As a project manager, you need to regularly monitor the projects that you are leading on; whether it's reading update reports from your teams or checking how planned activities are progressing. This is a time-consuming process, and in many cases, you need to employ subjective judgement based on your experience. The problem is compounded if you happen to be managing a portfolio of projects. Is there a quicker and more objective way of assessing project progress, that keeps pace with the changing nature of data-related projects?
Of course, there is. Regardless of the field, more and more teams are adopting project management software to plan activities, manage tasks, decisions and meetings, document outcomes and in some cases communicating with each other. This range of information are indicators of whether your project is progressing satisfactorily. Using machine learning, you can not only understand at a glance what the state of your project is but make forecasts that allow you to take actions before issues occur.
What is the health score of a project?
The health score is designed to replace the RAG (Red/Amber/Green) values that project managers use to indicate project status at the end of each reporting cycle. RAGs not only suffer from subjectivity but also the fact that there are only three possible values.
Our project health score is an integer ranging from 0 to 100, which allows a fine-grained comparison between individual project statuses. Furthermore, their values are calculated using information taken directly from Sharktower, thus taking human bias out of the loop.
Where is the data coming from and what actions can I base on it?
Click any Project Health tile to reveal one of our 'explainers' - a guide to how the metrics are calculated and suggested further actions.
The Detail section provides insights on the factors (e.g completed tasks and activities) which are having the most impact on the health score. And In the Areas for Focus section, you can see items to concentrate on (such as blocked tasks) that will help improve your health score in the next week.
A peek under the hood
The health score is calculated only using the information you enter into Sharktower. Data such as how many work items (such as stories and tasks) were in progress, how many were delayed or blocked, who were the team members that created these tasks are all used as input of the machine learning model. The model uses this information to find hidden patterns in previous projects that led to their differing scores and thereby progressively improve its predictions.