Options derived from the outcome, and why the choice changed

A request for a new plant offers one option and asks for a yes. An outcome-first project assembles several options from the changes that would close the gap, and scores each against every target. This chapter does that for the laundry. It builds a longlist from the benefits dependency network of Chapter 7, reduces it to a shortlist that includes doing nothing different and doing the least that could work, and scores all of them on the four measures and on one constraint that the original request never mentioned: whether the option can produce its evidence before the tender closes.

The result is a change of choice. The option the owners asked for fails two of the four targets and cannot be finished in time. The option derived from the outcome passes all four, costs less than half as much, and is ready a month before the evidence window opens. A third option keeps the owners’ instinct to invest in washing for the time when the washers actually run out.

From the network to a longlist

The benefits dependency network gives a list of changes, not a list of options. An option is a coherent package of changes that could be approved and delivered as one. The operations manager and the finance manager built the longlist cause by cause, using the network’s business changes as the headings.

• Ironer capacity and reliability: a preventive maintenance contract on line 1; a rebuild of line 1; a new line replacing line 1; a third line alongside the existing two; sending peak-day flatwork to another laundry.
• Dispatch: a 03:30 loading shift; route-planning software; an extra van and driver.
• Customers: a collection-time agreement.
• Wash room: a tunnel washer in a building extension; water-efficient washer-extractors in place of the oldest machines; rinse-water reuse; waste-water heat recovery; new dryers.

Each candidate was then filtered on three questions. Does it act on a cause found in Chapter 6? Can it be in service before the evidence window opens in month 6, if it is needed for delivery? Does it meet the constraints every option must meet, including hygiene to AS 4146:2024 and the hospital group’s terms? A third ironer line failed the second question, because there is no floor space for it without an extension. Sending peak-day hospital flatwork to another laundry failed the third, because the hospital group’s terms would have to allow it and the laundry would be relying on a competitor during its own tender.

This sequence, objectives first, then a longlist, then a filtered shortlist, is standard in public appraisal. The HM Treasury Green Book sets SMART objectives before the longlist is generated and appraises the shortlist against business as usual and a do-minimum option. Infrastructure Australia’s Assessment Framework (2021) puts problem definition first and options identification and analysis, from a longlist filtered to a shortlist, second, before the business case; Infrastructure Australia notes that the framework is changing, so the current version should be checked. A family laundry does not need the paperwork, but it gains from the discipline.

The shortlist

This is an illustration. All amounts are Australian dollars excluding GST. Five options went forward.

• Business as usual (BAU). No investment. It is the base against which the others are measured, and with the price cut it is not a safe choice: its margin at the new hospital price is 9.5%, and the contract, worth about A$1.41 million a year of contribution, is at risk.
• Do-minimum. The dispatch changes (item S), the customer agreement (C) and a preventive maintenance contract on line 1 that lifts its availability from 0.72 to 0.90. Capital A$140,000.
• Option A, the new plant. The owners’ brief: tunnel washer (T), three gas dryers (D), a 600 m² extension (E), RFID linen tracking (R) and amenities (M). Capital A$6,120,000.
• Option B, outcome-derived. The seven enablers of Chapter 7: I, F, S, W, H, X and C. Capital A$2,440,000.
• Option C, staged. Option B now, with a later decision gate on the tunnel and extension when washing capacity actually runs out.

Scoring every option on all four targets

Each option’s delivery result comes from applying its removal shares to the 412 failures by cause. Its cost per kilogram comes from the same fully loaded cost model as the A$1.711 baseline, including an 8% capital charge on new plant over 12 years and on buildings over 25 years. Its water and energy come from the wash, dry and iron model of Chapter 6.

Figure 1The shortlist scored against the four targets

	OTIF, at least 98%	Cost, at most A$1.66/kg	Water, at most 10.0 L/kg	Energy, at most 5.0 MJ/kg	Ready by month 6
Business as usual	91.2%: fail	A$1.711: fail	14.0: fail	6.00: fail	not applicable
Do-minimum, A$140,000	95.5%: fail	A$1.776: fail	14.0: fail	6.00: fail	yes
Option A, new plant, A$6,120,000	91.9%: fail	A$1.770: fail	8.38: pass	4.77: pass	no: 14 months
Option B, outcome-derived, A$2,440,000	98.2%: pass	A$1.625: pass	9.60: pass	4.89: pass	yes: month 5
Option C, B now and a tunnel gate later	98.2%: pass	A$1.625: pass	9.60: pass	4.89: pass	yes: month 5

Do-minimum reaches 95.5% (95.47%), leaving 211.9 failures, 118.9 more than the 93 allowed. Maintenance halves the breakdown failures and the dispatch changes and agreement work as they do in Option B, but without new ironer capacity 70% of the peak-day backlog remains, as Chapter 6’s exercise predicted. It also costs more than doing nothing: A$5,541,281 a year, A$1.776/kg, because it adds the early-shift penalties, the extra driver, the van, the software and the maintenance contract without any of the labour saving that a new line’s automatic feeder and folder bring. It does nothing for water or energy.

