See where margin leaks. Close the gaps. Prove the ROI.
Shrink. Waste write-offs. Customer credits. Returns. None of it arrives in your P&L as a single line with a cause attached, which is exactly why it survives. Avoidable food waste alone costs the average UK food and drink business £156,599 a year. You know the margin is going somewhere. What you lack is the number, the reason, and a case you will defend in front of the board.
Achieve every one of these with Infios WMS, delivered in the UK by Balloon One.
One change does the work: measure each loss at the moment it is created on the floor, instead of meeting it weeks later as a total in your accounts. Balloon One has been building that measurement into UK food and drink operations for 20 years.
Variance with a cause attached
Every movement scanner-confirmed against a location and a batch. Shrink surfaces in hours, attributable to a line, a location or a process.
Write-offs cut by design
FEFO and expiry control push shortest-life stock out first. Albion Fine Foods runs under 3% waste on fresh produce using ProFresh.
Credits you can dispute
Scan-level despatch evidence means a disputed short delivery becomes a record you produce, not a claim you concede.
A case that survives the board
Output per hour by task and zone, cost per order line, loss by cause. The ROI argument is arithmetic rather than assertion.
Delivered by Balloon One, exclusive UK partner for Infios WMS since 2005 and a SAP Business One Gold Partner.
Margin doesn't disappear all at once. It leaves in small amounts, in four places.
Individually, each of these is small enough to absorb and vague enough to argue about. Together they form one of the largest controllable costs in a food distribution business. They persist because by the time they reach you, they have already been aggregated into a number with no cause attached.
Shrink you can't locate
The variance shows up at the stock check, weeks after whatever caused it. You know the value. You don't know the line, the location or the process, so you can't stop it happening again.
Waste as a standing line item
Short-dated stock bought, handled, stored and then binned. You've paid the full cost of that product several times over before you write it off entirely.
Credits and returns you can't dispute
The product value is the smallest part of it. Add the collection, the re-pick, the admin, the disposal and the customer's goodwill. And with no record of what left the building, a claim gets credited rather than questioned.
Labour you can't judge
Overtime and agency spend climb, and you have no measure that tells you whether that's a staffing problem or a process problem. So the debate is settled by whoever argues hardest.
Every one of these costs is created on the warehouse floor and only becomes visible in your accounts weeks later, as a total. You are being asked to manage a cost using a number that arrives long after the event that caused it, with no record of the event itself. This is a measurement gap. The one place these costs are created is the one place you have no live data from. Close that gap and the leak stops being an argument and becomes a list of specific, fixable causes.
Balloon One's Out of Date research put avoidable food waste at £156,599 per UK food and beverage business annually. Businesses lose 12% of fresh or perishable stock each year, 7% of it created internally through over-ordering, poor rotation and handling errors. Managers named outdated technology (37%) and disconnected systems (33%) as the leading causes, and 64% still believe their current systems are adequate.
Out of Date · Balloon One research into the UK F&B supply chainWhat it looks like when the leak has a name, a location and a number.
This is a visibility exercise, and cost comes out of it. When each loss is recorded as it happens, the monthly total stops being a mystery to explain and becomes a set of decisions to make.
Variance found in hours, not quarters
Discrepancies surface while the cause is still traceable, attributable to a line, a location and a process, so the fix is specific rather than a memo about being careful.
Write-offs become an exception
Shortest-life stock moves first as a rule the system enforces, and short-dated product surfaces while it can still be sold. Waste stops being a monthly line and becomes an incident you investigate.
Fewer credits, and evidence for the rest
Most credits trace back to a mispick that never had to happen. For the ones that remain, you can show exactly what was picked, from which batch, and when it left.
A case you'd defend at board level
Labour measured per order line, losses measured at source, and a business case built from your own operational data rather than a vendor's averages.
UK food and drink businesses that closed the measurement gap.
Balloon One has been the exclusive UK partner for Infios WMS (formerly Körber, formerly HighJump) since 2005, and built the food-specific modules (FEFO, expiry control and cold-chain) that make the margin arithmetic work in a date-coded operation. The same record that closes the margin gap keeps you audit-ready for BRCGS, SQF and your customers' own standards, so the investment answers two questions at once. This is a WMS shaped around food and drink over 20 years, not a generic one pointed at it.
Wing Yip
The UK's largest oriental grocer. Weekly stock checks are now consistently accurate, with better traceability and more streamlined processes, which is where shrink visibility begins.
