Economies of Scale in
Health Insurance:
2026 Survey Results

Background on Economies of Scale and Cost Identification

While the largest costs for health plans are health benefits, not every employer group pays health plans to assume health benefit variance risk. Among Blue Cross Blue Shield Plans, about 47% of comprehensive members are fully insured compared to roughly 76% for Independent / Provider-Sponsored plans. By contrast, every member and every group pays health plans to assume responsibility for administrative activities of their health benefit programs.

“Administrative,” means all health plan costs other than payments to health care providers for care rendered to health plan members. Health insurance administrative costs include salaries, benefits, depreciation and amortization, leases of office space, advertising costs, consulting services, outsourced costs and so forth.

These natural accounting categories have limited value in describing and managing the costs of the activities that health plans perform because of differences in how organizations execute their activities. For instance, natural accounting categories may provide insight on the aggregate use of internal staff versus outsourced staff, but not what activities staff are engaged in. So, to capture the cost of the activities, the Sherlock Benchmarks ask that health plans report functional costs that often cut across natural accounting categories. So, health plan activities in the Sherlock Benchmarks are captured in functional costs such as Provider Services, Claims Adjudication, Corporate Services and Medical Management. These functional expenses implicitly include component natural costs of labor, depreciation, etc.

This report analyzes only two sorts of functional economies of scale, technical and administrative. A technical economy of scale arises from an investment in a capital-intensive process. Automation of claims adjudication activities is an example. A successful investment in auto-adjudication systems and electronic claims submission systems can yield a return through a decline in the end-to-end cost of processing and paying claims, and those savings may increase with volume. In other words, technical economies of scale entails reduced marginal costs stemming from overcoming the capitalized cost of original investment.

An example of administrative economies of scale is covering relatively fixed Finance and Accounting costs with greater volumes of members. If the cost of preparing and issuing financial statements is largely independent of the size of the organization, then the larger the organization, the more members there are, the lower the per member cost of those financial statements. Unlike technical economies of scale, it is not necessary to automate the process to achieve the lower costs.

This analysis does not measure other forms of economies of scale. For instance, this analysis does not quantify purchasing economies of scale in which high market share may increase the bargaining power of insurers versus providers.

Understanding economies of scale, and optimizing functional costs at a particular scale, is important because, while scale effects on administrative costs may be modest, they have an impact on activities integral to health plan operations. And while administrative costs are small relative to premiums, scale can impact the ability of the health plan to internally fund investments. Finally, if health care costs are cyclical, optimized administrative costs can amplify the effect of favorable health care trends on operating profits and can mute operating losses.

This report quantifies the effects of economies of scale and also illustrates scale’s scope and impact. This limitation means that many health plans of relatively modest size can achieve near administrative expense parity with their larger peers through effective execution, especially when combined with another attribute such as differentiation.

Method

This analysis is based on survey results of Blue Cross Blue Shield Plans and Independent / Provider-Sponsored health plans also used for the 2026 Sherlock Benchmarks. All data is for the 2025 calendar year and has undergone extensive validation procedures both by Sherlock Company and by the participating plans. Collectively, the 24 plans served 50.1 million Americans. The range of membership was from about 550,000 to more than 5 million among Blue Plans, and less than 100,000 to 1.4 million among IPS plans.

Economies of scale occur when unit costs decline as volume of enterprise output increases. Because the “output” of a health plan is health coverage service to its members, volume is defined as member months, which are reported by the plans. The costs that are the subject of this analysis are administrative, classified by function, described in the previous section. Each plan in the study reported its costs segmented into approximately 70-80 functions and sub-functions, depending on the universe, so that each of them may be analyzed individually. The unit costs in this analysis are the various administrative costs expressed Per Member Per Month (PMPM).

Any analysis of health plan economies of scale is complicated by the differences in the product mixes between the health plans. It costs much more to administer a comprehensive product sold to seniors than to people of working age since administrative activities are often related to the underlying health needs of the beneficiary: the older one is, the more health care one requires, and so the more claims processing costs are incurred by one’s insurer.

To overcome this and similar biases, each organization participating in the Sherlock Benchmarks reported each function’s costs segmented by product, such as Medicare Advantage and Commercial Insured. This makes it feasible to reweight each plan’s PMPM costs to eliminate the effects of product mix differences. So when comparing costs between organizations we express each plan’s PMPM expenses as differences from the mean universe values, after reweighting the universe values by each plan’s own product mix. Health plans with high cost values are expressed as greater than 100% of the mean at each plan’s product mix, while low values are less than 100%.

