How can you monitor contracts more effectively with data analysis?

2 Data sources and tools

To perform data analysis, it is necessary to collect and integrate data from various sources, such as contract documents and metadata, contract lifecycle management systems, enterprise resource planning systems, customer relationship management systems, and external sources. To analyze the data, you should use appropriate tools, like data visualization tools to present and explore the data visually and interactively, data analytics tools to perform calculations and queries on the data, and data science tools to apply advanced techniques like machine learning or natural language processing to the data.

3 Data analysis process

To monitor contracts more effectively with data analysis, you need to follow a systematic process. This process should include defining your objectives and questions, collecting and preparing your data, analyzing and interpreting the data, and communicating and acting on your results. Your objectives and questions should be related to the goals, challenges, and opportunities of your contract management process. You should also determine what data is needed to answer them. When collecting and preparing your data, you should consider where and how to access, extract, clean, transform, and merge your data sources. For analyzing and interpreting the data, you should use methods and tools that help explore, summarize, and model the data in order to derive insights and patterns. Finally, you should present and share your findings and recommendations in order to implement and monitor your actions.

4 Data analysis skills

To monitor contracts more effectively with data analysis, you need to develop and improve your data analysis skills, such as data literacy, which involves understanding, interpreting, and communicating data in a meaningful and relevant way. Additionally, you need to have the ability to manage data from various sources and formats, as well as the capacity to apply appropriate techniques and tools to analyze, model, and visualize data. Lastly, you should also be able to use advanced methods and tools to extract, process, and generate value from data.

5 Data analysis challenges

Data analysis can present some difficulties for contract management, including data quality, security, integration, complexity, and culture. To address these issues, you should adopt best practices such as establishing data governance, implementing data solutions, developing data capabilities, and fostering a data mindset. This includes defining roles and responsibilities for data management and analysis, selecting and deploying data platforms and systems, training and coaching data professionals, and promoting data awareness throughout the organization.

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?