Outcome-First Projects by the Numbers
Chapter 2 of 10 · 11 min read
Ends, means and the value at stake
Sort the laundry's aims into fundamental and means objectives, place the new plant as one means, and value the hospital contract at about A$1.41m a year of contribution.
Chapter 1 restated a request for new plant as an outcome: keep the hospital contract through a tender at a lower price, shown in four measures. This chapter asks two further questions before any option is considered. The first is how the owners’ aims fit together: which of them matter for their own sake, which matter only because they lead to something else, and where the requested plant sits among them. The second is how much the central aim is worth in dollars, because that number sets the scale for every option, every target and every argument about cost that follows.
The chapter builds an objectives hierarchy for the laundry, values the hospital contract as the contribution the business would lose without it, shows what the expected price cut does to the margin on its own, separates objectives from constraints, and ends with a project goal that treated a means as an end.
Values before alternatives
Ralph Keeney, in Value-Focused Thinking (1992), observed that most decisions are framed by the alternatives that happen to be on the table. A vendor proposes a machine, and the decision becomes whether to buy it, which model, and at what price. Keeney called this alternative-focused thinking and argued for reversing the order: first set out what the decision maker values, then create alternatives designed to achieve it. Values are what a business cares about; alternatives are only the means to get there. Starting with values tends to produce better alternatives, because it reveals options that nobody had thought to propose, and it gives a consistent basis for judging the ones that were proposed.
The owners’ request is a clear case of alternative-focused thinking. Tunnel washers were being sold to laundries like theirs, competitors had installed them, and so the question in the family’s minds became which tunnel and how soon. Value-focused thinking asks first what the family wants the business to be and do over the next several years, and only then which changes would serve that best.
Fundamental and means objectives
Keeney distinguishes fundamental objectives, the ends the decision maker values for their own sake in the decision at hand, from means objectives, which matter because they help achieve the fundamental ones. The distinction depends on the decision context. For a family business, keeping a particular contract is in the end a means to staying in business, but in a decision made because that contract is at risk, it is reasonable to treat it as fundamental: every option will be judged first on whether it keeps the contract.
This is an illustration. After two meetings with the owners, the operations manager and the finance manager, the laundry’s objectives settled into three levels.
Fundamental objectives, in this decision:
- Stay profitable and independent as a family business.
- Keep the hospital contract through the month-12 tender.
- Grow the hotel and serviced-apartment work, which pays better per kilogram.
Means objectives, the four measures from Chapter 1:
- Deliver on time and in full (OTIF) at or above what the hospital group requires.
- Keep the cost per clean kilogram low enough to hold a margin at the new price.
- Use few enough litres of water per clean kilogram to score well in the tender.
- Use few enough megajoules of energy per clean kilogram to score well in the tender.
Lower means, each a possible way of moving one or more of the means objectives: more effective ironing capacity on peak days, reliable dispatch and loading, enough washing capacity, arrangements with customers about when soiled linen is collected, and the new plant.
Placed in that structure, the new plant is a lower means. It is one way of providing washing capacity, which is one way of supporting OTIF, cost, water and energy, which in turn serve the contract and the business. There is nothing wrong with a means. The error is to mistake one for the end and to stop looking for others.
- Stay profitable and independent as a family businessfundamental
- Keep the hospital contractfundamental in this decision; 55% of volume
- OTIF at or above the tender requirementmeans objective
- Enough effective ironing capacity on peak dayslower means
- Reliable dispatch and loadinglower means
- Agreed collection times for soiled linenlower means
- Enough washing capacitylower means
- New plant: tunnel washer, dryers, extensionone possible means
- Cost per clean kg that holds the margin at the new pricemeans objective
- Water and energy per clean kg that score wellmeans objectives
- OTIF at or above the tender requirementmeans objective
- Grow hotel and serviced-apartment workfundamental
- Keep the hospital contractfundamental in this decision; 55% of volume
Asking why and how
Two questions move around the hierarchy. Asking “why does that matter?” of any objective moves up; asking “how?” moves down. Keeney uses the first to test whether an objective is fundamental: if the honest answer to “why does that matter?” is another objective, the first one is a means. When the answer is “because it is what we want”, the top has been reached.
Applied to the request, the ladder runs like this. A new plant matters because it would wash more linen, faster. That matters because linen must be ready in time for delivery. That matters because the hospital group will require 98% of deliveries on time and in full. That matters because without it the contract is lost. That matters because without the contract the business is not viable in its present form. The last answer is the end. Every rung below it is a means.