We measured economies of scale by regressing costs in each function (expressed as described above) against member months. A regression analysis fits a line through a scatter of each of the membership/cost points for each plan that minimizes the distance between those points and the line. Since technical or administrative economies of scale imply the existence of fixed and variable costs, where economies of scale exist, they plot as a curve. For ease and intuitive appeal, we converted the relationship to a straight line by calculating the regressions as the natural logs of the percent differences from mean values against the natural logs of the member months. (The use of natural logs requires positive values, so cost differences were expressed as percents of mean cost, as described in the previous paragraph.)

We considered the relationship between membership and costs to be significant if it displayed p-values of less than 0.1. A p-value is widely used to gauge the reliability of modeled relationships. Suppose a regression yields a 0.1 p-value: it can be interpreted as, “Assuming that there weren’t economies of scale, you’d obtain the observed difference in 10% of such studies due to random sampling error.” So, the lower the p-value, the more reliable the results.

Regression lines can have positive or negative slopes but, since economies of scale mean lower costs per member as membership increases, this discussion of the results is focused on negative slopes. The BCG (Boston Consulting Group) Slope is an intuitive way of expressing the slope of scale and it means the percent of the pre-doubling costs that the function will exhibit if the plan doubles in size. It is calculated as 2 to the power of the slope of the regression line.

Note that, where economies of scale exist, they are apparently not the only factor in cost differences. The R² describes the degree to which all the data points are found on the slope, and it is expressed as a percent. In other words, the predictive value of scale is that it explains R² percent of the differences between the points. It is unusual that the regression analyses have an R² that exceeds 50%. So, while scale plays an important role in those instances that we identify as significant, there are cost factors other than scale that may also help explain the differences between the plans’ function costs. For instance, each health plan’s information system investment cycle may also mute the relationship between costs and scale.

Figures 2-4 show the results of the regressions for each function in Blue Cross Blue Shield Plans, Independent / Provider-Sponsored Plans and the combination of both sets.

Blue Cross Blue Shield Results

Figure 2 shows the results of regression analyses of costs in each function and members for Blue Cross Blue Shield Plans. The 12 Plans included here range from about 550,000 to more than 5 million members.

Of Blue Cross Blue Shield administrative expenses, 41.5% are in functions that are significantly subject to economies of scale. From the regression lines, we estimate that a doubling of the size of these plans is associated with unit costs subject to scale that are 80.8% of their pre-doubling costs. This conclusion is based on trends that are weighted by the costs of each function. The Subtotal Expenses (all expenses less Miscellaneous Business Taxes) also displayed economies of scale with a BCG slope of 94.2%.

Of the 80 functions and sub-functions (including Sub-Total, Miscellaneous Business Taxes, and Total), 22, including Subtotal, exhibited economies of scale at a p-value of less than 0.1. These included Information Systems, Actuarial, and Corporate Services functions and are shaded blue.

There was one Blue Cross Blue Shield function with a p-value of less than 0.1 that exhibited diseconomies of scale. In other words, its slope displayed an increase in costs with an increase in scale. This function was BlueCard Home and Custom Par Fees. This is shaded lavender.

Independent / Provider-Sponsored Plan Results

Figure 3 shows the results of regression analyses of costs in each function and member months for Independent / Provider-Sponsored plans.

The 12 plans used for this analysis range from fewer than 100,000 to 1.4 million members. Of their administrative expense, 13.2% are in functions that exhibit economies of scale at a p-value of less than 0.1. A doubling of the size of these plans is calculated to lead to unit costs for those functions subject to economies of scale that are 77.2% of their pre-doubling value. Again, this is cost weighted. The slope of Subtotal expenses was not significant and its BCG slope was 96.8%.

For IPS plans, six functions or subfunctions displayed economies of scale, such as Other Claim and Encounter Capture and Adjudication, Other Applications Maintenance, Finance and Accounting, All Other Legal, among others. These are highlighted in blue. Three functions exhibited statistically significant diseconomies of scale, and they were Internal Sales Commissions, Payment Integrity and Benefit Configuration. These functions are highlighted in lavender.

Combined Universe Results

The Blue Cross Blue Shield and Independent / Provider-Sponsored universes reflect their respective origins and their operational philosophies and cultures. For instance, unlike the Blue Cross Blue Shield universe, half of the Independent / Provider-Sponsored Plans are owned by health systems. One possible reflection of this strategic difference is that, holding product mix equal, IPS plans seem to spend more on Medical Management, as Blue Cross Blue Shield plans spend more on information systems.

