This company has to process 27,450 announcements annually, many of them simultaneously. Now let’s look at exactly what it takes to process them. See how it compares to the way your company handles this problem.

1. First, assume someone must log in to eBuy three times a day to check for anything released to the firm, note the metadata about the opportunity in the eBuy portal, and download all attachments. Estimating this at 12 minutes each time they log in, 350 days of the year, this step consumes about 210 hours annually.
2. The next step is to perform quick key word searches, in Windows File Explorer or in Mac Finder, at the file level on materials downloaded from eBuy. This search is to determine which items should be opened by detecting missions, scopes, technologies, or use cases of interest to the firm. Performing this three times per day on downloaded materials, 15 minutes each time, 350 days per year requires another 263 hours annually. This produces a “filtered list” of opportunities that only may fit. By the way, we all know that key words about scope, NAICS, or desirable technologies are not the only factors to consider, but this is the limit of the typical company’s technology available to filter opportunities.
3. Then, a preliminary screening of items found in the filtered list must be performed by an employee. If we assume 30% of the annual count of announcements on each vehicle has key word matches, performing this step requires 10 minutes to navigate to the objectives and scope sections and quickly skim to assess the opportunity, then in the above example 1,377 hours are required for preliminary reading annually. Ten minutes is needed even if someone dumps the solicitation attachments into ChatGPT to get a summary they can quickly digest.
4. The next step is to perform a deeper reading of the opportunity files for those that pass the preliminary screening. If we assume that 20% of the opportunities passed preliminary screening (i.e., 20% of the 30%) and that performing a deeper reading of those takes two hours per opportunity, this adds 3,305 hours annually.
5. The last step is to route the opportunities that fit the firm’s interests to the company personnel who need to decide whether or not to commit resources. If we assume that half of the 20% that were read deeply fit well, and that 30 minutes is required to disposition each opportunity (50% of the 20% of the 30%), then we need another 330 hours annually.

Totaling this up, 5,485 hours are required to perform the rudimentary process as we have described it. That’s equivalent to 2.8 full-time personnel, which would cost around $300,000 in today’s market. The bottom line: for many companies, $300,000 is the equivalent cost to prepare a proposal submission and too much to spend on finding opportunities.

In the past, this onerous process has been how companies have handled the drudgery of finding seemingly relevant government contracting opportunities to bid on. But now, there’s a revolutionary opportunity evaluation solution available to organizations of all sizes that can greatly reduce the amount of time and money spent on identifying the right opportunities to consider.

For a much lower cost, all five of the above steps can be done automatically, faster, and better than with people power alone. GWAC NorthStar™ applies business developers’ logic and criteria to determine how well an opportunity fits each client. We codified decision criteria that you can directly configure in the system. Then, our solution automatically ingests, reads, and discovers all the attributes necessary to your decision, and scores each opportunity accordingly.

This tool enables you to, at a glance, see the most relevant items deserving your attention, saving you from wasting precious time and resources on the others.

Every service Deep Water Point & Associates (DWPA) provides combines our unique and powerful combination of agency insights applied by practitioner experts to enable clients to produce compelling advantages. A subscription to GWAC NorthStar can also lead to better win probability. DWPA has over 400 former federal agency executives with deep knowledge of programs, operations, culture, competitors, and decision makers. GWAC NorthStar subscribers can engage these experts to prepare for sales calls, for knowledge transfer on opportunity context, key personnel hot buttons, etc.

Find better opportunities faster and win more. Interested in learning more? Schedule a demo today and find out how GWAC NorthStar can revolutionize the way your company grows federal government sales.

Add some weather, makeshift shelters, finding food and water, and the occasional predator, and could spend a long time not reaching your destination. At potentially great cost. 

This describes navigating the Federal AI landscape, today. The landscape is enormous and varies widely. It contains some known features and paths, but much is untamed and unmarked. Here are a few noteworthy features of that landscape: 

• Some agencies have used artificial intelligence for decades. But Defense, Intelligence, and Civilian sectors have different histories of use, needs, budgets, and suppliers. Do you know how AI manifests itself in mission and business priorities? Do you know what customers will buy next? 
• Generative AI use is much newer, and users are fewer in number. As programs begin their own navigation of that terrain, they have more questions than answers. Do you know their environment well-enough to guide their journey?
• The Executive Branch has issued numerous complex strategies, frameworks, guidance, policies, procedures, and blueprints. Some protect missions. Some protect civil rights. Some blend the two. Do you know what’s foremost on the minds of potential customers?
• The government is concerned about civil rights violations in AI-supported analysis and decision making. Do you know how to meet these requirements during solution development? In business development – especially in early requirements-shaping conversations – do you know what to say to demonstrate your knowledge of and compliance with the requirements?
• Some AI legislation has been passed, and Congress has more in the hopper. Add to these Executive Orders, OMB directives and proposed regulations; budgets and budget artifacts; agency strategies and frameworks; standards-setting documents; SBIR/STTR releases, OTA solicitations, and R&D announcements; Congressional testimony and Committee reports; GAO and CRS reports; and trade regulations. Do you know where to watch and read to stay up on developments that will impact your business? 
• The Biden Administration’s October 30, 2023 “Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence” contained 186 shall statements and 98 deadlines. Do you have the resources and expertise to know which affect you?
• Dual-use featured prominently in this EO, addressing AI and generative AI, and clearly describing when export control laws and regulations applied. Dual-use controls might apply to entities never before covered. Do you know if they’ll apply to you?