Option A removes 90% of the 37 wash-capacity failures, 33.3 in all, and nothing else, leaving 378.7 failures: 91.9% (91.91%). It meets both sustainability thresholds, with 8.38 L/kg and 4.77 MJ/kg, because a tunnel washer reuses water from compartment to compartment and heats far less of it. But its annual cost is A$5,521,482, A$183,778 a year above the baseline, A$1.770/kg: the six wash-room roles it saves and its lower water and gas bills do not cover the capital charge on A$6.12 million.

Option B leaves 84.0 failures: 98.2% (98.21%). Its annual cost is A$5,071,051, A$266,653 a year below the baseline, A$1.625/kg. Water is 9.60 L/kg and energy 4.89 MJ/kg. Each pass is real, and several are narrow: 9.0 failures inside the delivery limit, 0.40 L/kg inside the water threshold and 0.11 MJ/kg inside the energy threshold.

Translated into margin at the new hospital price of A$1.76/kg, the options separate further. Business as usual earns 9.5%, do-minimum about 6.1%, Option A about 6.4% and Option B about 14.0%, above the 12% the cost target was built to protect.

Figure 2Cost per clean kilogram by option, against the A$1.66 ceiling

Business as usual1.711 A$/kg

Do-minimum1.776 A$/kg

Option A, new plant1.770 A$/kg

Option A, with vendor's 8 roles saved1.726 A$/kg

Option B, outcome-derived1.625 A$/kg

Ceiling from the purpose1.66 A$/kg

How robust Option B’s pass is

A pass by 9.0 failures rests on the removal estimates of Mapping benefits back to business changes and enablers, and it is worth knowing how far each could be wrong before the pass disappears. Unrounded, Option B leaves 83.95 failures, so the estimates can fall short by a combined 9.05 failures before the limit of 93 is reached. Taking one estimate at a time, the break-even values are these:

• Peak-day backlog: removal could fall from 95% to about 89.2% (157 failures, so each point is 1.57 failures).
• Breakdowns: from 85% to about 72.8%.
• Dispatch: from 80% to about 71.8%.
• Late soiled linen: from 60% to about 32.6%.

The backlog estimate is the most sensitive, because it applies to the largest cause: a six-point shortfall there uses up the whole margin. That is why Chapter 9 turns the new line’s capacity into a requirement with its own margin, and why the dispatch and backlog figures are the first leading indicators tracked in Chapter 10. The cost pass has a similar margin: A$108,149 a year, about A$0.035/kg, or roughly the cost of 1.6 full-time equivalents at A$68,000.

The Two-Option Comparison tool sets two options side by side on value, cost, delivery time and risk, and is a quick way to check the A against B comparison with different assumptions.

Time as a criterion

The scorecard has a fifth column because the purpose has a date. The hospital group will judge the laundry on the trailing 26 weeks before the tender closes at month 12, which are months 6 to 11. An option that is not working by month 6 cannot produce the evidence, however good it might be later.

Figure 3Readiness against the evidence window and the tender

1. Month 0Approval, in Julyironer line ordered on a 20-week lead time
2. Month 2Dispatch changes live03:30 loading shift, route software, extra van
3. Month 3Customer agreement signedcollection times and cages
4. Month 4Wash-room items in servicerinse reuse, heat recovery, three washers
5. Month 5New ironer line acceptedinstalled over two weekends
6. Months 6–11Evidence window, January to June26 weeks, 4,680 deliveries, at most 93 failures
7. Month 12Tender closesevidence submitted
8. Month 14Option A complete at the earliestdevelopment approval and construction
9. Month 18Current hospital contract endsthe new contract starts if the tender is won

Option A needs development approval for the extension and then construction, about 14 months in all. Even if it fixed delivery, which it does not, the laundry would enter the tender with today’s 91.2%.

Both durations, the 14 months for Option A and the five months for Option B, are estimates made from the inside: from quotes and the plan, not from the record of similar projects. Option B’s one month of slack is thin. The inside view and the plan on the table in Reference Class Forecasting by the Numbers explains why such estimates run optimistic and how to correct them with past outcomes; in the laundry’s case it argues for ordering the ironer line on the day of approval and for an agreed fallback if installation slips.

