KENYA · GUIDE 0566 · EDITION 4.2
Data entry service in Kenya: Operations and Quality Checks
Deliver the agreed result consistently
Enter a defined data batch using agreed source fields, validation rules, duplicate handling, confidentiality controls, and an exception queue for records that cannot be interpreted reliably from the supplied source material.
The operating sequence for this offer is:
- Agree a field dictionary, source batch count and permitted access, then validate a small sample and define how ambiguity will be handled.
- Enter supported information consistently, log unclear or missing values and prevent unapproved changes to the original records while processing the batch.
- Reconcile row counts and key fields, report exceptions and provide the agreed checked output without claiming an unaudited accuracy percentage.
Put acceptance into the job record
Row count and key fields reconcile to the source; exceptions are not silently filled.
Ask the client to reconcile totals and sample entries back to source records, deliberately including ambiguous dates, repeated names, missing values, and unusual amounts before accepting the full entry approach proposed.
Inspect at the point where a correction is still possible, then again at handover. Record rejected or incomplete output separately from accepted output. A completed task is not automatically an accepted task, and an invoice does not establish that the customer received the right result.
Measure real capacity
Time preparation, the main operation, transport, cleaning, approvals and correction as applicable. The slowest stage determines how much you can promise. Where two orders need the same person, space or equipment at the same time, resolve the conflict before confirming both deadlines. An additional enquiry should not erase a commitment already made.
| Operating checkpoint | Evidence for this business |
|---|---|
| Before starting | Enter a defined data batch using agreed source fields, validation rules, duplicate handling, confidentiality controls, and an exception queue for records that cannot be interpreted reliably from the supplied source material. |
| During delivery | Enter supported information consistently, log unclear or missing values and prevent unapproved changes to the original records while processing the batch. |
| At acceptance | Ask the client to reconcile totals and sample entries back to source records, deliberately including ambiguous dates, repeated names, missing values, and unusual amounts before accepting the full entry approach proposed. |
| At the pilot review | Maintain batch references, entered record counts, validation failures, ambiguous fields, duplicate decisions, sampled errors, client clarifications, and correction totals so acceptance rests on traceable quality rather than volume alone at project completion. |
Keep a correction and escalation rule
When inputs, access, specifications or customer instructions change, pause the affected work and confirm the effect on time and cost. Do not quietly lower the acceptance standard to avoid a delayed delivery. Keep rework caused by your error distinct from a customer-requested change of scope and agree the remedy clearly.
A complete-looking dataset can be wrong when blanks become invented values or duplicate customers are merged merely because names match, destroying distinctions the business depends on for its actual work and reporting.
Retain the minimum records needed to investigate a complaint without disclosing unrelated personal information. Use measured delivery and actual acceptance as the basis for expanding capacity, rather than the maximum theoretical output of a tool or production line.
Operating control points for this exact offer
| Sequence | Work method | Release checkpoint |
|---|---|---|
| 1 | Define date format, quantity unit and code fields using five sample rows. | Do not mix cartons and pieces in one quantity column without an explicit unit field or conversion approved by client. |
| 2 | Set supplier/item/document references as text before entry/import. | Test 00127 and a long reference; changing display after zeros were lost cannot recover the original reliably. |
| 3 | Enter page/line references so each row can be checked against source. | Unreadable quantities go to a query log rather than a guessed numeric cell. |
| 4 | Re-read all codes/quantities against source and use row counts/control totals by page where meaningful. | A matching grand total does not prove individual rows are correct; swapped quantities can cancel out. |
| 5 | Account for 200 source rows as entered, duplicates awaiting client decision or unresolved queries. | Open the final workbook and any CSV through the intended import route to confirm identifiers remain intact. |
Do not substitute a tick for an observation: record the count, measurement, approved sample or evidence reference used at each checkpoint. Mark unresolved work as held and identify who can approve the recheck.
Diagnose a failure before repeating it
| Observed symptom to investigate | Check the cause | Proposed response |
|---|---|---|
| 00127 becomes 127 | Check cell type and import route. | Re-import from original source as text; do not pad all codes blindly. |
| Page total differs | Compare source rows and entered quantities on that page. | Locate omissions/duplicates and recheck individual values. |
| Two rows share a reference | Check whether source repeats a transaction or entry duplicated it. | Ask client for the rule and retain provenance before removal. |
These are diagnostic prompts, not proof of the cause in a real incident. Separate suspect output, record any correction and repeat the relevant acceptance check. Link rejected units, rework time, replacement materials, customer credits and collection delays to the actual job result.