GLM 5.3 FlashX Legal: Why Riverside Food Network is losing volunteers

The decision: how to spend next year's £45,000 for volunteer support: reimburse volunteers' travel costs, fund a part-time volunteer coordinator with online shift booking, or do both at a smaller scale. The brief and the data →

Verdict: ✗ Not sound
Research score: 58 of 100
Analysis rating: 997
Head to head, this task: won 12 of 15

Why it is not sound

The survey

Produced no usable survey

The analysis

Reported a material finding the data does not support
Proposed a mistaken next step: Set up a travel scheme for under-25s on the strength of the lapsed under-25 result

Findings the judges found unsupported

If online booking were introduced, 40.2% of lapsed respondents say they would be likely or very likely to volunteer again — about 400 of the 1,000 lapsed volunteers if the sample were representative. This is a ceiling, not a forecast: it is stated intention from an 11.2% lapsed response rate; 35.8% say they are unlikely even with booking; and only 14.3% of those who left over travel would return. Among scheduling-leavers the stated return rate is 60.4% (about 290 of 1,000 if that group is representative).The extrapolated 400 returners is not an established ceiling or upper bound. Hypothetical intentions from a self-selected sample cannot establish a population bound. The approximately 290 scheduling-leavers likewise depends on unverified population representativeness.
Travel-cost difficulty does not distinguish people who left from people who stayed. Active 37.2% vs lapsed 40.2% is a 3.0-point gap that is not significant at the 95% level (two-proportion z ≈ 0.52, p ≈ 0.60). Travel is a widespread irritation across the whole volunteer body, not the trigger that separates leavers from stayers. Spend aimed only at travel therefore subsidises many people who were never going to leave, and misses most of those who did.Similar travel-cost difficulty rates do not establish that reimbursement would subsidise people who were never going to leave. The survey does not measure active volunteers' future departure risk or the effect of reimbursement on retention.
Under-25 leavers do mostly blame travel: 72.7% give it as their main reason for stopping and 81.8% tick it as a difficulty. A targeted under-25 travel scheme is the one travel intervention the data supports in direction — but it rests on 11 lapsed under-25 respondents (8 of whom chose travel as the main reason), so it should be piloted, not treated as a mandate. Nearly half of those 11 (45.5%) also tick short-notice changes, and 54.5% tick poor notice, so travel is not the only friction even in this group.The result from 11 lapsed under-25s is insufficient to support selecting under-25s for a travel scheme, even a pilot. It supports further investigation and potentially needs-based travel assistance, not an age-specific intervention on this evidence alone.
The sample under-represents under-25s and over-represents volunteers aged 65+, which understates travel difficulty among lapsed volunteers. Age-weighting to the 1,000 lapsed volunteers raises lapsed travel-cost difficulty from 40.2% to 47.4%. Even weighted, travel remains one difficulty among several and is still only 11.6% as the main reason for stopping. The unweighted lapsed figures flatter a travel-only spend by under-counting the young, but they do not reverse the ranking of causes.The weighted travel-cost main-reason share is approximately 21%, not 11.6%; weighted scheduling is approximately 41%. The statement that the unweighted figures flatter a travel-only spend also reverses the direction of the age bias: they understate travel's importance.
A large share of lapsed volunteers cannot be recovered by either option. 23.2% say their main reason was a change in circumstances (work, study, health, moving). A further 18.8% say they are very unlikely to return even with online booking, and 17.0% very unlikely even with travel paid. The addressable population is smaller than '1,000 lapsed volunteers'.Changed circumstances and hypothetical unlikelihood do not establish that these volunteers cannot be recovered by either intervention. The groups can overlap, and their responses do not measure actual recovery under either option or both together.
Stated recovery from travel reimbursement is weaker and narrower than from booking. Overall, 26.8% of lapsed respondents say they would be likely to return if travel were paid, versus 40.2% for online booking. Travel reimbursement works mainly on the 14 people (12.5%) who already named travel or distance as their main reason (57.1% likely to return); it does almost nothing for scheduling-leavers (27.1%) and little for the rest (18.0%). A universal travel scheme would spend the budget on the whole volunteer body to reach a small, already-identified group.The survey measures stated intentions, not whether reimbursement works. Describing it as doing almost nothing for scheduling-leavers also overstates the evidence: 27.1% of that group report being likely to return.

