How to Prepare Your Data Before an Epicor Kinetic Migration
The technical part of moving data into Epicor Kinetic is not what makes a migration succeed or fail. The preparation is. A migration built on clean, well-scoped data goes live on time and works. A migration built on years of unexamined legacy data goes live late, runs slow, and creates problems that take months to unwind.
This guide walks through how to prepare your data properly: what to leave behind, what to clean, how to map it, and how to test it before you commit.
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Why Data Preparation Decides the Outcome of Your Migration
Bad data does not improve when it moves to a new system. It gets amplified. Duplicate customer records, obsolete part numbers, and inconsistent naming conventions that were a minor annoyance in your old system become active problems in Kinetic, where more processes depend on that data being accurate. Every downstream function, from MRP to job costing to reporting, is only as reliable as the data feeding it.
Poor data preparation is the most common reason ERP migrations run late or disappoint after go-live. The transfer itself is a solved technical problem. The work that determines success happens before the transfer: deciding what moves, fixing what is broken, and confirming it all lines up correctly in the new system.
1. Audit and Inventory Your Existing Data
Before you touch anything, build a complete picture of what you have. A data inventory answers three questions: what data exists, where it lives, and what state it is in.
In a manufacturing environment, this means accounting for customer and supplier records, inventory and part masters, bills of materials, routings, open and historical orders, and financial data. Much of it lives in your current ERP, but some of it almost always lives elsewhere: spreadsheets, shared drives, a standalone quoting tool, someone’s desktop. The inventory surfaces all of it and tells you what you are actually working with before you start making decisions about it.
2. Decide What Not to Migrate
The most important step in a data migration is also the one most organizations skip: deciding what to leave behind.
The instinct is to move everything. Years of transaction history, every customer record, every closed job, every attachment. That instinct is a mistake. Importing everything into Kinetic causes slow performance, schema conflicts, and inflated licensing and storage costs. A new system loaded with a decade of dead data is slower and harder to work with than one loaded with only what the business actually uses.
The better approach is to separate active data from historical data. Active data, the customers, parts, suppliers, open orders, and current financial records your team uses day to day, gets migrated into Kinetic. Historical data that you need to keep for compliance or reference but do not use operationally gets archived in a secure, searchable location outside the ERP. This keeps Kinetic clean and fast while preserving every record you are legally or operationally required to retain.
This one decision, made early, shapes everything that follows. It reduces the volume of data you need to clean, shortens the migration timeline, and keeps your new system performing the way it should.
3. Clean, Standardize, and Validate
Once you know what you have and what you are keeping, the data hygiene work begins. This is three distinct steps, done in order.
Clean
Remove duplicates, obsolete records, and known errors. The customer who has not ordered in fifteen years, the part number that was superseded three revisions ago, the supplier you stopped using in 2019. If it is not active and you do not need it operationally, it does not belong in the migration set.
Standardization
Apply uniform formats and naming conventions across the data. Part numbering, unit of measure, address formats, customer naming. Inconsistency that your old system tolerated will create duplicate records and matching errors in Kinetic. Standardizing before migration is far easier than fixing it after.
Validate
Cross-check the data for accuracy before it moves, not after. Confirm that quantities, costs, and relationships between records are correct. Validation before migration catches problems while they are cheap to fix. Validation after go-live means fixing them in a live production system under pressure.
4. Map Your Data to Epicor Kinetic
Data mapping is the process of aligning your legacy data fields to Kinetic’s structure. Every field in your old system needs a defined home in the new one, and the two rarely line up perfectly.
This step tends to surface problems you did not know you had. Fields that were used inconsistently, data that was stored in the wrong place, information that exists in your old system but has no natural equivalent in Kinetic. Working through the mapping carefully is how you catch these mismatches before they become migration errors. It is detailed work, and it is worth doing properly, because a mapping mistake replicated across thousands of records is painful to correct later.
5. Choose Your Migration Approach
There are three common approaches to moving the data, and the right one depends on your size and complexity.
A big bang migration moves all data at once in a single cutover. It suits smaller operations with less complex data, and it is faster, but it carries more risk because everything happens at once.
A phased migration transfers data in stages, which allows testing and adjustment between phases and reduces risk, but takes longer.
A hybrid approach combines the two, moving critical master data first and layering in the rest in stages, balancing speed against safety.
Most mid-sized manufacturers land on some version of phased or hybrid, because the reduced risk is usually worth the extra time.
6. Test Before You Commit
No data migration should go live without testing first. Run the migration on a small, representative set of data in a test environment and check the results carefully. Did the records land in the right place? Are the relationships between customers, orders, and parts intact? Do the numbers reconcile?
Plan for multiple rounds. The first test almost always surfaces issues, and you want to find them in a sandbox, not in production on go-live day. Testing is what turns a migration plan into a migration you can trust.
How EC Solutions Approaches Data Migration
At EC Solutions, when we start a data migration with a manufacturer, the first thing we do is build a complete inventory of the data: what exists, where it lives, and what state it is in. Most manufacturers have more data spread across more places than they expect, and you cannot make good decisions about any of it until you can see all of it.
That inventory sets up the conversation that matters most: what to move and what to leave behind. Clients often assume everything has to come across, and they are surprised to hear that moving fifteen years of closed jobs and inactive customers into Kinetic is actively bad for the system they are about to rely on. Separating what gets migrated from what gets archived shapes the cost, the timeline, and the performance of the finished system, which is why we settle it early rather than late.
We are also honest about data quality. Most manufacturers have more data problems than they realize, and those problems only become visible once the inventory and cleaning work begins. A migration timeline that assumes the data is clean is a timeline that slips. We would rather set a realistic schedule that accounts for the cleaning work up front than discover the mess halfway through and blow past the go-live date.
None of this is glamorous work. But it is the difference between a Kinetic system your team trusts from day one and one they spend the first year second-guessing. If you are planning a move to Kinetic and want to understand what your data will actually require, that is a conversation worth having early.