Going back down with “how?” opens the alternatives that the request hid. How can the laundry get deliveries out on time? By ironing faster on peak days, by loading and routing vans better, by agreeing when customers release soiled linen, and by washing faster. The request named only the last. How can it cut cost per kilogram? By labour productivity in feeding and folding at the ironers, the largest single block of labour, as well as in the wash room. The questions are simple; their value is that they are asked deliberately, in order, before anyone falls in love with an answer.
The value at stake
The hospital contract is the fundamental objective at risk, so its value is the natural yardstick. It is tempting to quote the contract’s revenue, but revenue overstates what would be lost, because some costs would go with the volume. The right measure is contribution: revenue less the costs that vary with volume.
All amounts are Australian dollars excluding GST. At the expected tender price of A$1.76/kg, the hospital group’s 1,716,000 kg a year would bring in A$3,020,160. The finance manager estimated which of the laundry’s A$5,337,704 of annual cost would fall if that volume went:
- utilities, all variable: gas A$445,536, electricity A$210,600, water and trade waste A$222,768, together A$878,904;
- chemicals, all variable: A$202,800;
- labour, 60% variable, because rosters could be cut but supervision, maintenance, administration and minimum crewing could not: A$1,713,600 of A$2,856,000;
- vehicles, 50% variable, because runs could be cut but the fleet and its fixed costs would mostly remain: A$130,000 of A$260,000.
The variable costs total A$2,925,304 a year on 3,120,000 kg, or A$0.9376/kg. Each hospital kilogram therefore contributes 1.76 − 0.9376 = A$0.8224 to fixed costs and profit, and the contract contributes 1,716,000 × 0.8224, about A$1.41 million a year. Calculated without rounding the variable cost per kilogram, the figure is A$1,411,243; with the rounded A$0.8224/kg it is A$1,411,238, and the difference is only rounding.
The fixed costs, A$2,412,400 a year, would remain. Spread over the hotels’ 1,404,000 kg alone, they would lift the cost per kilogram to 2,412,400 ÷ 1,404,000 + 0.9376 = A$2.656/kg, against a hotel price of A$2.05. On the same cost assumptions, the business would move from a profit to a loss of about A$850,600 a year. That is what “keep the hospital contract” means in numbers: not a growth opportunity but the difference between a viable business and one that must shrink sharply or close.
If the contract would otherwise run for five more years, the present value of the contribution at risk, discounted at the 8% a year this book uses for the cost of capital, is A$5,634,683, about A$5.63 million. That is a sense of scale, not a budget: it says that keeping the contract is worth a great deal, and also that spending A$6.12 million to keep it would need a very good reason.
The estimate rests on judgements, chiefly the 60% of labour treated as variable. If only half of labour varied, the variable cost would fall and the contribution at risk would rise; if more varied, it would fall. The point of the number is its order of magnitude, which no reasonable judgement changes: the contract is worth more than a million dollars a year to the business. Scenarios, sensitivity and switching values in Demand and Benefit Forecasts by the Numbers shows how to test a benefit estimate like this one against its assumptions and find the value at which a decision would change.
What the price change does on its own
Winning the tender is not the same as standing still. The expected price falls from A$1.85 to A$1.76/kg, 4.9% less, and that alone moves the margin.
| Today, A$1.85/kg | Tender won at A$1.76/kg | Contract lost | |
|---|---|---|---|
| Hospital revenue | A$3,174,600 | A$3,020,160 | nil |
| Hotel revenue | A$2,878,200 | A$2,878,200 | A$2,878,200 |
| Total revenue | A$6,052,800 | A$5,898,360 | A$2,878,200 |
| Total cost | A$5,337,704 | A$5,337,704 | A$3,728,787 |
| Profit before tax | A$715,096 | A$560,656 | −A$850,587 |
| Margin on revenue | 11.8% | 9.5% | −29.6% |
The middle column is the one to study. If the laundry wins the tender and changes nothing else, revenue falls by A$154,440 a year and the margin falls from 11.8% to 9.5%. The owners’ aim is to stay profitable, not merely to stay open, so the price cut turns cost per kilogram from a nice-to-have into a means objective with a hard edge. Chapter 5 derives the cost target from exactly this arithmetic: the cost per kilogram at which the business keeps its present margin at the new price.
