Harnessing AI to Better Estimate IT Projects

Harnessing Strategy and Estimations: AI in Project Management

AI is revolutionizing almost every aspect of our world, and its potential applications seem limitless.

This inspired me to explore how AI could improve project management—an area I’ve specialized in as a program manager leading multiple initiatives.

Efficiency and automation have always been my focus, so why not use AI to revolutionize project planning?

Can Predictive Analytics and AI Improve Project Work Estimation?

Accurate work estimation is critical to a project’s success and in particular its profitability. Inaccurate or incomplete estimates at the outset can lead to project failure, in other words, cost overruns and schedule slippages.

To address this, organizations can leverage historical project data. Actual data captured over years of project delivery is invaluable for building predictive models.

The more high-quality data we have, the better the AI model’s performance.

Steps to Enable AI-Powered Project Estimation:

1. Evaluate Historical Data

   • Identify if data from past projects includes:

     • Activity Duration (Actual Start to Finish)

     • Level of Effort (Actual Hours)

     • Budget (Actual Cost)

     • Team Size and Composition

     • Project Category (e.g., Infrastructure Setup, Data Migration)

2. Key Data Considerations

   • What is the quality of the data?

   • Is the data structured and easily accessible?

   • How is the data stored (e.g., database, data lake, spreadsheets)?

3. Prepare and Analyze Data

   • Connect and ingest data using pipelines or tools (e.g., Azure Data Factory, Excel).

   • Cleanse data by removing duplicates, inconsistencies, or errors.

   • Load consolidated data into a view for exploration using BI tools like Power BI, Tableau, or Python libraries like Pandas.

4. Build Predictive Models

   • Use machine learning techniques, such as regression or neural networks, to identify patterns and correlations in the data.

   • Apply the model to estimate work for new projects based on historical trends.

With high-quality data and structured approaches, the possibilities for innovation in project management and predictable outcomes are endless!