In a prior post, Data Double Talk, we asked three key questions:
- How accurately does our data reflect the organization?
- How consistent is data between data warehouses?
- Is our data both relevant and useful?
You evaluated the questions and I’m certain a few eyebrows were raised. The follow-up question has now transformed from understanding to resolution:
What can we do to clean the data for an efficient load into Workday?
As Workday will likely become, or already is, a centralized hub for your information, it is critical to have accurate and precise data. Oftentimes we will work with customers who have this in mind when switching to Workday. For the first few loads, some customers face difficulty translating their data due to incomplete, improperly formatted, duplicated, or poorly maintained information. These problems happen to every company at some point, but don't worry - there are a few steps you can perform to help cleanse your data while preparing it for a Workday implementation.
Step 1: Copy your existing data. This is an important step in the beginning. Initially, any data modifications should be made here to prevent unforeseen problems (such as deletion or deprecation of good data). From this data copy, analytics can be performed to determine the effectiveness of your data cleansing plan.
Step 2: Plan the migration. Work with your consulting partner to determine what information you want to bring into Workday. Then, develop a plan to review and correct this information internally. As tenants are built and you move closer to completing the Workday implementation, the quality of data is expected to increase.
Step 3: Build the right testing team. Build a team to efficiently work through this process. This team should consist of those you trust to not only manipulate data in the system, but also those who have the ability to make decisions as necessary when correcting data.
Step 4: Look for Trouble. Develop reports or methods to find problematic areas in your system. Duplicate employees or SSNs, birth dates before 1900, etc.
Step 5: Soft Launch. Execute your plan, preferably on a small scale to start. This is the step where you get your hands dirty and improve the data in your system.
Step 6: Revise and Repeat. Both during and after these data cleansing sessions, your plan should be evolving to include any additional items or address problems you’ve encountered. The goal is to continuously improve the data each time which will result in better data for a Workday implementation.
Following these six steps and molding them to fit your specific organization will help ensure you’re prepared for a move to Workday. Additionally, it will help you resolve the three questions we raised previously, and allow you have confidence in your data being up to date.