Many organizations have budgets that expire at the end of the fiscal year. This can cause a rush to utilize the funds and may lead to choosing low-quality projects at the year’s end. In fact, spending in the last week of the year is 4.9 times higher than the rest of the year, according to the American Economic Review! How can an agency insure that their funds are being used in the best ways possible? There have been recent studies on the performance of machine learning and various data analytics practices helping organizations to limit their risks when choosing a project. By analyzing workforce, costs, financial health, influence, supply chains, past performance, and other factors, automated tools can help managers focus their resources on potential risks that might have been buried in large, diverse data.

Listen in as Federal government leaders discuss how ML can be implemented in their source selection processes and where they see the future of source selection heading!