Figure 4 shows the results of regression analyses of unit costs for each function and members for the combined set of Blue Cross Blue Shield Plans and Independent / Provider-Sponsored Plans. The combined universe has a larger sample size than each of the universes individually, and the range of plan size was greater.

The 24 plans included here range from fewer than 100,000 members to over 5 million members. Of their administrative expenses, 33.0% are subject to economies of scale. A doubling of the size of these plans is calculated to lead to those costs subject to economies of scale falling to 88.8% of their pre-doubling value. Again, these calculations reflect a weighting by their costs. The Subtotal Expenses also displayed economies of scale with a BCG slope of 96.1%.

Of the approximately 70 total functions and sub-functions for the combined universe, 13 displayed economies of scale, which includes subtotal. Some of these functions include Sales, Information Systems, Finance and Accounting and Actuarial, shown in Figure 4. The areas with statistically significant diseconomies of scale were Claim and Encounter Capture and Adjudication and Outside Litigation. (Miscellaneous Business Taxes also displayed a statistically significant diseconomy of scale, but it is not included in this count because it is not part of Subtotal Expenses.)

Application

Understanding economies of scale can be helpful in situations in which it is necessary to estimate the cost structure of a health plan that is experiencing growth. Organic growth and acquisitions are two business situations in which such an analysis would apply.

Figure 5 illustrates how the values calculated in the combined universe case (Figure 4) would impact costs. This illustrates the case where a firm exactly doubles in size through an acquisition.

Recall that, for the Combined set of Blue Cross Blue Shield and Independent / Provider-Sponsored plans, the BCG Slope was 88.8% for the 33.0% of administrative costs that are subject to economies of scale. Expenses subject to economies of scale are 3.7 percentage points of the 11.2% total and are $22.11 of the $67.00 PMPM total. (This is similar to typical costs of commercially insured members.)

The effect of scale is calculated as the scale slope of 88.8% times the pre-doubling 3.7 percentage points represented by expenses subject to scale, or 3.3%. (The $600 PMPM is in line with premium revenues for commercial insured products.) This reduces the $22.11 PMPM in expenses subject to scale to $19.64 or by $2.47. That value times 2 million members, times twelve months models savings of $59 million on a combined administrative expense of about $1.6 billion or by 3.7% on a PMPM basis.

While the savings are modest in the context of the combined administrative expenses, the percent impact on combined operating profits is much greater. The increase from $120 million to $179 million is 49.5%.

While the BCG Slope is an intuitive way of expressing economies of scale, doubling the size of the firm is a special case. So, to calculate all possible alternatives, the BCG Slope must be converted to a marginal scale effect. The marginal scale effect is the BCG Slope adapted for the size of the smaller plan (“Target”) relative to the larger plan (“Suitor”). We show its calculation in Figure 6.

Suppose a health plan increases its membership by 50%, rather than doubling. This could occur if a one million member plan was to acquire a 500,000 member plan. (For simplicity, we ignore the implications of scale on baseline expenses of the smaller plan.) The 79.8% marginal scale effect is the BCG Slope adapted for this 50% increase in membership. The steps for converting a BCG Slope to a marginal scale effect are described on the left side of Figure 6, and the right side applies them to the combined 88.8% BCG Slope as an example.

Incidentally, the use of the marginal scale approach can also be applied to the Figure 5 case of the combination of two similarly sized organizations. The steps used in Figure 6 yield a marginal scale effect of 77.6% which, when applied to the $265 million in the Target’s scalable administration (rather than the combined companies), produces the same $59 million savings as found in Figure 5.

Click to enlarge

Note: The 79.8% marginal scale effect shown in Figure 6 and used in Figure 7 is built up function by function. These steps are applied to each function’s BCG Slope from the regressions, and the results are weighted by each function’s share of costs subject to scale. Working the example’s steps by hand from the overall 88.8% BCG Slope gives 79.9%. The two differ slightly because combining the functions before the calculation gives a slightly different result than combining them after.

In Figure 7 we apply this marginal scale value to estimate the effect of economies of scale on a business combination where the Target is one-half the size of the suitor. To calculate the scale-related savings, we multiply the calculated marginal scale effect of 79.8% (see Figure 6) by $133 million in the Target’s expenses that are subject to scale. This reduces those expenses to $106 million and yields an estimated effect of scale on the target plan of $26.8 million.

Again, the percent effect on earnings is greater than that on costs. While scale reduces the Target’s administrative expenses by 6.7% from $402 million to $375 million, its operating profits increase by 89.2% from $30 million to $57 million.

