April kicks off the second half of the federal government\u2019s fiscal year, starting federal portfolio, program, and project managers\u2019 annual race to spend every dollar of their remaining budgets by Sept. 30. Required to use and account for every dollar, these public servants are always on the lookout for new capabilities and tools to help them make better decisions faster.<\/p>\n\n\n\n
Fortunately, enterprise decision management tools \u2013 augmented with workflow automation aided by artificial intelligence \u2013 can enable agencies to find, understand, and use their data more effectively to make the most of precious budget dollars.<\/p>\n\n\n\n
To execute their second-half blitz, federal managers must pore through mountains of data across thousands of programs. They must make sound decisions despite persistent challenges: potentially duplicative projects, unseen dependencies, time-consuming data calls, stovepiped data sources, legacy tools and formats, and low visibility into outcomes.<\/p>\n\n\n\n
More federal agencies are harnessing new advances in AI, workflow automation, and other advanced technologies for budget forecasting and planning. Applied strategically at scale, these features can reduce decision time and increase transparency, discovery, and traceability of data across programs. Federal managers are using these capabilities to improve strategic alignment, accelerate mission success, and preserve \u2013 and potentially expand \u2013 their budgets going forward.<\/p>\n\n\n\n
In 2024, it\u2019s not a question if AI will proliferate, but when, how, and by whom. No one \u2013 including federal agencies \u2013 wants to be left behind. Enterprise decision management platforms incorporating AI and automation technologies can help federal managers visualize data in new ways, revealing how money flows through their complex organizations and leads to on-the-ground results.<\/p>\n\n\n\n
Workflow automation can integrate diverse data sources by linking and pulling information from different systems, updating them all in real time, and breaking down silos. AI capabilities can improve this process with gap analysis and automated recommendations tuned to each agency\u2019s unique mission requirements.<\/p>\n\n\n\n
New decision-oriented workflows can transform program actions with AI recommendations into data-driven learning cycles \u2013 making it easier to ask questions, get answers, and learn faster. Predictive natural language processing (NLP) builds off AI capabilities to make it easier to drill into each project, mine unstructured data, see AI-suggested items, and link investments.<\/p>\n\n\n\n
These features and others create transparency across data sets, enabling data organization and discovery in hierarchical and topical ways that transcend typical reporting and reveal new actionable insights. Using these tools, portfolio managers can find similar, possibly duplicative, investments.<\/p>\n\n\n\n
Project managers can adjust their risk tolerance as they gain greater command of schedules and interdependencies. Program managers can streamline data calls about cost, schedule, and performance. All three can link funding, project, portfolio, and capability data for visualizing alignment mapping of budget flows, from resource sponsors down to the minutiae of project execution.<\/p>\n\n\n\n
When considering enterprise decision management platforms with AI-augmented workflow automation for budget planning, federal managers should look for the following features:<\/p>\n\n\n\n
\u2014 Similarity Analysis and Contextual Search. More than just keyword search, these functions can reveal hidden relationships across thousands of programs to drive complete assessment and betterdecisions.<\/p>\n\n\n\n
\u2014 Command View. A single interface integrating all systems and data, instead of \u2018swivel chair\u2019 management requiring switching among multiple systems and screens<\/p>\n\n\n\n
\u2014 Machine Learning. The software learns and improves over time through AI suggestion and user interaction, while keeping the historical \u201cwhy\u201d behind every decision.<\/p>\n\n\n\n
\u2014 Fast Setup. All new capabilities need to work with existing systems without rip and replace.<\/p>\n\n\n\n
Empowering managers to make better decisions faster not only improves federal agencies\u2019 immediate annual spending, but also the government\u2019s long-term capacity to serve the American people. Many federal leaders seek predictive tools for divestment decisions \u2013 figuring out what stays and what goes to achieve optimal return on taxpayer money.<\/p>\n\n\n\n
As a few simple clicks reveal duplicative or deprioritized efforts, users can chart new pathways to free up resources, illuminate modernization pathways, and scale up innovation.<\/p>\n\n\n\n
Case in point: At AFCEA WEST 2024 last February, Rob Wolborsky, chief engineer at Naval Information Warfare Systems Command (NAVWAR), described how his team recovered over $10 million through divestment analysis. Their efforts enabled NAVWAR to fund more strategic efforts such as AI.<\/p>\n\n\n\n
The U.S. Department of Defense\u2019s increasing willingness to test operational AI concepts as part of enterprise decision management is a model for long-term success across the federal government. Now that these pathways have been charted, agencies can double down on these and similar efforts. Doing so would help their portfolio, program, and project managers take a frontline role in leading federal digital modernization.<\/p>\n\n\n\n
Mark Fedeli is vice president of sales at CORAS.<\/i><\/p>\n","protected":false},"excerpt":{"rendered":"
To execute their second-half blitz, federal managers must pore through mountains of data across thousands of programs.<\/p>\n","protected":false},"author":7,"featured_media":79147,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_yoast_wpseo_meta-robots-noindex":"","_yoast_wpseo_meta-robots-nofollow":"","_yoast_wpseo_canonical":"","_acf":"","_yoast_wpseo_primary_category":26,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","_smg_distribution_targets":[]},"categories":[112,31,15,14,26],"tags":[],"coauthors":[5989],"class_list":["post-27674","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-home","category-management","category-it-networks","category-opinions"],"acf":{"subheadline":"","legacy_arc_id":"732IR35RY5AANJAKNUU6YMQHFI","arc_canonical_url":"\/opinions\/2024\/04\/22\/power-through-fiscal-year-end-budgeting-with-ai-workflow-automation\/","remove_feature_photo":false,"is_sponsored":false,"subtype":"","redirect_url":"","disable_inline_ads":false,"native_logo_pretext":"Presented By:"},"yoast_head":"\n