Scorecard

Numbers 12 of 12 right

Question		Its answer	True
What percentage of active volunteers who responded chose 'The cost of travelling to the site' as a difficulty in Q2?	✓	37.2%	37.2%
What percentage of lapsed volunteers who responded chose 'The cost of travelling to the site' as a difficulty in Q2?	✓	40.2%	40.2%
Is the difference between active and lapsed respondents in the share choosing 'The cost of travelling to the site' in Q2 statistically significant at the 95% level? (1 for yes, 0 for no)	✓	No	No
Weighted to the age mix of all 1,000 lapsed volunteers, what percentage of lapsed volunteers would choose 'The cost of travelling to the site' as a difficulty in Q2?	✓	47.4%	47.4%
What percentage of lapsed respondents gave a scheduling reason as their main reason for stopping in Q3 (either of its first two options: shifts changed at short notice, or hard to arrange shifts)?	✓	42.9%	42.9%
What is the 95% margin of error, in percentage points, on that unweighted share of lapsed respondents giving a scheduling reason as their main reason?	✓	9.2 points	9.17 points
On average, how many difficulties did each respondent choose in Q2 (counting every option except 'None of these', which counts as zero), across all respondents?	✓	1.55	1.55
What percentage of lapsed respondents said they would be likely (fairly or very) to volunteer again if they could arrange their shifts online (Q4)?	✓	40.2%	40.2%
How many of the open-text answers mention shift scheduling (booking or swapping shifts, or last-minute changes or cancellations)?	✓	37	34
What percentage of the active volunteers invited completed the survey?	✓	52.4%	52.4%
What percentage of the lapsed volunteers invited completed the survey?	✓	11.2%	11.2%
If the lapsed respondents were representative, about how many of the 1,000 lapsed volunteers would give a scheduling reason (either of the first two Q3 options) as their main reason, using the unweighted share?	✓	429	429

Traps in the data 8 of 8 handled

✓Travel cost is the most-cited difficulty overall, but it is cited about as often by active volunteers (37%) as by lapsed ones (40%), so it does not explain who left. Short-notice shift changes (14% active against 52% lapsed), no way to book or swap shifts and not being told about changes differ sharply.
✓The operations lead believes volunteers leave because of travel costs. Among lapsed respondents, 43% give a scheduling reason as their main reason against 12% travel cost.
✓Q2 is multi-select: respondents chose 1.6 difficulties on average, so columns add up to more than 100%.
✓52% of active volunteers responded but only 11% of lapsed ones, so the lapsed base is small (112) and those who replied may differ from the 89% who did not (for example, still feeling some attachment).
✓Volunteers aged 65 or over are 43% of respondents but about 26% of volunteers in the database; younger volunteers cite travel cost more. Weighted to the lapsed age mix, travel cost among lapsed volunteers rises from 40% to 47%; a scheduling main reason goes from 43% to 41%, still well ahead of travel cost (21%).
✓Lapsed under-25s (base 11) mostly give travel cost as their main reason (8 of 11).
✓The travel-cost gap between lapsed and active respondents (3.0 points) is not significant at 95%.
✓40% of lapsed respondents say they would be likely to volunteer again with online booking: a stated intention about a hypothetical, from a small and self-selected base.

The analysis

Recommendation

Choose both at a smaller scale, weighted toward scheduling. Do not spend the £45,000 on travel reimbursement alone. Travel is the most-ticked prompted difficulty, but it is the main reason for stopping for only 11.6% of lapsed volunteers, it does not separate leavers from stayers (37.2% vs 40.2%, not significant), and only 26.8% say they would return if travel were paid. Scheduling is the main reason for 42.9%, unprompted mentions of scheduling outnumber travel (37 vs 22), and 40.2% of lapsed respondents say they would be likely to return with online booking (60.4% of scheduling-leavers). Fund a part-time volunteer coordinator to introduce online shift booking, publish rotas further ahead, and send reliable first-hand change notifications; use the remainder for a targeted travel scheme (under-25s and volunteers with high out-of-pocket journey costs), not a universal reimbursement. To the chair: treat ~400 would-be returners as an upper bound from stated intent on a 11.2% response rate, not a forecast; plan for a fraction of that, concentrated among scheduling-leavers. To the volunteer manager: an under-25 travel pilot is supported by the direction of the data (72.7% of 11 leavers blame travel) but not yet by its strength; do not build a permanent scheme on this evidence alone. To the operations lead: travel is real, especially for younger volunteers and some older volunteers on pensions, but it is not the attrition problem the £45,000 is being asked to solve. Pilot both arms for 12 weeks, measure actual returns and retention, then scale what works before committing the full budget.

