One of the central issues in economics is what ensures that scares resources will not be wasted in creating goods and services. What ensures efficiency? There are two subordinate questions: (1) How do we measure it? And (2) What can society do to make sure there is no waste?
This is not unrelated to the issue of how we ensure that societies resources are spent making the things that people value the most. Together, the idea of no waste (which is called “efficiency”) and producing the most wanted things (which could be called “allocative efficiency”) determine the “value” of those things we produce and the value of the resources that go into producing them. In a market system, these “values” are prices set via supply and demand, and the dynamic forces of competition between suppliers and free entry and exit of suppliers who are chasing profits. To reiterate, in a health sector context, there are two kinds of efficiency.
Technical efficiency- Producing outputs at minimum costs – this is about how things are produced
- Do we assign the right number of workers to our clinic to ensure they are fully utilized?
- Do we have the right mix of nurses and other staff, so nurses do not do things that staff that are paid less could do?
Allocative Efficiency– Producing the right outputs meet organizational objectives – what is the mix of things are produced? Are we allocating (eg budgeting) resources properly across activities in the firm— could we get more yield (or profit) if we reallocated the mix of activities or products?
- Do we spend enough on prevention as contrasted with curative care ?
- Do we spend too much on a few high cost patients who get very little health gain?
Efficiency means “no waste”. What that means is the in the production process, the input output relationship (called the production function) defines the maximum output that can be produced for any level of input (or, if you prefer, the corollary, the minimum input level that can produce any particular level of output). In the chart below,
Costs, which are described more below, are a product of three things— (1) the technical input-output engineering possibilities involved in making the product or service, often described by a production function, (2) the price that the firm pays for the inputs, and (3) the choices the firm makes in properly choosing the mix of inputs to produce the level of output they choose. We return to costs below.
Technical Input-Output Relationships
Productivity is output per unit input. It is a technical, or engineering-like concept. It is depicted as a production function, which describes the possibilities for generating various output levels by expending more or less resources (see below).
On the production function points below the line are achievable, but is not very efficient, because we could produce a higher level of output (on the production function) with the same expenditure on inputs. Points above the line are not feasible with existing know how. Productivity (output per unit input) is often used as a metric for understanding whether the economy or an industry like health is getting more from its scarce resources, or not. Productivity growth is highly valued.
The level of technical progress changes, and this effects the shape of the production function. When the computer comes along, for example, and allows auto-control of production, for example, it allows the firm to produce more with less, and the experience is called “an improvement in efficiency”.
On the production function such an improvement causes the production function to shift up. Producing more with the same inputs as before, and making the *** points feasible. Progress is experienced in improved productivity in many ways: innovative products (the cotton gin, inventing/discovering penicillin, know how in terms of starting a fire, or inventing hybrid disease resistant seeds). Investments in physical capital (FC on the chart) will increase the productivity of variable inputs like labor.
Investments in human capital will do the same thing, shifting productivity to higher levels for the same level of hours worked. (Human capital is skill level, know how, and of course formal education). Health status is also a form of human capital, as is education, marriage, worker migration to find better “fit” with the economy. Better management capabilities or finding more effective way to run an operation is also an important area of human capital investment. Organizations choose to invest in a variety of forms of physical and human capital. Both tend to reduce the need for variable resources in order to achieve the same output level (eg they reduce the variable costs per unit) and improve contribution margin. They may, of course, often be considered added fixed costs (as all capital investments are considered fixed costs).
Generally, the adoption of improved capital of whatever form, the whole optimum for the organization changes. The optimum level of output may change (the optimum sized facility (output level with the lowest cost) will change, the relative value of certain kinds of employees will change, as will their salaries, and some resources, possibly even important ones in the past, will forever be shed. Progress isn’t best seen as layering new capabilities onto old ones. Think of it as a massively deep reorganization of everything. It always get spread over time, often as a result of managerial lags in discovering the full implications of the technological progress at work.
The production possibilities above the line, shown by the *, are impossible to achieve. For a given level of variable input, we just cannot produce these high output levels. The output levels shown by the + are possible. Here we could produce less output than is possible. We do this all the time, and it is called “technical or productive inefficiency”; producing less than might be possible with the resources we are using. When organizations operate in this region (+++) the have costs of production that exceed the minimum possible.
Why can this happen? Obvious answers are that they are ignorant, or their managers and systems can’t deliver it, or they pay too much for resources, or whatever. From economics, however, the answer is different. This happens because nobody is forcing them to do better. That is, we observe persisting inefficiency only when markets and competitive pressures are absent.
When does this happen? When the organization has monopoly power, for whatever reason. Maybe government protects them (patent, licensing, or a highly regulated industry) or there are other barriers for competitors to enter the market and force them to be more efficient in order to survive. Or maybe consumers are not effective shoppers for best value. This can happen when they can’t assess value as they shop (asymmetric information) or when they don’t pay the full price (like when they have insurance).
So efficiency is a technical thing, relating to inputs and outputs. Generally, we would expect any organization to prefer to be efficient. Why? Because regardless of their degree of competition they can produce more profit if they are efficient. But, external pressures to be efficient can also be present when the organization faces competitive pressures that customers will flee unless they set the lowest possible price. This external pressure is sometimes present, sometimes not.
