To enable AI in project management, a data-first strategy is needed

According to the Gartner AI in Organizations Survey, only one in ten companies accomplishes putting at least 75% of AI projects into production.

There are three major barriers to success: data accessibility, data scope and quality, and data volume. The concept of ‘data maturity’ covers all of these issues, and can help businesses keep track of how well they’re doing with their strategies.

Having unstructured, unorganized data is not enough. If the data is siloed between teams, stored incorrectly, or simply lost, your organization doesn't have the mature, detailed, and accurate data it needs. This can be avoided by adopting a data-first strategy.

This has been my recent experience when working on an AI project to test the hypothesis if it is possible to predict which projects will progress to the next phase of development based on purely operational attributes (e.g Cycle Time, PTS, Costs, Sentiment, Risk, Team Turnover). Whilst there were many other operational attributes that we wanted to add to the model, we were hampered by the lack of access and retrievability and thus decided to test the model utilizing a limited set of operational attributes (6 in total). We have created a model with 88% accuracy for predicting project progression, which we would like to continue developing and improving by adding more operational data. This experience has highlighted the need for a Data First Strategy if we are to realise the benefits of AI in Project Management. As stated by Grefly, some aspects of a Data First Strategy will include:

• Create universal data policies. Reduce the amount of time spent cleaning and validating data by having set policies in place.
• Design your strategy, budget, and plan. By laying out your short- and long-term goals, as well as strategies to achieve them, you can avoid problems further down the line
• Find the right people. For a data first strategy to succeed, you need experts in both data management and governance
• Invest in infrastructure. Hiring the right people is meaningless without the right technology

I would love to hear back via the comments where your organization currently stands in terms of maturity in having a Data First Strategy