How good is the data in your earned value management system (EVMS)? The quality of data influences the amount of confidence users and clients have in your reporting. The data underpins your ability to monitor and control the project as well, so beyond reporting, there is a very practical reason for ensuring that your EVMS and the associated processes are as robust as possible.
We support a lot of earned value management system implementations and also carry out assurance and reviews for clients that have a system in place already. Often, improving your data quality in an EVMS is straightforward once you have identified any issues or limitations in the way the system works.
In this article, we’ll share a few areas to consider that impact the data quality in an EVMS.
1. Data formatting
The formatting of your data is crucial for making sure that the reporting out of your system is accurate, standardized and understandable. For example, make sure that dates and currencies are set up in a standard way and that there are naming conventions where required.
A surprising number of errors can be quickly addressed by focusing on formatting. It’s worth spending some time defining what fields are for and how they are to be used so that the team understands how to enter data in a way compatible with data quality.
2. Batch processing
Batch processing can save so much time, but only if it is a seamless process! When we worked with Wood, a global leader in the delivery of project, engineering and technical services to energy and industrial markets, they asked us to review the issues that were stopping the back processing from being as efficient as it should be.
When a batch process doesn’t run as planned, your team will spend valuable time trying to troubleshoot the problem and manually run, recreate or put together the data that is required while they are waiting for the batch process issue to be resolved. That’s a waste of time and effort: it’s better to resolve the problems at the root and make sure people understand what causes critical issues so they can be avoided in future.
3. Reporting templates
The out of the box reports provide a good starting point, but if you want to go further, tailoring reports in Primavera P6 or Deltek Cobra is the answer. Custom reports can be set up to show stakeholders exactly what they want. They can be scheduled to run at a cadence that best suits you and the team.
Custom reports improve data quality because you can make sure that data is presented in a consistent format. For example, they can be set up to use the same fields in every report, so that – to take a simple example – ‘date’ means the same thing across a range of reports. Reporting timelines can be standardized to remove any conflict between reporting across different periods.
EVMS reporting templates provide flexibility in a customized way. You can better support your clients and internal stakeholders by making sure they have the information they need in the format they prefer.
4. Error reporting
Another area where Wood asked for our support was setting up a more robust error reporting and logging process. It would be great to think that data quality issues could be resolved once and for all, but the truth is that there will be errors. It’s inevitable, with many users, each entering new data week after week, some of whom will probably be new to using the system.
An efficient error reporting process allows the team to review and correct problems quickly, working with end users to ensure data errors are corrected at source.
5. Data integration
A full EVMS pulls data from a range of sources, including Oracle Primavera P6 and Deltek Cobra, and you may have other applications in your IT estate that support project delivery and reporting. We created templates for flat file program data integration for Wood. Our team also made sure that data sources providing input to the monthly reporting cycle were aligned with Deltek Cobra’s requirements.
Data integration is an area where we often find quality issues. It’s important to understand the data sources, where there could be conflicts, how data sources interface with each other and how data is mapped between the systems. If you put garbage into your EVMS, you’ll get garbage out. Make sure the data in source systems meets your quality standards before you start.
Data integration supports reporting requirements to ensure your teams have access to the information they need to track and monitor project performance using earned value analysis.
Improving data quality in an EVMS has an immediate, noticeable effect. The right data can inform project decisions and ensure work is carried out in the most effective way, for example by reducing monthly recurring costs. It improves customer confidence and saves your team time and rework. When was the last time you looked at your data quality?