The Federal AI landscape presents daunting competitive, contracting, and project management challenges for existing and new AI solution providers. DWPA’s Federal AI Landscape market intelligence report will provide the map and compass you need to navigate the environment and meet those challenges. 

The scope of change and opportunity is enormous. A single example is the just-released Department of Defense (DoD) 2023 ‘Data, Analytics, and Artificial Intelligence Adoption Strategy,’ which focuses on longstanding goals for a “unified approach across data, analytics, and AI activities; an educated, empowered workforce skilled at incorporating commercial teams and tools; continued advanced research and rapid experimentation; and effective integration with our Allies and partners.” The DWPA Federal AI Landscape will forecast where that strategy is likely to lead to help you shape opportunities that are likely to follow.  

It’ll also track the DoD’s Chief Digital and Artificial Intelligence Office’s effort to understand how DoD might accelerate the adoption of generative AI to support warfighters. It’ll also evaluate DoD objectives in conjunction with mandates from the new FY2024 National Defense Authorization Act, which signals an urgent need for AI proficiency backed by appropriations exceeding $34B for AI/Machine learning (ML) technologies and basic research.  

The Federal AI Landscape report is being developed by DWPA’s AI Innovation Cell. The Cell is staffed with select agency, technology, and business development experts from nearly 500 company Associates. Using primary sources and comprehensive research, the Cell analyzes and tracks the “features” of the landscape noted above, plus more, to provide clients actionable information about the who, what, where, how, and when of Federal AI opportunities for client capabilities. And with the depth of DWPA’s agency experts, you’ll understand the why. 

DWPA will begin taking subscriptions for the Federal AI Landscape report and AI Innovation Cell in March 2024. Contact Ted.Milone@DWPAssociates.com or Michael.Dougherty@DWPAssociates.com in our Market Intelligence section for more information.

Follow us here on ThinkSpace to learn more.

This trajectory isn’t inevitable. Individuals and teams need time to gain generative AI knowledge and skill, and organizations can do many things to enable or hinder that knowledge and skill acquisition. You can expect early adopters to be motivated to do more, however, and the next adopters to observe with interest. Whether individuals and teams began using generative AI in 2023 or they start in 2024, you’ll notice they want to advance use to create more benefit. Only leadership can turn use into adoption to produce strategic gains, not just tactical.

In December 7 and December 8 ThinkSpace articles, DWPA distinguished adoption and use and explained how adoption can lead to strategic gains. Growth is a central strategic gain, so how do you harness early adopters’ experience and energy to grow in 2024? Consider the following four principles or practices.

1. First, know your strategic intent and write it down for everyone to know. Clarifying growth goals will channel early adopters’ efforts who would use generative AI differently for different ends, such as to position in the market, enter an adjacent market, reduce costs, or create new value propositions.
2. Second, decide how you’ll measure progress and success. This not only tells you how well efforts produce results, it helps early adopters further target generative AI use. Generative AI is a powerful, nuanced capability which requires a fair degree of trial and iteration. Working from broad objectives subject to interpretation can waste time, money, and effort. Knowing exactly what target to aim at will enable individuals and teams to make the best choices. It’ll also help with Practice 3.
3. The third practice is to assess organizational capabilities against your strategic intent. This can be an extensive effort you might wish to undertake for many business reasons. For purposes of harnessing early adopters’ experience and energy to grow in 2024, you can chunk it down. Ask early adopters to identify capabilities needed to accomplish the growth objectives they support with generative AI. They’ll know the task, process, resource, partner, and other requirements they need to succeed[1].
4. The fourth and final practice is to think like an entrepreneur. By adopting generative AI, you’re doing something different to create new value. This necessarily involves the discovery and validation of new business model elements, and your teams might not be familiar with ways to do this. Encourage them to identify assumptions, formulate hypotheses to test, and then review evidence they gather. Establish the practice of discovery, appraisal, and application of what is learned and you’ll increase your odds of using generative AI to grow.

As you start a new calendar year, one-third through the fiscal year, the question isn’t whether you’ll harness early adopters’ efforts to grow. Nor is the question when, because when is now. The question is how you’ll draw together the curiosity, talent, motivation, and ingenuity of individuals and teams to support growth and other business objectives. These four generative AI adoption practices will get you started.

Follow us here on ThinkSpace to learn more. For details, contact your Client Executive or Lou.Kerestesy@DWPAssociates.com.

[1] To organize what can be far-ranging discussions, DWPA recommends using the Business Model Canvas (or similar framework) for these conversations.