When markets don’t work well, or when organizations don’t care, it is hard to force organizations to be efficient (to produce at the minimum cost). We see that in health care a lot.
Market Advantages of Being Efficient
When firms are more efficient than others in an industry it provides enormous leverage for them. They may gain the following:
- Ability to price at the same level of the competitors, but make higher margins
- Ability to gain market share by pricing below the competitors, and drive them away
- Relative to competitors, ability to self fund activities like loyalty and share building promotional campaigns, R&D on new products, and better service
- Relative to competitors, long term security regarding sustainability in the industry
These are enormous advantages, and firms routinely examine the efficiency with which they operate with an eye to making improvements in efficiency.
Allocative Efficiency
Given scarce resources, this means producing the combination of products that yields the greatest level of overall output (welfare). Generally we might illustrate this with a “production possibility curve or a schedule as shown below. The multiproduct firm has this issue, the society trying to decide how much of each product and service to produce has this problem, the person trying to decide how to balance work, home and school has this problem.
This semester you are trying to decide how to allocate your time between family (F), school (S) and extra effort for work (W). You figure you are committed to work 40 hours a week for sure, to sleep 50 hours a week, have 14 hours a week personal time, and to spend 12 hours a week commuting. You also think you must devote a minimum of 20 hours a week for “family time”, and 15 hours a week to school. So, of the 168 hours a week, you have only 17 hours a week discretionary time left. How best to allocate this time is the problem. The following data show how you think about the value of time spent doing each of the three activities in question;
F S W
Total “benefits” of spending 1 extra hour a week on
20 7 12
Total “benefits” of spending 2 extra hours a week on
30 11 17
Total “benefits” of spending 3 extra hours a week on
38 14 21
Total “benefits” of spending 4 extra hours a week on
44 16 24
Total “benefits” of spending 5 extra hours a week on 49 17 26
Total “benefits” of spending 6 extra hours a week on
53 18 27
Total “benefits” of spending 7 extra hours a week on
56 19 28
Total “benefits” of spending 8 extra hours a week on 58 19 29
Total “benefits” of spending 9 extra hours a week on
59 19 29
In this simple example we are trying to solve an allocation problem. Three streams of activity are presented, with a scarce resource to be allocated. The “best” or “benefit maximizing” way to allocate 17 hours of time is to spend 8 hours on family, 4 hours on school, and 5 hours on work. At this point we achieve maximum total benefits from the resource we are allocating. The way we do it, by deciding where best to spend the first hour, then the second, then the third and so forth, is essentially equating the ratio across activities.
For an economy, we would maximize benefits by allocating resources across products the same way. But it would be more complex. The principle is the same: Allocate resources to products and services so that the we achieve production levels for each output such that ratio of incremental benefits (to consumers) to incremental cost for all products are equal. So, if we have a product for which the output level is such that marginal benefits/marginal costs is higher than others, then society would be able to adjust the output levels are arrive at a higher level of net benefits. Specifically, to produce more of this product, and drive down the ratio of incremental benefits to costs until it is equal to all other products. And services.
Measurement of Efficiency
Industrial engineering is the field that concerns itself with efficient design of operations. Even as “lean” and “Six sigma” creep into service businesses, these are products of industrial engineering activity done in manufacturing to hone the production process to make it continuously searching for the most efficient way to do things. Trying to find the location of the production function, trying to move from the +++’s to the production function itself.
In manufacturing, efficiency is easier to analyze than in service businesses like hospitals. Mainly the problem in service businesses is:
- Identifying and measuring the “output”
- The fact that service producers usually make multiple kinds of outputs
- And, finding ways of adjusting costs across multiple outputs for the for resource costs associated with producing them (eg adjusting for severity or casemix).
Service businesses are often characterized by “professional” standards (sometimes licenses) for the key labor categories. This is one way of dealing with the fact that multiple products are produced, and that we need some way to make sure that we deliver the right product to the client. When you have one product the whole thing is much easier. So for lawyers, accountants, doctors and nurses, pilots, even civil engineers, and others— we have created ways of making sure that organizations have information on who is able to make the right services, and who is not.
In health care, the growth of the industry has sought ways to define the output(s), because that is key to understanding how one might measure and control efficiency, and to control and improve quality, A local doctor started all this in 1913:
“ Really the whole hospital problem rests on one question: What happens to the cases? [. . .] We must formulate some method of hospital report showingas nearly as possible what are the results of the treatment obtained atdifferent institutions. This report must be made out and published by eachhospital in a uniform manner, so that comparison will be possible. With such a report as a starting-point, those interested can begin to ask questionas to management and efficiency”.
