# Epicor Kinetic Data Load Effort Calculator > Source: https://netray.co/tools/epicor-kinetic-data-load-effort-calculator > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: Free Tools ## Short answer Estimate total data migration hours for an Epicor project from record counts, error rate and number of test cycles. ## Category epicor ## Erp Epicor Kinetic ## Audience - Epicor project manager - Epicor consultant - Data migration lead ## Tool **Kind:** calculator **Inputs:** #### Records to migrate **Key:** records **Type:** number **Default:** 60000 **Min:** 0 **Step:** 1000 **Unit:** records **Help:** Total across parts, partners, BOMs, balances and open documents. #### Number of entities **Key:** entities **Type:** number **Default:** 12 **Min:** 1 **Step:** 1 **Unit:** entities **Help:** Parts, customers, suppliers, BOM, open orders, balances and so on. #### Expected error rate first load **Key:** error_pct **Type:** slider **Default:** 8 **Min:** 0 **Max:** 40 **Step:** 1 **Unit:** % #### Fix effort per 100 errors **Key:** fix_per_100 **Type:** number **Default:** 1.5 **Min:** 0 **Step:** 0.1 **Unit:** hours #### Mapping hours per entity **Key:** map_per_entity **Type:** number **Default:** 12 **Min:** 0 **Step:** 1 **Unit:** hours #### Test load cycles **Key:** cycles **Type:** slider **Default:** 3 **Min:** 1 **Max:** 8 **Step:** 1 **Unit:** cycles #### Hours per test cycle **Key:** cycle_hours **Type:** number **Default:** 16 **Min:** 0 **Step:** 1 **Unit:** hours #### Blended hourly rate **Key:** rate **Type:** number **Default:** 95 **Min:** 0 **Step:** 5 **Unit:** per hour **Outputs:** #### Mapping hours **Key:** mapping **Expr:** entities * map_per_entity **Format:** number #### Errors in first load **Key:** errors **Expr:** records * error_pct / 100 **Format:** integer #### Cleansing hours **Key:** cleanse **Expr:** errors / 100 * fix_per_100 **Format:** number **Description:** Assumes later cycles fix most remaining errors at lower volume, so only the first-load errors are counted. #### Test cycle hours **Key:** testing **Expr:** cycles * cycle_hours **Format:** number #### Total migration hours **Key:** total_hours **Expr:** mapping + cleanse + testing **Format:** number **Primary:** true #### Estimated labour cost **Key:** cost **Expr:** total_hours * rate **Format:** currency **Primary:** true **Chart:** #### Total hours vs expected error rate **Type:** line **X:** error_pct **From:** 0 **To:** 40 **Steps:** 20 **Series:** - total_hours **Disclaimer:** A planning model with simple assumptions. Real effort depends on data quality, tooling and team experience, so calibrate the inputs from your own test loads. ## Content **Intro:** Data migration is the part of an ERP project most often underestimated. This calculator turns record counts and error assumptions into a transparent hour estimate that you can challenge and refine. **Sections:** #### How to use it **Body:** Enter your record volume, the number of entities, the expected first-load error rate and your cost per hour. Adjust mapping hours per entity and fix effort based on how clean your data is. The result shows mapping, cleansing and test hours separately, plus the total and cost. Use the chart to see how sensitive the plan is to error rate. **Bullets:** - Count entities, not tables - Use a test sample to measure the real error rate - Recalculate after each test cycle #### The model behind it **Body:** Total hours equals mapping plus cleansing plus testing. Mapping is entities times hours per entity. Cleansing is first-load errors divided by one hundred, times the fix effort per hundred errors. Testing is the number of cycles times hours per cycle. It is deliberately simple so assumptions can be read and argued about; it excludes training, cutover weekend time and project management. #### Reading the results **Body:** Look at which component dominates. If cleansing is the largest, investing in profiling and de-duplication before the first load will pay off. If testing dominates, automate your reconciliation checks. The chart is usually steep: moving from a 5 percent to a 20 percent error rate can change total effort noticeably, which is why sampling early matters. #### Common mistakes **Body:** Estimates fail when teams assume a clean source and never test. They also assume one test cycle, when three or more are typical for complex data. Treat the output as a starting range and revisit it once you have seen real errors. **Bullets:** - Assuming error rate is near zero - Leaving out opening balance reconciliation - Not budgeting for business-side data owners' time **Cta:** If your estimate shows cleansing as the biggest cost, we can help with a private profiling and de-duplication assistant that runs on your own infrastructure. **Faq:** #### What does the error rate mean? **Answer:** It is the share of records that fail validation or need manual correction in the first load. Measure it by loading a representative sample into a test environment rather than guessing. #### Does it include go-live weekend effort? **Answer:** No. It covers mapping, cleansing and test cycles. Plan cutover time separately using a cutover plan, since it depends on load volumes and reconciliation steps. #### Which hourly rate should I use? **Answer:** Use a blended rate across consultants and internal staff who do the work. If internal time is not charged, enter a lower rate and treat the output as external cost only. #### How accurate is the estimate? **Answer:** It is a planning range. Accuracy improves when you replace defaults with measurements from your own test loads, especially error rate, fix effort and hours per cycle. ## Search terms epicor data migration effort, epicor data conversion estimate, erp data migration hours calculator, epicor implementation estimate, data cleansing effort calculator, epicor project data load planning --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json