Stephen T’s Blog Spot

In a previous post I argued that effectiveness is only half the question, and that a program can work and still be a poor use of money. That raises the obvious follow-up: how do you actually build a cost-effectiveness case that will survive scrutiny? The good news is that most of it is not exotic math. It is disciplined bookkeeping and honesty about assumptions. Here are the steps that matter.

1. Fix the perspective first. Decide whose costs and benefits count: the funding agency alone, or society more broadly? This single choice governs the entire ledger, because participant time, volunteer labor, and costs pushed onto other systems are in or out depending on it. Most arguments about a cost-effectiveness result are really arguments about perspective, so state yours plainly and up front.

2. Choose the comparator honestly. The result is incremental, so it depends entirely on the alternative you measure against. Compare the program to the realistic next-best option, not to doing nothing and not to a straw man. The comparator often decides the verdict, which is exactly why it deserves to be chosen in the open rather than chosen to flatter the program.

3. Count all the costs, not just the visible ones. The program budget is not the cost. List every resource the program actually consumes, staff, space, and materials, and then the easily forgotten ones: participants’ time, donated facilities, administrative burden, and costs shifted onto other agencies. Value each at what it would otherwise be worth. This ingredients approach is tedious, and it is where most weak analyses fall apart.

4. Put future costs and benefits in present-value terms. A dollar spent or a benefit received years from now is not worth the same as one today, so you discount future flows back to the present. This matters most for programs whose payoffs arrive late, such as prevention or early education, because the discount rate quietly shrinks distant benefits. For federal work the rate is not yours to invent: OMB Circular A-94, revised in 2023, sets the discount rates, tied to Treasury rates and updated annually. Use the prescribed rate and state it.

5. Express the result as an incremental ratio, and compare it to something. Report the extra cost per additional unit of outcome relative to your comparator, then set it against a meaningful benchmark: a threshold, a competing program, or the other uses bidding for the same money. A ratio floating on its own is not yet a decision. The point of the number is the comparison.

6. Stress-test every load-bearing assumption. The result rests on uncertain inputs, the effect size, the unit costs, the discount rate, and how long the benefits last. Vary them and watch what happens. One-way sensitivity analysis moves one input at a time; a probabilistic version varies them together to show how often the program still comes out ahead. If the conclusion flips under plausible values, that is the finding, and you report it.

Notice that none of these steps is really about arithmetic. They are about candor: declaring the perspective, choosing a fair comparator, counting the costs no one likes to count, discounting honestly, and showing the assumptions rather than burying them. A cost-effectiveness case earns its authority the same way any good analysis does, by making every consequential choice visible enough for a skeptical reader to check. The last step in particular is the same discipline this series has returned to before. A result you have not stress-tested is a result you do not yet understand.

So here is my question. When you make a value-for-money case, do you declare your perspective and comparator and show how the answer moves as the assumptions change, or does a single tidy ratio carry the whole argument?