Lottery reconciliation business case

Automate the work behind the control.

LottoReco helps retailers establish daily lottery control or reduce the work behind an existing reconciliation process—while preserving management review.

The operating change

Same control. Fewer manual steps.

The business case starts with the stores' current position: no daily audit, spreadsheets, or included back-office lottery accounting.

Manual exampleRepeated every shift
1Read ticket countsCollect pack and bin activity
2Complete spreadsheetCalculate lottery sales
3Enter back officeRe-key shift totals
4Match to POSCompare recorded sales
5Review differencesInvestigate exceptions
With LottoRecoAutomated reconciliation
1Capture activityScanner, mobile, or supported data source
2Reconcile automaticallyLottery activity matched with POS data
3Review exceptionsManagement keeps oversight
Observed customer result
45 min→under 5

Reported closing time for a supported workflow.

Customer statement
“LottoReco cut our closing time from 45 minutes to just 5 minutes.”
Balraj, Owner · Chevron Gas · Mountain View, California

Management view

What changes—and what does not.

Work removed

−
Shift-end spreadsheet preparationLess calculation and transcription by store staff.
−
Duplicate entry into back-office toolsFewer handoffs between the count, worksheet, and system.
−
Routine line-by-line comparisonAttention moves from every row to the exceptions.

Control retained

✓
POS comparisonLottery activity remains matched against recorded sales.
✓
Difference visibilityManagers can still identify and investigate variances.
✓
Store and multi-store oversightResults remain reviewable across locations.

Business case

See the annual value.

Start with the process your stores use today, then replace the example values with measured labor or loss-exposure assumptions.

No daily audit means no reliable record when a loss is found. Missing packs and small discrepancies can accumulate, while limited pack, shift, and employee history can leave owners without the evidence needed to investigate and act consistently.

No-audit risk assumptions

Adjust these numbersEnter a planning range for monthly loss exposure, then validate it during the pilot.
Estimated monthly loss exposure

Cost-benefit result

Net annual benefit range
$1,900–$5,500
Potential annual ROI380%–1,100%
Potential loss avoided less annual software cost
Annual loss exposure$2,400–$6,000
Potential annual loss avoided$2,400–$6,000
Annual software cost$500
Benefit / cost4.8×–12.0×
Estimated payback1–2.5 months

Formula: locations × monthly exposure × 12 × expected reduction, less annual software cost. Potential ROI = net annual benefit ÷ annual software cost. This scenario assumes the entered reduction is achieved and should be validated during the pilot.

At these assumptions, one location has a potential net annual benefit of $1,900–$5,500.
Beyond the calculation

Additional operational value from LottoReco

01Earlier discrepancy detection

Surface over/short issues, missing packs, and payout differences while the shift is still recent.

02Instant investigation

Move from a flagged exception to relevant shift and inventory history without rebuilding the day from separate records.

03Clearer accountability

Keep store, shift, and follow-up information together for manager review.

04Stronger inventory control

Track scratch-ticket packs and inventory movement with a consistent daily record.

05Multi-store visibility

See which locations are complete and which exceptions need attention first.

Recommended approval

Prove it against the current process.

A pilot creates a defensible decision using actual store labor, exception rates, and manager experience.

01 · BASELINE

Measure today

Record closing time, settlement work, corrections, and unresolved differences under the current process.

02 · PILOT

Run in selected stores

Use representative locations and keep the same review expectations.

03 · DECIDE

Review measured results

Compare labor saved, reconciliation quality, and staff adoption before rollout.

Use your stores to build the final case.

Start with a measured pilot, validate the assumptions, and take actual results to the board.