How do you ensure data quality and accuracy in software license metrics audit and reporting?

1 Define clear objectives and scope

Before you start collecting and analyzing data, you need to define what you want to achieve and what you want to measure. For example, are you preparing for a vendor audit, a contract renewal, a budget planning, or a software optimization project? What are the key software license metrics that matter for your purpose, such as usage, entitlements, compliance, costs, or value? What are the data sources, tools, and methods that you will use to gather and verify the data? Having clear objectives and scope will help you focus on the relevant data and avoid unnecessary or inaccurate information.

2 Establish data governance and standards

Data quality and accuracy depend largely on how you manage and maintain your data throughout its lifecycle. You need to establish data governance and standards that define the roles, responsibilities, policies, procedures, and controls for data collection, storage, processing, validation, reporting, and improvement. For example, who is responsible for updating the data inventory, resolving data discrepancies, ensuring data security, and reviewing data quality reports? What are the data formats, definitions, categories, and rules that you will use to ensure consistency and compatibility across different data sources and systems? How often will you perform data quality checks and audits?

3 Use reliable and automated tools

Manual data collection and analysis can be prone to errors, delays, and inefficiencies. You need to use reliable and automated tools that can help you streamline and simplify your software license metrics audit and reporting process. For example, you can use software asset management (SAM) tools that can scan your network and discover your software assets, inventory your licenses and entitlements, monitor your software usage and consumption, calculate your compliance and costs, and generate reports and dashboards. You can also use data quality tools that can help you identify, correct, and prevent data errors, such as duplicates, missing values, outliers, or anomalies.

4 Validate and verify data

Even if you use automated tools, you still need to validate and verify your data to ensure its accuracy and completeness. You need to compare and cross-check your data from different sources and systems, such as contracts, invoices, purchase orders, license keys, certificates, or receipts. You need to reconcile your data with your vendors and suppliers, such as requesting confirmation letters, audit reports, or usage statements. You need to review and update your data regularly, especially when there are changes in your software environment, such as new installations, upgrades, migrations, or decommissions.

5 Communicate and collaborate

Data quality and accuracy is not only a technical issue, but also a business and organizational issue. You need to communicate and collaborate with your stakeholders and partners, such as IT managers, software owners, vendors, auditors, or consultants. You need to share your objectives and scope, your data governance and standards, your tools and methods, and your results and findings. You need to solicit feedback and input, address questions and concerns, resolve issues and conflicts, and align expectations and goals. By communicating and collaborating, you can ensure that your software license metrics audit and reporting is accurate, relevant, and useful for your decision making.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?