Which areas can we improve or automate with AI and Big Data?
a) Selecting and Prioritizing Projects
Selection and prioritization of the wrong projects lead to wasted resources, lack of focus, reduction of value creation, and eventually bankruptcy. The use of new intelligent tools in project selection and prioritization could bring the following benefits:
- AI can better predict the success rate of projects, increasing suitable investments and reducing bad ones;
- Remove human biases and subjectivity that interfere with making the best choices;
- Invest in projects that are ready to be launched and have the proper project fundamentals in place;
b) Project Management Office
With data analytics and automation, we can now help organizations streamline and optimize the PMO’s role. The most famous case is French President Macron’s using the latest technology to maintain up-to-date information about all the French public-sector projects. The use of new intelligent tools brings several benefits:
- Better monitoring of project progress, complementing the input from project managers;
- The capability to anticipate potential issues and addressing some simple ones automatically;
- Improved preparation and distribution of project reports along with capturing feedback;
- Greater sophistication in selecting the best project management methodology for each project;
c) Virtual Assistants
We can also develop “Bots” or “virtual assistants,” which allow project managers to rely on the experience programmed into a virtual assistant to find the best solution. The digital assistant learns from past time entries, project planning data, and the overall context to tailor interactions and capture critical project information smartly. Project managers and project sponsors will be able to ask their smartphones anything from “what is the status of my project?” to “what are the potential risks that we will face?” or “which stakeholder should I talk to first?”.
d) Project Definition and Planning
One of the main challenges when defining a project is determining the “what,” the design, requirements, project management terms, and scope. The more accurate the scope, the more precise our project estimates will be. A number of technology start-ups have created tools to help define scope. It reads requirements and user stories as if it were a human and performs much of the time-consuming analysis work done by project managers and their teams.
Besides scope definition, project planning, which is the other activity which requires a tremendous amount of effort during the initial phases of the project, leverage project data to facilitate project planning processes; drafting detailed plans and resource demand in minutes.
e) Reporting automation
Project progress reporting remains primarily a manual exercise involving repetitive tasks such as collecting, challenging and validating project information accuracy, sending reminders, consolidating all the information in customized reports for the project team, senior management, or steering committees. The task is not only highly time-consuming, but the data and facts presented in the reports are, in most instances, at least a few weeks old. Today, we interactive visual tools that use machine learning models and real-time information to identify project issues before creating problems, indicating project status, benefits achieved potential slippage, and team sentiment in a clear, objective way.