Industry insight

7 Challenges Food Manufacturers Face and How Valdata Solves Them

These are the seven issues most common to food producers. Each section shows the impact, how Valdata resolves it, and a short checklist to guide evaluation.

1. Recipe control and version drift

Impact

Small recipe edits that are not governed lead to inconsistent results, label mismatch, and rework. Teams cannot tell which version ran on which day.

How Valdata helps

Valdata manages recipes with versions, approvals, and controlled change. Operators run the approved version only. Labels and claims are generated from the source recipe so what runs is what goes on the label.

Checklist: version approval, change audit, label from source, role-based access

2. Incomplete traceability and slow recall drills

Impact

Lot lookups take too long. Forward and reverse links are missing or live in spreadsheets. Mock recalls turn into a scramble.

How Valdata helps

Valdata records full lot genealogy from raw to finished and from finished back to source. Teams can filter by lot, date, or customer and export the report in minutes.

Checklist: full genealogy, instant lot filter, drill and export, customer-ready format

3. Expiry control and waste from poor rotation

Impact

Materials go out of date in storage or sit in the wrong location. Teams discover the problem after the write off.

How Valdata helps

Valdata tracks lots with expiry and uses first to expire / first out logic (FEFO). Alerts show what will expire soon, where it is, and what is reserved for work orders.

Checklist: expiry dates, first expire / first out, reserve for orders, aging alerts

4. Quality records scattered across systems

Impact

Quality checks live in many places. During a customer visit, it takes time to gather the evidence that a lot met the plan.

How Valdata helps

Valdata links each quality plan to its lots and batches. Results are stored with pass or fail rules and can generate a certificate from real test data (CofA).

Checklist: quality plan link to lot, result limits, pass or fail rules, certificate from test data

5. Manual data entry at scales and on the line

Impact

Operators record weights by hand. This creates delays and transcription errors that affect yield and compliance.

How Valdata helps

Valdata connects directly to most makes and models of scales. Weights flow into the batch record without manual entry so data is reliable and timely.

Checklist: direct scale connection, automatic capture, batch record link, exception alerts

6. Production planning that misses real constraints

Impact

Schedules look fine on paper but fail on the floor due to changeover time, allergen rules, or missing materials.

How Valdata helps

Valdata planning considers recipes, lots, allergens, and expiry. Teams plan with real constraints and reserve materials so lines run without last minute changes.

Checklist: line and allergen rules, changeover time, reserve lots, shortage alerts

7. Margin drift from yield loss and rework

Impact

Actual cost is higher than planned. Loss comes from incorrect picks, scrap, label errors, and rework that is not measured.

How Valdata helps

Valdata tracks standard and actual with yield and variance. Reports show where loss occurs so teams can focus on the steps that move the margin.

Checklist: actual versus standard, yield variance, scrap capture, exception review

Next steps

Use the checklists above during demos and pilots. Run a pilot with your actual recipes and labels on one or two lines and measure the improvement in yield and compliance.

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