Option C: the tunnel, when the washers run out

The owners’ instinct to invest in washing was not wrong. Chapter 6 showed the washers at 81.7% utilisation today and reaching 90%, 66,096 kg a week, during year 4 at 3% growth. At some point the laundry will need more washing capacity, and a tunnel washer in an extension may then be the right answer. What was wrong was the timing and the reason: it was aimed at a constraint that does not yet bind, and at the expense of the constraint that does.

Option C keeps the tunnel as a decision for later. It implements Option B now and sets a decision gate on the tunnel and extension, A$5,000,000 together, to open when wash utilisation has held at 90% for 8 weeks. The gate is written now, with its trigger and the measures the decision will use, so that it is not forgotten or decided on impulse.

Deferring A$5.0 million by the expected four years has a value even if the tunnel is eventually built exactly as planned. At 8% a year:

5,000,000 × (1 − 1/1.08⁴) = 5,000,000 × 0.2650 = A$1,324,851 in present value.

It also has a value that the arithmetic does not capture. In year 4 the laundry will know whether it kept the hospital contract, how fast volume actually grew, and what washing technology costs then. If the contract were lost, the tunnel would not be needed at all. Waiting, testing or proceeding: simple real options in Stage Gates and Stopping Rules by the Numbers sets out when the right to wait is worth more than committing now and when it is not.

Figure 4Committing to the tunnel now against gating it

Option A now

• A$6,120,000 committed before the tender result is known
• Fixes 33.3 of 412 failures; OTIF 91.9%
• Built for washing capacity not needed until about year 4
• Decided on today's volume and prices
• No present-value saving

Option C, gate in about year 4

• A$2,440,000 committed now; A$5,000,000 decided later
• Fixes 328.1 failures now; OTIF 98.2%
• Trigger: 66,096 kg a week held for 8 weeks
• Decided on actual growth, contract result and prices then
• Deferral worth about A$1.32 million in present value

The errors: one measure at a time, and a vendor’s claim

This is an illustration. Two errors appeared while the options were being compared, and both were caught by the same rule: no option is ranked until it has been scored on all four targets.

Ranking on one measure. The owners’ first comparison put Options A and B side by side on water alone, on which A wins clearly with 8.38 L/kg against 9.60. A later draft, prepared to answer that comparison, ranked them on capital alone, on which B wins with A$2.44 million against A$6.12 million, and recommended B without anyone checking its delivery result. The first ranking chose an option that fails delivery and cost. The second chose the right option by luck: on capital alone the do-minimum, at A$140,000, would have beaten both, and it fails all four targets. A ranking on a single measure says nothing about the others, and the measure chosen tends to be the one that favours the option its author already prefers.

The vendor’s claim. The tunnel supplier’s proposal stated that the tunnel would save eight wash-room roles, not the six in the operations manager’s model. The owners asked whether that changed the answer. It does not: two more roles save A$136,000 a year, bringing Option A to A$1.726/kg, still above the A$1.66 ceiling and still above today’s A$1.711. And no number of wash-room roles changes Option A’s delivery result, which stays at 91.9%, because the failures are not in the wash room. The claim was answered in a single sentence once the scorecard existed: it moves one cell, and that cell still fails.

Why the choice changed

The owners asked for a new plant because the plant was old, the washers were busy and a tunnel would save water, energy and labour. All of that was true. It was not the problem the business had to solve in the next twelve months. Working back from the outcome found that the hospital contract depends on delivery and price, that delivery fails in the ironer room and the dock, and that the evidence must be produced in six months that start half a year from approval. Options derived from that analysis look different from the request, and the best of them meets every target at less than half the capital. Tracing every scope item and requirement to a target now tests whether every item in that option, and in the request, earns its place.

Exercise: deferring by three years

Suppose volume grows faster than expected and the tunnel gate is expected to open after three years instead of four. What is the present value at 8% of deferring the A$5.0 million tunnel and extension by three years, and how much of the four-year value is lost?

Worked answer. The present value of deferral is 5,000,000 × (1 − 1/1.08³) = 5,000,000 × 0.2062 = A$1,030,839. Against the four-year value of A$1,324,851 that is A$294,012 less, but deferring is still worth more than A$1 million in present value, and the information gained by waiting is unchanged. Faster growth makes the gate open sooner; it does not make committing to the tunnel before the tender the better choice.