Dr Eugene Codman, Address to the Philadelphia County Medical Society, 1913
It took until about 1970, and the cost increases associated with Medicare/Medicaid, before Robert Fetter at Yale actually began to look into this issue seriously. His team eventually produced output measures in the form of 383 different hospital inpatient products. The Diagnosis Related Groups (DRGs) got picked up by the Congress and the Federal government and made into a set of 383 prices to use to pay for Medicare covered hospital care. And, the DRGs, having been refined a number of times since then, are used to measure output of hospitals in order to not only pay, but to: measure efficiency, measure outcomes, and to allocate budgets across facilities. They encouraged similar kinds of output measures to be developed for other kinds of health care businesses (home health, nursing homes, and even physicians).
Costs and curves
Costs are the expenses we incur as a supplier of goods or services. Keeping costs at a minimum is the life’s blood of business— if we cannot keep costs at or below the level of our competitors, we may well not survive. Keeping costs down is one of the key managerial responsibilities, along with finding a steady stream of customers who are loyal to our product or services, and keeping the power of government on our side.
Costs, in theory, are either fixed or variable. What economists mean by this distinction is that FC are costs associated with the servicing of long term illiquid assets (building, debt service costs, machinery, office equipment, etc.) and the costs associated with salaried workers, who cannot easily be ‘let go’ just because volume projections or the operations plan are not being met. Variable costs are those costs associated with selling more goods, or less goods. We usually think of elements of costs that are easily adjusted down if we aren’t selling as much as we had hoped, or can be adjusted upward if we ramp up production levels. Things like hourly worker hours, power costs, supplies, raw materials, sales commissions. This is theory. In reality there isn’t a bright line between cost elements—within an operating period some costs are very variable, some very fixed, and some that are somewhat fixed. But, the theory is useful in supporting observed behavior and influence of economic forces, even though somewhat simplistic assumptions are used.
Fixed costs are invariant to output. They are a fixed amount, and must be paid regardless of output. While to total is fixed, if we compute average fixed costs (by dividing FC by Q) we see that AFC fall continuously. The more we produce, the lower is the average fixed cost.
Variable costs are more interesting, and are responsible for the shape of the cost schedules, or curves. The total variable costs rise with output, by not at a uniform rate. Variable costs reflect the production function’s shape: the marginal productivity of the variable factors of production (in the face of a rigid set of fixed factors, like plant size and fixed equipment). So, we observe that total variable costs rise as volumes increase, but then rise at a higher and higher rate with respect to output as a result of diminishing returns to the variable factors of production. The main panels of the accompanying chart show the relationship of the production functions shape and the total variable costs. The small panel on the left translates this to the shape of the unit variable cost curve (the average variable cost curve). The U shape is the result of increasing return to the variable factor of production (on the left side) and the diminishing returns to the variable factors (on the right side). see the figure below
The total costs are the sum of variable and fixed costs. The average total costs the total costs divided by the number of units. Looking across possible volume levels the average costs (ATC, AVC) are U shaped, because of increasing and then diminishing returns — a feature that stems from the shape of the production function (the technical relationship between inputs and outputs). The AFC is not u shaped, since it is a fixed amount, divided by volume levels. Fixed costs are “spread” across more and more volume—so the AFC gets lower and lower as volume increases. When we plot ATC, AVC and AFC together on the same graph, the distance between ATC and AVC is the AFC. See the second figure.
The supply behavior (decisions to supply or not, and how much) of firms is governed by variable costs (AVC and MC). MC is the change in TC when volume increases by one unit. For those with calculus, the MC is the first derivative of the TC. There are three rules about supply:
- firms will shut down (not produce anything) unless price is higher than AVC. This is the same thing as saying that unless contribution margin is +, firms will not sell.
- The firm will always optimize financially (eg profit maximizes) when they sell the quantity of goods indicated by the point where P=MC. The only exception is when the firm has monopoly power (a downsloping demand curve) when they will sell the quantity where MR=MC.
- In cases where the price exceeds MC, there will be an incentive to sell more
Long run costs
The LR is a planning concept. It asks, what can the firm look like if we consider options for size, organization, product, etc. There are no rigid fixed costs in the LR, since everything is variable. There is no diminishing returns as a result. If, the firm doesn’t believe that price will cover its ATC in the long run, then it will not go forward.
There are factors that will tend to make the LR ATC curve U shaped. As we consider larger and larger scales of operation for our firm, we imagine that average costs will fall with size. These “economies of scale” arise because with size, come opportunities for lowering our costs. More leverage over supplies to get lower prices, more leverage over clients and customers which might cut the costs associated with “customer service”. We can also expect more power to set lower wages for our workers. And with size might come advantages in marketing and distribution of our products. These things help cut our average cost.
But with increased size come counterveiling forces that ten to increase average costs. These are inefficiencies associated with management control problems. How do we keep the organization lean and mean as it gets very large. Is management able to get the maximum productivity out of all workers, is it possible to train enough competent managers to staff the growing organization, can we keep getting top technical people for key jobs, when our demand for them is 10X or 100X as bog as when we were smaller? These kinds of “growth” and “bureaucratic” problems contribute to increasing average costs. So, as we grow, there are factors tending to reduce costs. And, at the same time, as we grow, there are other factors tending to increase costs. Generally speaking, the initial growth of the firm features the economies of scale outweighing the diseconomies of scale. As the firm grows even more, eventually the diseconomies of scale outweigh the economies.
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