Once the framework for the marginal scalar effect is established, then it can be universally applied to any scale scenario. An estimate of the effect of economies of scale in this way can be helpful as an initial approximation or as a default assumption when more in-depth analysis is not feasible. Since each organization has its own unique cost structure and the slopes of the economies of scale vary by function, it would be more appropriate to apply each of the scale slopes to each functional area. While this greater granularity hones the estimate, due diligence will likely further modify that estimate.

Other Observations

Diseconomies of Scale. In the Blue Cross Blue Shield set, there was one function that saw costs increase with scale. For IPS plans, three functions exhibited diseconomies of scale. The combined set had two functions with diseconomies of scale. We do not know why certain costs tended to increase with membership but it is possible that they reflect strategic investments in growth, membership retention and challenges associated with higher market share.

Qualifications. This study analyzes the experience of firms of various sizes to estimate scale, and its intent is to provide information to health plans as they consider their individual strategic situations. One qualification to the results is that each firm operates differently and in different competitive environments so that differences between firms that we attribute to scale may also stem from other factors. For instance, larger organizations may operate in service areas that have competitive environments that affect costs independently of the technical and administrative economies of scale.

Also, the size of the organizations may establish the bounds for which the conclusions are reliable. For instance, we suspect that organizations smaller than plans reflected here would enjoy steeper declines in PMPM costs as they grow. This is consistent with our earlier remark that the presence of fixed and variable costs in a function implies that economies of scale would resemble a curve.

Finally, in our measurement of economies of scale we focused on differences in actual scale as a point in time, that is, a cross-sectional analysis. Because strategic decisions are long term, we elected not to employ a short duration time-series analysis.

Closing Thoughts

We sometimes face skepticism concerning our conclusions of limited economies of scale. Many other industries such as manufacturing, transportation and farming are known to enjoy these economies. In the health care sector of the economy, hospitals, like hotels, also exhibit economies of scale which is why occupancy rates are an indicator of profitability in both sectors.

An intuitive way of considering economies of scale is to consider the actual activities of health plans and how they are executed. Many of the activities that health plans perform grow with membership, such as responding to customer service inquiries, processing manual claims and processing manual enrollment transactions. When a plan adds a new member, he or she requires the same services as all previous members. Other functions may also be linked to volume, though more loosely, like the Provider Network Management and Services and Information Systems functions. Even the few areas that appear fixed can increase with the size of the plan. While Corporate Executive and Governance would be expected to be relatively fixed, the numbers of support staff, compensation and the enterprise-wide consulting usually grouped in that function can increase in larger organizations.

Moreover, the technical economies of scale, such as those discussed at the beginning of this analysis, may at the same time give rise to higher costs that partially offset the advantage. Suppose the investment in claims autoadjudication achieves its objective of reducing the need to process claims manually, thereby allowing for the redeployment of the staff that performed it. This change will nevertheless not entirely eliminate claims processors. In fact, a countervailing effect may be that the claims beyond the capability of the autoadjudication system are more complex, and therefore require greater effort and knowledge than the average claim. This more complex claim adjudication could require the expertise of claims people who are higher level and better paid, which could offset the advantage of reduced staffing. This paradox may occur in many activities that health plans increasingly automate.

Another intuitive way of thinking about economies of scale is to compare costs across the actual industry structure. Consider the vast size differences between organizations providing health coverage. They range from UnitedHealth, at about 50 million members and almost $448 billion in annual revenues in 2025, to organizations that serve only tens of thousands of members. UnitedHealth’s administrative expenses appeared slightly lower than those of Blue Cross Blue Shield Plans in calendar 2024, the most recent year of our public company analysis. In reaching this conclusion, we excluded the effect of differences in the mix of comprehensive products, excluded products such as Stand-Alone Part D as well as Optum service operations and added our estimate of UnitedHealth’s medical management expenses to administration from health benefits. UnitedHealth and these smaller companies coexist in a low margin competitive market: the fact of numerous competitors of a wide range in size argues against overstating the significance of advantages stemming from scale.

Application of Economies of Scale to Your Health Plan’s Administrative Costs

We have an interactive Economies of Scale Model on our website that reflects the content of this study. It enables users to estimate how changes in membership size affect each cluster of expenses.

To use the model, first populate the percent difference between your current membership and your estimate of membership in the long term. Then enter the PMPM cost for any cluster or total value for which you wish to estimate the effect of that difference in size. The cost value after the effect of the difference in scale will be shown. Expense estimates may be calculated in total or by clusters of functions: Sales and Marketing, Medical and Provider Management, Account and Membership Administration, and Corporate Services.