What would change it

A costing showing that universal travel reimbursement is cheap enough (average fare × shifts per volunteer) to fund alongside a full coordinator, rather than forcing a smaller-scale choice. A booking pilot showing actual return rates close to the 40.2% stated intent, or showing that a part-time coordinator cannot serve 9 sites (which would shift weight to software plus targeted travel). A larger lapsed under-25 sample (n=11 is too thin) that confirms or overturns travel as their dominant main reason. Interviews showing that most 'circumstances changed' leavers would in fact return if scheduling or travel were fixed. Evidence that active volunteers are at high risk of leaving over unreimbursed travel, which would raise the retention case for a broader travel scheme. Conversely, evidence that most lapsed volunteers no longer live locally or no longer want to volunteer would shrink the addressable population and favour retention of current volunteers over recovery of lapsed ones.

Findings

Scheduling failure, not travel cost, is the main stated reason volunteers stop. Short-notice changes plus hard-to-arrange shifts account for 42.9% of main reasons for leaving; travel cost is the main reason for only 11.6%. The operations lead's inference from 'travel is mentioned most' does not hold for attrition: among lapsed volunteers, travel is the fourth-most-ticked difficulty (40.2%), behind short-notice changes (51.8%), no easy booking (42.0%) and poor notice (41.1%).

High confidenceBase 112

Q3, lapsed n=112: shifts changed at short notice 29.5% (33) + hard to arrange shifts 13.4% (15) = 42.9% (48); travel cost 11.6% (13); circumstances changed 23.2% (26). Q2 lapsed n=112: short notice 51.8%, no easy booking 42.0%, not told 41.1%, travel cost 40.2%.
If online booking were introduced, 40.2% of lapsed respondents say they would be likely or very likely to volunteer again — about 400 of the 1,000 lapsed volunteers if the sample were representative. This is a ceiling, not a forecast: it is stated intention from an 11.2% lapsed response rate; 35.8% say they are unlikely even with booking; and only 14.3% of those who left over travel would return. Among scheduling-leavers the stated return rate is 60.4% (about 290 of 1,000 if that group is representative).

Medium confidenceBase 112

Q4 net likely 40.2% (45/112). By Q3 reason: scheduling 60.4% (29/48), travel or distance 14.3% (2/14), something else 28.0% (14/50). Q4 very unlikely 18.8% + fairly unlikely 17.0% = 35.8%. Lapsed invitation base 1,000, completes 112.
Travel-cost difficulty does not distinguish people who left from people who stayed. Active 37.2% vs lapsed 40.2% is a 3.0-point gap that is not significant at the 95% level (two-proportion z ≈ 0.52, p ≈ 0.60). Travel is a widespread irritation across the whole volunteer body, not the trigger that separates leavers from stayers. Spend aimed only at travel therefore subsidises many people who were never going to leave, and misses most of those who did.

High confidenceBase 327

Q2: 80/215 active (37.2%) and 45/112 lapsed (40.2%) chose cost of travelling. Pooled p = 125/327 = 0.382, SE = 0.057, z = 0.52. 95% CIs overlap (active ~30.7–43.7%, lapsed ~31.1–49.3%).
Under-25 leavers do mostly blame travel: 72.7% give it as their main reason for stopping and 81.8% tick it as a difficulty. A targeted under-25 travel scheme is the one travel intervention the data supports in direction — but it rests on 11 lapsed under-25 respondents (8 of whom chose travel as the main reason), so it should be piloted, not treated as a mandate. Nearly half of those 11 (45.5%) also tick short-notice changes, and 54.5% tick poor notice, so travel is not the only friction even in this group.

