in program costs, which are the majority of most not-for-profits’ costs. I certainly do not believe organizations are intentionally choosing inefficient program costs to manipulate overhead. But, I think it is possible that the focus on overhead rates can blind management to potential efficiency gains in program costs. Ironically, if donors and managers have been focused for years on managing to a low overhead rate, many organizations may have already realized the big efficiency wins in management and general expenses. For these organizations improvements in overall efficiency may yield higher overhead rates.

 
The strongest advantage of overhead as a metric is that it can be used to compare different types of nonprofits. Hospitals, schools, conservation groups, and homeless shelters all can be compared on overhead rate. Unfortunately this strength breaks down on more detailed inspection. One of the more interesting things I have learned since I started working for a nonprofit is that overhead closely corresponds with the type of nonprofit organization (or at least their funding source). Organizations with a large GIK component to their ministry often have very low overhead rates due to the value of the goods they distribute. Child Sponsorship organizations tend to have higher overhead rates due to the additional administrative effort required to connect each sponsor and child. (There are arguably programmatic and stability advantages to this higher cost). Grant funded organizations tend to have overhead rates which fall in the middle. In other words, the type of donations received can have a bigger impact on overhead rate, than the quality of an organization’s management.

 
So, what should we be measuring? There is clearly need for comparisons among not-for-profits. There are also benefits from these comparisons both for donors and management. But there are clear flaws in overhead as the comparison tool of choice. I think it would be wise to evaluate similar types of not-for-profits based on a grouping by mission (for example Relief & Development, Conservation, Medical Research, etc.). For each grouping an efficiency measure could be determined by dividing total costs by a common outcome metric. For example, animal shelters could report costs per animal served. Then efficiency could be better gauged for similar organizations.

 
I also think that breadth of analysis can be a solution as well. Part of the problem with overhead is that it is often viewed as the defining, authoritative metric. If other metrics are considered as well (unrestricted undesignated net assets, growth rate adjusted for organizational size, liquidity, etc.) a more complete and useful comparison emerges.



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