To evaluate the quality of the data captured on PPO, clients are generally interested in answers to questions such as the following:
- Is the Project Manager allocated at the correct time during the project Life Cycle?
- Have Risks been uploaded to the project?
- Does the project have a project plan?
- Do all Tasks have responsible persons identified?
- Does the project plan include Milestones?
- Have all open Issues been updated in the last 14 days?
- Has the project Budget been recorded?
- Are there any overdue Issues (Issues where the due date has passed)?
By making use of a custom entity, PPO has the ability to automatically calculate the answers to these questions and present them as Red or Green indicators. This allows users to quickly assess the quality of the data presented and then identify areas where improvements need to be made. The results of the Data Quality Indicator questions will be displayed on each project’s View page and can also be extracted in Reports at portfolio and project level.
Each project is also issued with an overall score and RAG indicator to enable comparison with other projects.
In addition PPO also has three standard Data Quality Indicator Reports which will be deployed as part of the implementation of the Data Quality Indicators. These reports are the:
Portfolio Data Quality Report
Project Data Quality Analysis Report
Project Data Quality Report
How do I go about setting this up?
Note: The setting up of Data Quality Indicators requires the PPO Support Team to set up an Event Handler to enable each project to automatically receive the list of Data Quality Indicators (see step 5 below). For more information on Event Handlers, see the following FAQ.
Step 1: Identify, define and specify the list of rules
The first step in setting up Data Quality Indicators is to decide which aspects of data quality will be tested for and define the rules and conditions.
The end result will look as follows:
This step is key to successfully implementing the Data Quality Indicators and the PPO Consulting Team can be approached for assistance. To do this, log a support call from the support portal and the Support Team will assign your call to a consultant.
Step 2: Implement and configure the Data Quality Indicators entity
To implement the Data Quality Indicators entity, go to Administration and click on Data Fields. Select one of the unused custom entities and click on Edit Entity. Specify a name and plural name for the entity and make sure it is in use before clicking on submit. For detailed information on editing entities, see the following knowledge base article.
The rules identified in Step 1 need to be added in a custom list item that will serve as the title of the quality indicator. This needs to be a short description of the rule that will be applied.
It will be useful to also set up a custom list for category, to allow users to group types of data quality indicators together.
Once these custom lists have been created, implement the following data fields on the Data Quality Indicators entity:
For full details on setting up custom lists, see the following knowledge base article. For more information on configuring data fields, please click on the link for the relevant knowledge base article.
Step 3: Set up a template project
The data quality indicators need to be set up on a template project. This will serve as a base from which the quality indicators will be copied onto all new projects.
To set up the quality indicators, create a template project if one does not already exist and go to the Data Quality Indicators entity for that project.
Then add a data quality indicator record for each type of rule to be checked. Also, populate the rule definition field with a detailed account of the rule.
Step 4: Set up test records and update the specification
Once the template project has been populated, set up the data quality indicators on four other (live) projects to serve as test data.
In addition set up two fields on the Projects entity: one for Data Quality Score and one for Data Quality RAG. Make the fields calculated, but only put the field key in the formula box. The technical team will implement the required functions in these fields as part of the next step.
The specification started in step 1 needs to be updated with the field keys (as set up in step 2) and with the expected results of the test data. This will assist the technical team to set up the data quality indicator rules.
Step 5: Log a call with the PPO Support Team
Log a support call with the PPO Support Team requesting the following actions be taken:
- Implement the data quality indicator rules (as per the specification);
- Copy the data quality indicators to all existing projects;
- Set up an event handler to copy over the data quality indicators from the template project to all projects created going forward;
- Implement the calculations for overall score and overall RAG on the project entity; and
- Deploy the standard Portfolio Data Quality Report and Project Data Quality Report
The above request will be completed in steps, with the support team providing updates on progress after each step has been completed.
Expected time frame and costs
Once the call is submitted as per step 5, the PPO Support Team will provide a quote for the implementation of the data quality indicators, which will depend on the complexity of the quality indicator rules. When steps 1 to 4 have been completed, the support team will implement the requests in step 5 within five working days.