Reference no: EM133438017

Part I: One of the most significant obstacles that prevents effective multi-agency and inter-governmental collaboration are the layers that information or tasking authorities need to pass through in order to accomplish a goal. I would argue that efficiency is a bigger issue in collaborating between agencies because often times information will have to pass through multiple chains in order to be disseminated to the greater IC. Additionally, a larger organizational issue is that each entity within the IC has specific tasking and priorities that they focus on. It is likely that entities will prioritize what's important to them first, then focus on external taskings or requests for information. This organizational culture seen amongst the IC puts up a barrier and inhibits information sharing practices (Maras, 2017). Different agencies have different opinions or standard operating procedures surrounding information sharing. As with most government agencies, we must also consider the way politics influence relationships within the IC.

When we get into different types of intelligence, agencies that deal with SIGINT have to abide USSID System (ODNI, 2011). This is a legally binding document that outlines guidelines and procedures that U.S. SIGINT entities must follow. This includes dissemination control guidance. Much of what these SIGINT entities do is not disseminated to the greater IC due to classification levels and clearances. This lack of ability to share intelligence may cause some animosity within the IC because it seems that certain agencies are intentionally gatekeeping.

Part II: From a tactical perspective, there are obvious impediments on information sharing due to the vast amount of platforms and information technology (IT) systems maintained by nations and agencies (Corbett, 2022). Many of these systems and practices were created intentionally isolated, when there was not a push to communicate with each other. This issue is especially obvious when the IC looks at ways to share information with our allied partners across domains. While some of this has to do with classification levels and different clearances of users, there may be a better way to streamline information sharing. If this issue is resolved, it could save different agencies from wasting time doing redundant intelligence collection and reporting. Perhaps artificial intelligence can assist in filtering common terms or phrases and alert those organizations when they are working on similar projects or collection.

On the most tactical level, and speaking from personal experience, the biggest obstacle that we face in the IC is when organizations get tunnel-visioned on their own work and do not collaborate with their partners. Part of this has to do with the hierarchical structure or chains of commands some organizations have. However, it ultimately comes down to individuals being eager to either pick up a phone or send an email to form relationships and partnerships with agencies that can provide assistance. Networking within the IC can make complex processes more streamlined, especially when members know the appropriate point of contact to reach out to for specific problems. Building these partnerships can facilitate widespread success throughout the community (Carter, 2014).

Part III: To overcome these presented obstacles and create a streamlined approach, collaboration needs to be encouraged within each agencies and higher-level leadership needs to empower their analysts or operators to pick up a phone or send an email to get after a problem or question. While this cultural change may take a while, there are other short-term solutions to the communication issue. Agencies can better utilize their liaison officers or LNOs to pass information through. This requires detailed pass downs and reach back support contacts. The majority of IC agencies have designated LNOs that are tasked with facilitating bi-directional flow of intelligence and can appropriately represent their agency (DHS, 2021).

For the obstacle of too many IT systems and databases, the IC could research better ways to utilize artificial intelligence and machine learning. While I personally do not understand the technicalities or specifics of these topics, this could help with both information sharing and efficiency. Implementing artificial intelligence into the current databases could help analysts and operators better understand huge amounts of data (Corbett, 2022). Machine learning could also use pattern algorithms and filter layers to extract and highlight key words and patter match products within domains. This could help reduce redundant reporting and collection. There may be concerns with machine error potentially creating classification mistakes or presenting other challenges to operational security. Either way, it is likely that the IC has already been researching better frameworks on how to untangle the large amount of data sets that will only get bigger throughout the years.