AI and Cora PPM: 5 Key Innovations

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Cora CTO Pat Henry looks at the 5 ways Cora PPM is using AI to enhance project management practices.

Overview

Artificial intelligence (AI) has opened up a new world when it comes to managing project portfolios.

Here are five key innovations that are already starting to make a difference.

1. Aim

The aim is to leverage the vast amount of data available within your project portfolio management (PPM) platform to identify what attributes are important in predicting the success of a project. What is it that great project managers do? Can your PPM platform leverage data for project success prediction or guide users to take actions shifting the project’s RAG status from red/amber to green? Are there indicators signalling project failure, prompting a decision to cut losses and move on?

2. Motivator

Cora PPM platform gathers a significant amount of operational-level data from various sources such as logs, registers, workflows, uploaded documents, audit trails, etc. However, this data wasn’t being analyzed comprehensively at the project or portfolio level. Instead, we depended on the project manager to interpret the data’s meaning for their project. Based on their insights, we updated the project RAG status and reported any issues by updating registers, logs, and reports upwards.

Leveraging our AI and ML expertise, we identified a market gap for automating manual analysis in project management. Automated insights into project and portfolio status empower on-the-ground project managers to make faster decisions, freeing up time for value-added activities over admin work.

3. Proof of concept

We’re expanding our offerings in financial information, including cost books and financial forecasting. Forecasting, particularly in the context of EAC (estimate at completion), is a key focus for AI and ML techniques. Accurate cost forecasting is crucial for precise revenue estimates, with the EAC remaining constant throughout the project.

To grasp EAC deviation, we aimed to identify the data points (levers) influencing EAC adjustments. This information serves a dual purpose: AI and ML techniques can provide a percentage confidence level for predicted EAC deviation/adjustment. Simultaneously, it informs client companies about crucial attributes requiring tracking and monitoring, facilitating potential process changes.

In four months, we upskilled our technical team on data extraction, cleaning, and the fundamentals of AI and ML. The team gained exposure to various learning algorithms, including supervised and unsupervised learning, as well as reinforcement learning techniques. They also learned to identify the types of problems and data best suited for these algorithms.

4. Natural language processing

Another area of research and innovation within Cora’s platform is around natural language processing. Over $100bn worth of projects, in over 50 countries across the globe are managed using Cora PPM daily. At any one point in time, there are over 300,000 live projects operating in Cora PPM.

While operating these projects, extensive free text and numerous documents, including handwritten notes, are entered into the system. Currently, this information is stored in its raw form. Project managers need to log in and manually select to view this information before making decisions or updating the project status. The natural language processing service will parse, extract, and annotate all this raw data, enabling machine interpretation.

Having the ability to run sentiment analysis (looking at text someone enters and trying to gauge mood based on what is inputted) on a project or a portfolio will enable our clients to ensure that they are focusing their efforts on the correct projects and portfolios. The system will be able to raise early warnings where the perceived sentiment does not correlate to the reported project or portfolio status, and potentially escalate risks or issues.

5. Strategic portfolio management (SPM)

Currently, we are further developing our strategic portfolio management product, Cora SPM, which will build upon the strong foundations of Cora PPM. We will apply advanced data analytics to convert operational-level data from project and portfolio management platforms (such as Cora PPM) into insights.

Cora SPM will have the capability to predict the success of projects, identify which projects should be included in a portfolio, and, ultimately, guide project and portfolio managers to ensure that they achieve repeated success.

Incorporating advanced data analytics and machine learning into the project and portfolio management space, when combined with our in-house domain expertise, will give Cora a significant competitive advantage, especially in our strategy realization offering.

Further Insights

Find out more about Cora’s project portfolio management software solution or scroll down to read more insights into the benefits of AI for Project Management.

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