Improve data quality in ServiceNow part 2

 

Improve data quality in SN part 2

Intro

Welcome back.

In part 1, I explained what Data Quality entails and more specifically how the Foundation Data is crucial for running the SN platform smoothly and most effectively. Now that we know what data is necessary to maintain, we can dive deeper and propose some tips and best practices on how to improve the quality of the Foundation Data, which includes companies, users, groups, roles, departments, locations, etc.

Note: improving CI Data Quality is a whole different story. 

Refer to this article for more insights:

https://www.servicenow.com/content/dam/servicenow-assets/public/en-us/doc-type/resource-center/white-paper/wp-cmdb-improving-configuration-item-data-quality.pdf

Build a Business Case for Data Quality Improvement

Accurate and reliable data is the backbone of any successful organization. Countless data quality improvement projects are started across organizations since poor data quality can lead to misinformed decisions, wasted resources, and lost opportunities. On the other hand, good data quality can enable efficient workflows, automation, and even AI.

For creating business cases for data quality improvement initiatives and justifying the cost of a tool like Data Content Manager, this blog post is very helpful: https://datacontentmanager.com/importance-of-foundation-data/

Here is it talks about:

• The Cost of Bad Data
• Understanding Data Quality
• Identifying Stakeholders
• Assessing the Current Cost of Poor Data Quality
• Outlining a Solution
• Starting Small, Showing Results
• Comparing Approaches
• Calculating ROI
• Addressing Risks & Challenges

Scheduled Jobs

The most obvious tool to improve the quality of the foundation data is using scheduled jobs (i.e., deactivating users when they leave the company). However, the downside of using scheduled jobs is that the tickets and business apps assigned to the inactive users remain intact. In other words, the tickets and CIs contain the same inactive users. So, how to solve that? How to prevent the tickets and CIs from being assigned to the same inactive users?

Audits

One solution is to run daily audits to ensure these occurrences are caught and reported automatically. Refer to this article for more insights: https://datacontentmanager.com/are-you-sure-your-business-application-owners-are-still-there/

A good tool for running audits is the Data Content Manager (DCM). With DCM, you can quickly draw a Blueprint that matches the above data models. You can then run an audit against that Blueprint to check how accurate and up-to-date your current foundation data is (source: https://datacontentmanager.com/importance-of-foundation-data/)

A comprehensive use case is: Validating Task Assignments

Reference: 

https://www.youtube.com/watch?v=5wD2D1R2OUI&list=PLAF7bJqXgn1HXuEtWqQmmbDFyuytx8A7B&index=8&ab_channel=DataContentManager

Dashboards 

Another solution is to create real-time dashboards that drive user behavior. In other words, these dashboards can drive users to take immediate action. This means that they could drill through into real-time data and actually take ownership of it. 

For more insights, have a look here: 

https://www.youtube.com/watch?v=c3OcTCu_ty8&list=PLwqatgy6MBNPZ-5L0G0z5UIyYAw60Hkud&index=36&ab_channel=ExploreAnalytics 

Data Content Manager

DCM is a ServiceNow-certified app available in the ServiceNow Store. It has already gone through all the steps above. Furthermore, it is maintained and further developed for future compatibility and feature enhancements.

Most importantly: when things change, you only need to adjust your DCM Blueprints to match your changed requirements or create new ones to address new needs. There is no development involved.

While there are undoubtedly some overlapping steps, especially in defining requirements, getting DCM into use is very straightforward: 

• Acquire a license
• Install
• Create your first Blueprint, run an audit, and you will get results

Key Takeaways

To improve data quality in ServiceNow, it is essential to identify and address the challenges that hinder data quality. Based on the provided search results, here are some key takeaways:

• Data Quality Management: Implementing a data quality management solution, such as Data Content Manager (DCM) or Blazent’s Data Quality Management for ServiceNow, can help improve data quality by providing analytics that fuel improved insights and enabling service management staff to get at-a-glance information that helps speed investigation and response.
• CMDB Data Quality: The Common Service Data Model (CSDM) is a powerful tool for improving CMDB data quality. However, convincing stakeholders to invest in data quality improvement can be challenging. It is essential to demonstrate the importance of adequate data quality in enabling most capabilities of the ServiceNow platform.
  NOTE: Regarding the data inconsistencies reports, most of them could have been automatically handled (referring to the data inconsistencies in these reports) by the CSDM if it were properly put in place. In other words, the CSDM would have automatically corrected the data inside these reports.
• Data Ownership: Clear data ownership is crucial for improving data quality. It is essential to identify who is responsible for maintaining and updating data to ensure consistency and accuracy.
• Data Validation: Implementing data validation rules and checks can help ensure that data is accurate and consistent. This can be achieved through the use of Quality Clouds Field Analysis, which provides a powerful tool for decluttering the ServiceNow instance and improving adoption.
• Data Governance: Establishing a data governance framework can help ensure that data is managed effectively and consistently across the organization. This includes defining data standards, data ownership, and data quality metrics.
• Data Quality Metrics: Establishing data quality metrics can help track and measure data quality over time. This can include metrics such as data accuracy, completeness, and consistency.
• Data Quality Improvement: Implementing a data quality improvement process can help identify and address data quality issues. This can include identifying and correcting data errors, improving data validation rules, and establishing data governance frameworks.

Best Practices for Improving Data Quality in ServiceNow

• Establish clear data ownership: Identify who is responsible for maintaining and updating data to ensure consistency and accuracy.
• Implement data validation rules and checks: Use Quality Clouds Field Analysis to declutter the ServiceNow instance and improve adoption.
• Establish data governance frameworks: Define data standards, data ownership, and data quality metrics to ensure effective and consistent data management.
• Track and measure data quality: Establish data quality metrics to track and measure data quality over time.
• Implement a data quality improvement process: Identify and correct data errors, improve data validation rules and establish data governance frameworks to improve data quality.
• Use analytics and reporting: Leverage analytics and reporting tools, such as Data Content Manager (DCM) for ServiceNow, to gain insights into data quality and identify areas for improvement.
• Train and educate users: Provide training and education to users on data quality best practices and the importance of maintaining accurate and consistent data.

By following these best practices and implementing the recommended solutions, you can improve data quality in ServiceNow and ensure that your organization gets the most value from its investment in the platform.