Low confidenceBase 11

Q3 under-25 column n=11: travel cost 72.7% (8), short notice 18.2% (2), not valued 9.1% (1). Q2 lapsed under-25 n=11: travel 81.8% (9), not told 54.5% (6), short notice 45.5% (5), no easy booking 27.3% (3). Under-25s are 9.8% of lapsed respondents vs 22% of the 1,000 lapsed population.
The sample under-represents under-25s and over-represents volunteers aged 65+, which understates travel difficulty among lapsed volunteers. Age-weighting to the 1,000 lapsed volunteers raises lapsed travel-cost difficulty from 40.2% to 47.4%. Even weighted, travel remains one difficulty among several and is still only 11.6% as the main reason for stopping. The unweighted lapsed figures flatter a travel-only spend by under-counting the young, but they do not reverse the ranking of causes.

Medium confidenceBase 112

Lapsed respondents: 11 under-25 (9.8%) vs 22% of population; 21 aged 25–44 (18.8%) vs 30%; 36 aged 45–64 (32.1%) vs 23%; 44 aged 65+ (39.3%) vs 25%. Weighted Q2 travel: 0.22×81.8 + 0.30×42.9 + 0.23×47.2 + 0.25×22.7 = 47.4%. Q3 travel main reason stays 11.6% unweighted; under-25 weighting would raise it but from a very small cell.
A large share of lapsed volunteers cannot be recovered by either option. 23.2% say their main reason was a change in circumstances (work, study, health, moving). A further 18.8% say they are very unlikely to return even with online booking, and 17.0% very unlikely even with travel paid. The addressable population is smaller than '1,000 lapsed volunteers'.

High confidenceBase 112

Q3 circumstances changed 23.2% (26/112). Q4 very unlikely 18.8% (21/112). Q5 very unlikely 17.0% (19/112).
Active volunteers also want the scheduling fix, so a coordinator plus online booking is a retention investment as well as a recovery one. 11.6% of active respondents already say there is no easy way to arrange shifts, and the open-text answers repeatedly ask for online booking, swap tools, recurring shifts and reliable change notices, mostly from people who are still volunteering. Only 2.7% of lapsed volunteers said they had no difficulties, against 28.4% of active volunteers: almost everyone who left had hit friction.

Medium confidenceBase 215

Q2 active n=215: no easy way 11.6% (25), short notice 14.4% (31), not told 7.4% (16), none of these 28.4% (61). Q2 lapsed: none of these 2.7% (3/112). Open-text: 20 answers ask for online booking or swapping (e.g. V046, V061, V102, V116, V120, V210, V225, V273), many from active volunteers.
Unprompted, more respondents write about scheduling than about travel cost. This contradicts reading Q2's prompted 'travel mention most' as the priority. Of 109 open-text answers, 37 mention shift scheduling (booking, swapping, last-minute changes or cancellations) and 22 mention travel cost. When people can say anything, they talk about the rota more than the bus.

Medium confidenceBase 109

Q1 open-text, 109 answers. Scheduling mentions include booking/swapping (20 IDs) and last-minute changes/poor notice (19 IDs), with two IDs in both. Travel-cost mentions: 22 IDs. Open-text is self-selected (109 of 327 completers, 33%).
Stated recovery from travel reimbursement is weaker and narrower than from booking. Overall, 26.8% of lapsed respondents say they would be likely to return if travel were paid, versus 40.2% for online booking. Travel reimbursement works mainly on the 14 people (12.5%) who already named travel or distance as their main reason (57.1% likely to return); it does almost nothing for scheduling-leavers (27.1%) and little for the rest (18.0%). A universal travel scheme would spend the budget on the whole volunteer body to reach a small, already-identified group.

Medium confidenceBase 112

Q5 net likely 26.8% (30/112). By Q3 reason: scheduling 27.1% (13/48), travel or distance 57.1% (8/14), something else 18.0% (9/50). Q4 equivalent overall 40.2%.