Birchall Foodservice
A national foodservice operator running ambient, chilled and frozen, with full warehouse transparency and traceability across the estate.
Classic Fine Foods
Fresh, frozen and pastry to the world's best restaurants and hotels, where short shelf life makes expiry write-off a permanent margin risk.
Huel
One of the UK's fastest-growing food and drink brands. Infios WMS was brought in to support in-house warehousing through a global expansion strategy.
Measure the loss at the moment it happens. Then the ROI argues itself.
A warehouse management system is, for your purposes, a measurement instrument that also prevents the thing it measures. We deliver Infios WMS in the UK, with the food-and-drink modules we've built on it over 20 years: FEFO and expiry control, cold-chain monitoring, demand forecasting for perishables and scanner-guided tasks. Here's how that maps onto each of your questions.
“Where is all this shrink and waste cost actually coming from?”
From events nobody recorded. Record every movement and the cost acquires a cause.
Every receipt, put-away, move and pick is scanner-confirmed against a location and a batch, which makes stock accurate in real time rather than at quarter end. Variance then surfaces in hours, while the cause is still findable, and it's attributable to a specific line, location or process instead of being absorbed into one number. On the waste side, FEFO and expiry control make first-expired-first-out a rule the system enforces rather than a habit you hope for, and short-dated batches surface while there's still time to sell them. Demand forecasting for perishables then attacks the same cost further upstream, by buying closer to what you'll actually sell.
- Real-time stock accuracyEvery movement confirmed on the scanner, so the book figure and the floor figure stay together.
- Variance with a cause attachedDiscrepancies traceable to a line, a location and a process, not a quarterly total.
- FEFO and expiry controlShortest-life stock ships first by rule, and short-dated product is flagged while it's still sellable.
- Forecasting for perishablesLess short-life stock bought means less short-life stock at risk in the first place.
“We're getting killed on credits and returns. What's driving them and how do we cut them?”
Mostly mispicks. Stop the mispick at the scan and the credit never gets raised.
The large majority of credits in a food operation begin as a picking error: wrong item, wrong quantity, wrong date code, or an ambient pallet in a chilled order. Scanner-guided, system-directed picking verifies the product, the location and the batch before the line is confirmed, so the error is caught on the floor rather than at the customer's door. That removes the credit, and with it the collection, the re-pick, the disposal and the admin behind each one. And where a claim does arrive, you have a lot-level record of what was picked and despatched, which turns a credit you'd have conceded into a conversation you can have with evidence.
- Errors stopped at the scanProduct, location and date code verified before the pick counts, not after the customer complains.
- The whole cost avoidedNo credit note, no collection, no re-pick, no disposal, no goodwill spend.
- Evidence for disputed claimsLot-level despatch records mean a claim can be tested rather than automatically credited.
- Fewer awkward conversationsAccuracy is the cheapest form of customer retention available to a distributor.
“Are we overstaffed, understaffed, or just inefficient, and how would I even measure it?”
You measure output per hour by task and zone. Then the answer is arithmetic rather than opinion.
Because every task is issued and completed through the system, the work becomes measurable: picks per hour, lines per shift, and cost per order line, broken down by task and by temperature zone. That distinguishes the two situations that look identical on a payroll report: a team that's too small, and a team spending half its shift walking. Where it's the latter, optimised slotting and picking routes reclaim that capacity before you spend anything on headcount. Where it genuinely is a staffing question, you'll be making the case with your own numbers. It also gives you a defensible baseline: measure for a period, change one thing, measure again.
- Labour analytics by task and zonePicks per hour and cost per order line, chilled, frozen and ambient separated out.
- Staffing vs process, separatedTells you whether you're short of people or short of efficiency. They look the same on a payroll line.
- Capacity before headcountSlotting and route optimisation recover time already being paid for.
- A measurable baselineChange one variable, measure the effect, which is the basis of an ROI case that survives scrutiny.
“And how do I build a case for this that survives the board?”
From your operational data, not our averages, with the assumptions visible and yours to challenge.
We'd rather hand you a model you can interrogate than a headline percentage you'd have to take on trust. A margin review works through your own shrink, credit, write-off and labour figures, identifies which of them a WMS actually touches and which it doesn't, and sets out the licence and implementation cost against it, phased so that spend follows proven benefit rather than preceding it. Balloon One has also published a whitepaper on WMS ROI and a business case template if you'd rather start building the argument yourself before speaking to anyone.