The comparison also shows why the four means objectives cannot be traded freely against each other. An option that lifts OTIF to 98% but raises cost per kilogram may win the tender and still fail the first fundamental objective. An option that cuts cost but leaves OTIF at 91.2% fails the second. Only an option that clears all four is acceptable, and Chapter 5 says by how much.
Constraints are not objectives
Some requirements are not things to maximise or trade but limits every option must respect. For a laundry that handles hospital linen, the main ones are hygiene and safety. AS 4146:2024 Laundry practice, published in December 2024 and superseding AS/NZS 4146:2000, covers the handling, laundering, transport and storage of clean and soiled textiles in commercial, industrial, hospital, institutional and other laundries. Work health and safety law applies to every change to plant, shifts and loading. The trade-waste arrangements with the local water utility apply to anything that changes what goes down the drain.
These belong in the hierarchy as constraints, not as objectives. The difference is practical. An objective can be traded: a little more cost for a lot more OTIF may be a good bargain. A constraint cannot: an option that saved water by compromising disinfection would not be a cheaper option, it would be an infeasible one. Writing hygiene as an objective invites someone to score it and trade it. Writing it as a constraint makes it a filter that every option passes or fails before scoring starts. Chapter 9 turns the hygiene constraint into a testable condition on the water target.
The error: a means treated as an end
This is an illustration. The first draft of the project charter, prepared before the objectives were sorted, stated the project goal as “maximise wash throughput (kg/h)”. It was a reasonable-sounding sentence, and every vendor proposal scored well against it, because each one washed faster than the present machines.
The flaw appeared in the owners’ review meeting, when the operations manager walked the goal up the ladder. Why does wash throughput matter? So that linen is ready for ironing sooner. Why does that matter? So that deliveries leave on time. Why does that matter? Because the hospital group requires 98% OTIF. At that rung the docket analysis from Chapter 1 applied: washing was the primary cause of 37 of 412 failed deliveries. The rest came after washing. On a peak day, about 1,553 kg of flatwork was still waiting to be ironed when production ended, a figure Chapter 6 derives from the ironers’ effective rates. A faster wash room would only make that pile arrive at the ironers earlier and wait longer.
“Maximise wash throughput” had two faults. It named a lower means as the goal, so the project would have been judged a success if the tunnel washed fast, whatever happened to deliveries. And it had no stopping point: “maximise” gives no level at which enough is enough, so it could justify any spend. The correction was to move throughput down the hierarchy, under “enough washing capacity”, with no target of its own until washing actually becomes the constraint, and to restate the project goal in terms of the fundamental objectives and the four means objectives. The charter now reads: keep the hospital contract through the month-12 tender at the new price while holding the margin, shown by OTIF, cost per clean kilogram, and water and energy per clean kilogram against targets set from the tender and the price.
Before you buy: challenge the need, then judge the whole-life commitment gives a broader checklist for testing whether a proposed purchase serves a need at all. The objectives hierarchy is the laundry’s version of that test.
Where the hierarchy leads
The hierarchy and the value at stake do three jobs in the chapters that follow. They tell Targets derived from the purpose, not from the baseline where each target value must come from: the tender for OTIF, water and energy, and the margin at the new price for cost. They give the benefits dependency network in Mapping benefits back to business changes and enablers its right-hand side, the objectives the changes must serve. And they give every later argument a sense of proportion: a change that protects A$1.41 million a year of contribution is worth serious money, and one that serves no objective in the hierarchy is worth none, however attractive it looks on its own. Chapter 1 found the first sign of that: most of the requested plant aims at washing, which sits on one small branch of the tree.
Exercise: a smaller hospital share
Suppose the hospital group sent 50% of the laundry’s volume instead of 55%: 1,560,000 kg a year. Using the same variable cost per kilogram, A$0.9376, and the same expected price of A$1.76/kg, what contribution would the laundry lose each year if it lost the contract, and what is the present value over five years at 8%?
Worked answer. The contribution per kilogram is unchanged at 1.76 − 0.9376 = A$0.8224. The contribution lost is 0.8224 × 1,560,000 = A$1,282,944, about A$1.28 million a year; with the unrounded variable cost the figure is A$1,282,948. The five-year annuity factor at 8% is 1 ÷ 1.08 + 1 ÷ 1.08² + … + 1 ÷ 1.08⁵ = 3.9927, so the present value is 1,282,948 × 3.9927, about A$5.12 million. The stake is smaller but of the same order, and the conclusion holds: keeping the contract is worth far more than a year’s profit, and the options must be judged on whether they keep it.