In today’s fast-paced world of project management, communicating data is more important than ever for the project’s success. Whether you are working for a big company with teams spread across the globe or leading a small, local project, the way you share the project data can make or break your success.
Organizations need accurate and timely information in the project schedule to execute the project. When this schedule data is communicated well, everyone involved stays on the same page, informed, and able to make smart decisions together.
In this article, we will explore why communicating schedule data is so important in projects with focus on large-scale projects, commonly managed within the Primavera ecosystem. We will look at how it impacts decision-making, keeps stakeholders engaged, and contributes to overall project success. By sharing best practices and common mistakes to avoid, we hope to help project managers and team members improve their data communication and lead their projects to successful outcomes.
The Project Schedule – XER Files
XER files, or files with the extension .xer, are a type of data file primarily associated with Oracle Primavera P6, a popular project management software. These project files contain data related to the project timeline, such as activities, resources, and costs.
Data is present in a specially structured format. Hence, these files serve to facilitate the exchange of project data between different users and Primavera systems. XER files help project managers to keep everyone informed of the project status.
Apart from the applications that are part of the Primavera ecosystem such as P6 and OPC, a third-party software solution, ScheduleReader can be used to open an XER file and view the project information inside.
In addition to ScheduleReader, several applications designed to improve the workflow within this ecosystem are available on the market, including ScheduleCleaner.
Introduction to ScheduleCleaner
ScheduleCleaner is another specialized software tool designed to streamline the process of controlling the shared project data, particularly the data in files created with Primavera P6. It helps project managers and schedulers manage their project data more effectively by allowing them to remove or mask sensitive information from existing XER and XML files before sharing them with stakeholders. This ensures that only relevant and necessary information is communicated, maintaining data privacy and clarity.
The key features of ScheduleCleaner include the ability to delete or mask the data that is indirectly connected with the project architecture (existing codes, existing units, existing rates, existing prices, etc.), allowing users to standardize schedules according to specific projects or organizational requirements.
This software is particularly useful for large projects where maintaining data integrity and privacy is crucial, and for organizations that regularly share schedule updates with clients, contractors, or other external parties.
Overall, ScheduleCleaner enhances the efficiency and security of schedule management, contributing to smoother project execution and better communication.
Step-by-Step Guide to Cleaning XER Files with ScheduleCleaner
- Step 1: Open ScheduleCleaner
Launch ScheduleCleaner: Open the ScheduleCleaner application on your computer.
- Step 2: Import the XER File
Import File: Go to File > Add File.
Select Add File: Browse to the location of your XER file and select it
Alternative – Drag and drop the XER file from a folder on your PC inside the open ScheduleCleaner application window.
- Step 3: Set Up the Workspace
Select Cleaning Options: In the main interface, you will see a “Clean” option. Navigate to the Quick window under the “Clean” option. The general settings in the “quick clean” include removing specific data such as:
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- Removing All Risks
- Removing All Progress
- Removing All POBS data
- Removing All Pricing
- Removing All Costs
- Removing All Rates
- Removing All Units
- Converting Global to Project Calendars
- Converting Global/EPS to Project Activity Codes
- Converting EPS to Global Activity Codes
- Changing the output file version number
- Adding Prefix/Suffix to activities
Additional data categories for removal can be selected through the customization window. To customize the settings, check or uncheck the boxes according to the data you want to remove.
- Step 4: Execute the Cleaning Process
Set the settings for the new, cleaned file: Select the suffix of the cleaned file, and the output folder where the new file will be stored.
Start Cleaning: Click the green arrow like “Ready to Clean” button to initiate the data removal process.
Clean file: ScheduleCleaner will create a copy of your original schedule, with the chosen modified settings applied to the new schedule file, located on the same location where the original project file resides.
In the following video, the cleaning process is thoroughly explained through multiple examples by one of the leading global Primavera P6 educators, Michael Lepage from Plan Academy:
Automation and working with multiple project files
ScheduleCleaner also allows users to create templates with a pre-made set of modifications. These templates can then be re-used and applied to one or multiple project files, allowing users to save time and automate the cleaning process.
The following how to videos explain the processes of working with templates and using the “Batch clean” feature.
Techniques for validating cleaned data
The application ScheduleReader can be used to preview the data in the XER and XML schedules.
You can simultaneously open several instances of the application and perform side by side comparisons of two schedules on your monitor, thus easily validating the difference between data from the original and modified schedule.
You can learn more about this application and download it during a free 15-day trial through the official website.
General Practices for Controlling Project Data
Effective project data management is crucial for ensuring the success of any project. By following best practices, project managers can maintain data accuracy, improve team collaboration, and enhance decision-making processes.
Procedures for Data Management
The following procedural recommendations can help ensure that the information used for decision-making is reliable and up to date.
Regular Data Review: You can ensure that schedule data is accurate and free of errors by putting in place a regular procedure for checking it and looking for any discrepancies or out-of-date information. Maintaining a regular update on the status of your project guarantees that everyone in the team is operating with the most recent data, which is also essential for making wise decisions.
Data Cleaning: Cleaning data involves removing any inaccuracies, duplications, or irrelevant information from the project database. Establish a consistent process for data cleaning that includes identifying and correcting errors, filling in missing data, and ensuring that all data entries adhere to the same standards and formats. This process not only improves data quality but also makes it easier to analyze and use effectively.
Data Backup and Recovery: Implement a robust system for backing up project data regularly. This ensures that you can recover valuable information in case of data loss due to technical issues or human error. Establish clear protocols for data recovery to minimize downtime and ensure continuity.
Access Control: Establish and oversee who has access to certain project data kinds. This can help with security and integrity of data.
Training Team Members on Schedule Data Management
Developing a collaborative work environment and preserving project data integrity depends on your team having the knowledge and abilities to handle schedule data efficiently. The suggestions listed below may be useful:
Comprehensive Training Programs: Develop and implement training programs that cover all aspects of schedule data management. This includes understanding the project management software being used, best practices for data entry, and procedures for reviewing and cleaning data. Training should be ongoing, with regular refresher and updates as new tools or methods are introduced.
Use of Tools and Software: Train team members on the effective use of project management tools and software, such as Primavera P6 and ScheduleCleaner. Provide hands-on training sessions and resources to help them become proficient in using these tools to manage schedule data efficiently.
Promoting Collaboration and Communication: Create an atmosphere where team members are at ease sharing knowledge regarding scheduling data management. Frequent team meetings and collaboration tools may make sure that information is shared, and data management problems are quickly resolved.
Monitoring and Providing Feedback: Regularly monitor the data management activities of team members and provide constructive feedback. Recognize good practices and address any issues or mistakes to help team members improve their data management skills continuously.
By implementing these best practices for controlling project data, organizations can ensure that their project information remains accurate, secure, and useful throughout the project lifecycle. Proper data management and thorough training of team members are key to achieving project success and fostering a collaborative and efficient work environment.
Clean and accurate data – The building blocks of successful projects
In conclusion, maintaining clean data is fundamental to the success of any project. Clean data ensures that project managers and team members can make informed decisions, track progress accurately, and communicate effectively with stakeholders. By implementing regular data review and cleaning procedures, organizations can prevent errors, reduce risks, and enhance overall project performance.
Using software tools such as ScheduleCleaner can also facilitate effective data management.
It is equally crucial to train team members in schedule data management since it gives them the abilities and know-how needed to handle data efficiently. A proficient team plays a crucial role in upholding data integrity, cultivating a climate of responsibility and cooperation, and eventually propelling the project toward its objectives.