Data Migration is often the bottleneck which busts the budget and shatters the schedule early in any implementation project. Problems encountered during data migration often force your staff to maintain both the new systems and the legacy system for a period of time. This parallel processing is inefficient and unnecessary if data migration tasks are effectively automated and easily replicated. Unfortunately, this is not always the case. Why?
To answer this question we must first define data migration and understand the tasks involved.
Data migration is the process of transferring current and historical data from one or more legacy systems to a new, more efficient and more effective system. The tasks involved typically include data extraction, data cleansing, data mapping, data loading and data validation, hereafter referred to as EXTRACT>CLEAN>MAP>LOAD>VALIDATE.
A typical payroll implementation project will require that the EXTRACT>CLEAN>MAP>LOAD>VALIDATE process be executed multiple times, often 3 to 4 times. At minimum, there will be two legacy data migration cycles: one during the Build & Validate phase and one during the Deploy phase. The latter occurs after the latest payroll processing cycle in the old system and before the first payroll cycle in the new system. This final data migration cycle is designed to provide a final synchronization of the new payroll system to the legacy system and often must happen within a one or two week window.
Now, back to the question of why this data migration process can be a major project bottleneck and source of budget overruns and schedule extensions. The answer can be summed in two words – dirty data. More specifically, the data cleansing tasks often are not automated, or even documented, and therefore not easily repeatable. Each successive EXTRACT>CLEAN>MAP>LOAD>VALIDATE cycle wastes time and money re-cleaning data, usually manually, which were cleaned, usually manually, in the previous cycle. This rework usually means that the final data load cannot be accomplished in the window available between the last payroll cycle in the old system and the first payroll cycle in the new system resulting in the duplication of efforts to maintain, or synchronize, the two systems.
How can you avoid the dirty data trap?
- Don’t rely on your implementation partner to clean your legacy data if you don’t have to. You and your expert staff are aware of dirty data in your legacy system before you even decided to implement a new payroll system. Establish an in-house team of IT and Payroll experts to clean and correct the data in the legacy system before the implementation project begins.
- If you do not have the capability or bandwidth to clean the legacy data in-house, tell your implementation partner upfront, during the Initiate or Discovery phase of the project. Be prepared to accept additional cost and time during the early phases of the project for your implementation partner to work with your IT and Payroll staff to develop a programmatic system to clean and map your data. This is the classic example of “pay me now, or pay me later.” If you don’t spend the time and money up-front, you will spend it on the back-end in the form of rework, budget overruns, and schedule slippages. The back-end costs are even higher because they include project team frustration and loss of project momentum. If you go live with dirty data you risk alienating employees and possibly even incur additional financial liability.
- Be prepared to allocate sufficient staff resources to ensure a comprehensive validation of the migrated data. Remember, the accuracy of your data is always your responsibility. Take the data migration task seriously and don’t assume it is a minor effort.
In conclusion, your implementation partner should be able to guide you through these important project tasks and help you avoid the dirty data trap. At RSM McGladrey, we offer a proven
By: David Funk, RSM McGladrey – Microsoft Dynamics Certified Payroll Implementation Partner
Look for future blogs from David Funk on the following Payroll Implementation topics:
- Prepare your staff
- Standardize pay policies
- Develop a realistic schedule
- Synchronize integrated systems