The DCM Blog

5 Steps to Better Data Quality (Especially in CMDB)

By Mikko Juola

March 16, 2023
5 Steps Abstract

The role of the CMDB is more important than ever. At the same time, we continuously see companies struggle with the quality of data in their CMDBs. The data is often outdated and inaccurate, causing processes that rely on the CMDB not to perform as they should.

After all, the CMDB is only as good as the data it contains.

Getting started with CMDB data improvements can be difficult and overwhelming. Furthermore, data quality is often seen as a project. However, projects end, and if there is no process for maintaining data quality after the project, the quality of data is bound to degrade.

We’ve talked about our 5 Steps Model since 2018. It is a simple tool to help address the problem of data quality. It can be applied to any data but works particularly well with the CMDB.

Our product, Data Content Manager, fully supports the 5 Steps model, and it helps you define your requirements for data quality and then audit your data against those requirements. All with easy-to-use graphical data modeling tools and precise deviation reporting running within your ServiceNow instance.

Here are some of the benefits of following the 5-steps model together with Data Content Manager:

  • Structured approach for phased implementation
  • Ownership established from the start
  • Same process for any data in ServiceNow
  • Measurable results from the beginning
  • Improved visibility to current and target states
  • Ready-made reports for different stakeholders
  • Understandable KPIs for data providers

The Five Steps 

5 Steps Overview

Here are the five steps in brief, and below is more detailed information and examples for each step:


    1. Select the most important data domain or area to focus on.
    2. Define ownership for the domain.
    1. Define where record-level data providers can be found.
    2. Create a Blueprint to cover the required provider data.
    3. Audit and remediate provider data.
    1. Define your Minimum Viable Data Model.
    2. Audit your data against the data Minimum Viable Data Model.
    3. Use the data provider information for remediation task assignment
    1. Define the target data model for the domain
    2. Audit and remediate
    1. Refine the target model
    2. Audit, remediate, and repeat
    3. Expand to the next data domain

Step 1 – Select Data Domain

The Data Domain diagram shown here is an example based on ServiceNow’s Common Service Data Model. The CSDM domains can be used as Data Tiers in DCM with more specific Data Domains underneath them—for example, a Business Applications domain under the Design tier.

  1. Identify different data areas/domains related to ServiceNow Data Management
  2. Select the most important domain
  3. Define who is the data owner for the whole domain (from an information architecture point of view)
  4. Select the most important data class as the root class for your Blueprint

Note: “Most important” may vary between organizations and perspectives. Importance may be impacted by data criticality, volumes, current quality, required effort, and people’s availability, for example.

For the remainder of this article, we use the Business Applications domain as an example. All of the data models below are Blueprints drawn with Data Content Manager. 

Step 2 – Define Data Providers

  1. In this example, we selected Business Applications as a more specific domain under the “CSDM Design” domain (or tier as we refer to it)
  2. Next, define how to find the responsible person or provider for the data, starting from the root record. Read this article about the Consumer-Owner-Provider model to understand what a Data Provider is. In the example, we use an IT Application Owner reference from a Business Application to a User record
  3. Create a scheduled audit for the Blueprint
  4. Check the results and inform the Domain Owner if mandatory data is missing. In this example, both User and Group references are set as mandatory. You should aim for  100% compliance against this Blueprint.

Target: Ensure every record in the selected domain/class has a data provider defined. This information can be used to assign remediation tasks later.


Step 3 – Secure Minimum Viable Data

  1. Leave the previous Blueprint running as a scheduled audit. It is for continuously verifying that your Data Providers exist and are valid.
  2. Then, create a new Blueprint to expand the from the previous one to include other minimum data related to business. For example, add a Field Setup to define minimum required attributes or a relationship to an Application.
    • Limit your scope to Minimum Viable Data. For example, only include critical applications in the beginning
    • Create a scheduled audit for the new Blueprint. This audit should apply to all root records, but it can be limited to only records that have a provider. That means that you need to fix any provider issues first.
    • Check the Audit results and assign remediation tasks to Data Providers – in this example the IT Application owners of the Business Applications.

    Target: Data providers are now responsible for filling in the minimum information and relationships for their CIs.

    Step 4 – Reach Target Model

    1. Leave the previous Blueprints and Audits running
    2. Collect feedback and quick wins from the previous steps. What has been accomplished with better data quality so far?
    3. Then create another blueprint with more details and requirements. Requirements can and should relate to specific use cases. Another way to progress is by extending the scope of audited records.
    4. Create a scheduled audit for the new Blueprint
    5. Use these audit results to evaluate your readiness for the next phase

    Target: Identify a target model for the future and follow progress on how to get there. Set targets for data providers to increase compliance over time. Remember to celebrate achievements and communicate quick wins!

    Step 5 – Refine and Repeat

    1. Create new version(s) of the Target Model
    2. As previously defined data and relationships are in place, more requirements can be considered for data modeling and audits. This can mean:
      • More related data or more detailed filters
      • More root records to be included in audits
      • Changing optional data to mandatory
      • Creating more specific models based on different use cases
    3. This is an iterative step that will continue forever
    4. Along with this step, one should expand to other data domains.

     Target: Make sure that previously achieved data compliance is maintained while constantly evaluating and redefining the target data model based on current demand and future plans.

    A Systematic Approach

    With this kind of systematic approach and Data Content Manager to support your efforts, you can easily communicate:

    • your current state,
    • your target models,
    • and progress to your various stakeholders.

    With clearly defined data requirements and the results DCM provides through visual dashboards, you will have a much better chance of winning your stakeholders’ trust and support. CMDB initiatives, like any other project, require management support to succeed.

    If you want to know how DCM can help you walk these steps, please do not hesitate to book a demo session to see DCM in action and get your questions answered.

    Additional CSDM Resources

    We have written a lot on aligning with the Common Service Data Model and how Data Content Manager can help ease the journey.

    Here are some excellent places to start:

    Please reach out to us if you have any questions!

    Mikko Juola

    Mikko Juola

    Chief Product Officer at Qualdatrix


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