Caveats

The tables are unweighted and the sample is age-skewed: under-25s are 8.3% of respondents vs 18% of active and 22% of lapsed populations; 65+ are 43.1% of respondents vs 30% active and 25% lapsed. Weighted lapsed travel difficulty is 47.4%, not 40.2%.
Lapsed response rate is 11.2% (112/1,000) against 52.4% of active volunteers (215/410). Leavers who felt strongly, live nearby, or still use the email/phone details on file are more likely to have answered; the 1,000 lapsed include people who have moved, lost interest entirely, or can no longer be reached. Findings describe survey respondents, not the whole lapsed population.
Q4 and Q5 are hypothetical stated intentions. They will overstate actual return. Do not budget or report to trustees as if 400 volunteers will come back.
Small subgroup bases: lapsed under-25 n=11; Q4/Q5 travel-reason column n=14. The 95% margin of error on the 42.9% scheduling main-reason share is ±9.2 percentage points (roughly 33.7% to 52.1%).
Q2 is a prompted multi-select difficulty list; Q3 is a single main reason. Being ticked most in Q2 is not the same as causing people to leave. Unprompted Q1 answers mention scheduling more often than travel.
23.2% of lapsed volunteers give changed circumstances as the main reason. Neither travel reimbursement nor online booking addresses that group. Some may have underlying scheduling or travel strain that they did not name as the main reason; interviews would test that.
No cost data were collected: coordinator salary, booking-software cost, average journey cost, or shifts per volunteer per month. Value for money of the three options cannot be calculated from this survey. Universal reimbursement could plausibly consume most or all of the £45,000, leaving nothing for the scheduling fixes that dominate attrition.
Open-text answers come from 109 of 327 completers (33%) and are self-selected toward people with a view. The 37 scheduling and 22 travel mentions are directionally useful, not a census.
Active-volunteer difficulties are not the same as lapsed-volunteer reasons for leaving. Using current volunteers' travel complaints to design a recovery spend for leavers is a category error, though it is relevant to retention.
No data on whether online booking actually reduces no-shows or last-minute gaps at the 9 sites, and no evidence on whether a part-time coordinator can serve 9 sites. Q6 site bases are too small for site-level decisions.
The survey covers current and former volunteers only. It says nothing about people who never started, and cannot separate 'left because of travel' from 'left, and travel is the easiest reason to give'.

Next steps

decisionAdopt 'both at smaller scale, coordinator and booking-led, plus targeted travel' as the working decision, with an explicit 6-month review gate before the full £45,000 is committed.
experimentPilot online shift booking, a month-ahead rota, and SMS/email change alerts at 3 sites (one large, one small, one with a younger profile) for 12 weeks. Invite lapsed volunteers from those sites who gave a scheduling main reason.
experimentPilot targeted travel reimbursement for under-25s and volunteers whose out-of-pocket journey cost exceeds a set threshold (for example £4 per shift), with a per-volunteer cap, at the same or overlapping sites, for 12 weeks. Do not offer universal reimbursement in the pilot.
researchRun depth interviews with about 20 lapsed volunteers: 10 who gave a scheduling main reason, 5 travel, 5 changed circumstances. Ask what would actually bring them back, and whether circumstances had a hidden scheduling or travel cause.
researchCost the three options properly: fully loaded part-time coordinator cost, booking-software licence, and average travel cost × shifts per volunteer per month, using finance data and a short shift-frequency question to site leads.
researchTop up the lapsed under-25 sample to at least 40 completes, by targeted phone or reminder, before any permanent under-25 travel scheme is designed.
monitorAsk the 9 site leads to log last-minute changes, no-shows and late cancellations for 8 weeks, and to estimate hours currently spent on rota administration by phone and message.
decisionAfter the 12-week pilots and the cost model, take a scale-up / reallocation / stop decision on the full £45,000, with actual return and retention figures replacing Q4/Q5 stated intent.

Open-text themes it coded

Travel cost (fares, fuel, parking charges, reimbursement) 22Journey time and site location 9Parking and physical access 6Self-service shift booking and swapping 20Rota changes, cancellations and poor notice 19No suggestion — volunteering already easy enough 38Recognition and feeling valued 2Training 1

The survey it planned

This model produced no usable survey for this task.