- Your figures, not our averagesThe model is built on your numbers, with every assumption stated and challengeable.
- Honest about scopeWe'll tell you which losses a WMS won't touch — that's what makes the rest of the case credible.
- Phased investmentDelivered in stages, so the spend can follow demonstrated benefit.
- Board-ready outputA business case template and ROI framework you can put in a paper, not a sales deck.
Put your own numbers on it.
Four figures you'll already have to hand. Nothing is sent anywhere, and nothing is required to see the result. The arithmetic happens in your browser as you type.
These are your figures and your assumption. We haven't put a recovery percentage in your mouth: Balloon One makes no claim on this page about what a WMS would recover in your particular operation, because we don't yet know your operation, and a number you can't interrogate is worth nothing in a board paper. The slider is there so you can test the shape of the case at an assumption you'd be willing to defend. Establishing a defensible figure is exactly what the margin review is for.
The things you're actually wondering.
Where is all this shrink and waste cost actually coming from?
In a date-coded operation it's usually four things: stock that moved without being recorded, product that expired because newer stock was easier to reach, damage nobody logged, and counting errors that compound between stock takes. What they share is that none of them were recorded at the moment they happened. Scanner-confirmed movements and enforced FEFO address the causes; real-time accuracy is what lets you see which of the four you actually have, and in what proportion.
We're getting killed on credits and returns. What's driving them and how do we cut them?
Most begin as a picking error: wrong item, wrong quantity, wrong date code, or a mixed-temperature order. System-directed picking verifies product, location and batch before the line is confirmed, so the error doesn't reach the customer, which avoids the credit and everything attached to it. For claims that do arrive, lot-level despatch records let you test the claim instead of conceding it.
Are we overstaffed, understaffed, or just inefficient, and how would I even measure it?
You measure output per hour by task and zone, and cost per order line. That separates the two cases that look identical on a payroll report: too few people, versus people spending half a shift walking. If it's the second, slotting and route optimisation recover paid-for time before you spend on headcount. Either way you end up arguing from your own numbers rather than from impressions.
What's the actual ROI, and how do I build a case for it?
Honestly, nobody can quote you a credible figure before looking at your operation, which is why the calculator above uses your assumption rather than ours. A margin review produces the defensible version: your shrink, credit and labour figures, which of them a WMS genuinely affects, and the licence and implementation cost set against that. Balloon One also publishes a WMS ROI whitepaper and a business case template if you'd rather draft the argument first.
How quickly would this show up in the P&L?
It depends which leak is largest, and the sequencing is worth understanding. Picking accuracy and stock accuracy change as soon as scanner-guided work goes live, so credits and variance move first. Expiry write-off follows the rhythm of your stock cycle, since FEFO has to work through what you're already holding. Labour gains usually come last, because they follow slotting changes that need data to justify. We'd rather set that expectation now than have you explain a flat first quarter.
Do we have to replace everything at once?
No. We deliver in phases, and Infios is built to integrate with what you already run. Balloon One is a SAP Business One Gold Partner with strong EDI and systems-integration experience, so the WMS sits alongside your ERP and finance systems rather than forcing a rip-and-replace, which also means the spend can be staged.
Will this work across ambient, chilled and frozen?
Yes. Mixed-temperature operations are exactly what the food modules were built for, with FEFO and expiry rules and cold-chain monitoring configured per zone. Several of our clients run all three regimes into the major UK retailers and foodservice wholesalers on this platform.
Book a margin review.
A short, no-obligation session that turns the figures you just estimated into ones you will defend. We'll work through where your losses are actually created, which of them a WMS affects and which it doesn't, and what the investment case looks like against your own numbers.
What we'll cover- Your four leak points: shrink, waste, credits and returns, sized against your figures
- Cause, not total: which losses are recording gaps, which are process, which are buying
- Compliance overlap: where the same records cut margin loss and satisfy BRCGS and customer audits
- Labour: whether the evidence points to staffing or to efficiency
- The case: cost, phasing and the assumptions you will stand behind
Pick a time on the calendar. It takes about 30 seconds and a confirmation goes straight to your inbox. If a WMS is the wrong answer for where your margin is going, we will tell you so. Not ready to talk? Take the ROI whitepaper instead.