Episode 8 — Write crisp intelligence requirements stakeholders love
In Episode 8, Write crisp intelligence requirements stakeholders love, we focus on the skill that quietly determines whether intelligence work succeeds or fails before it even begins. Intelligence requirements are the starting point of the entire cycle, and weak requirements almost guarantee wasted effort no matter how skilled the analysts are. When requirements are clear, analysis feels focused and efficient, and outputs tend to land well with stakeholders. When requirements are vague, teams drown in data and still disappoint the people they are trying to help. This episode is about learning how to ask the right questions in the right way, so intelligence work starts with purpose instead of guesswork. A well-written requirement is not paperwork, it is an accelerator that protects time and increases impact. Once you see how powerful good requirements are, you stop treating them as a formality and start treating them as a craft.
At its core, a good intelligence requirement is a specific question that a decision-maker needs answered in order to take action. That action might be funding a control, prioritizing a remediation, accepting a risk, or changing an operational posture. If there is no decision attached, the requirement is probably incomplete. The requirement should make it obvious who the audience is, what decision they are facing, and what uncertainty they are trying to reduce. This does not mean the answer must be simple, but the question must be. Analysts should be able to read the requirement and immediately understand what success looks like. When a requirement is framed around a decision, analysis naturally stays relevant because it is anchored to an outcome. This is the difference between producing intelligence and producing information that happens to be interesting.
One of the most common problems teams face is vague requests that sound reasonable but are impossible to satisfy. Turning a request for more information into a precise and measurable requirement is a critical skill. A vague request often hides a real concern that has not been articulated yet. Your job is to uncover that concern and translate it into a question that can be answered with evidence. For example, more information about a threat usually means someone is worried about exposure, impact, or likelihood, but they have not named which one. By asking follow-up questions, you can reshape the request into something concrete, such as whether a specific threat is likely to affect a specific asset within a specific timeframe. Precision here saves hours of unnecessary collection later. It also makes the final product easier to evaluate, because you can clearly see whether the requirement was answered.
Broad requirements like tell me everything about ransomware are tempting because they feel comprehensive, but they are a trap. They imply unlimited scope, unlimited time, and unlimited relevance, none of which exist in reality. No team can deliver everything, and even if they could, the result would overwhelm the recipient. Broad requests also push analysts toward generic summaries that do not influence decisions. Avoiding this trap means being comfortable pushing back and narrowing the question. Narrowing is not refusal, it is refinement, and it is part of professional intelligence work. When you replace a broad request with a focused requirement, you are increasing the chance that the output will actually be used. This is how intelligence earns trust over time.
Strong requirements usually begin with conversation, not writing. Meeting with stakeholders to understand their pain points before drafting requirements is essential because it reveals what is really at stake. Stakeholders often describe symptoms rather than decisions, and listening carefully helps you translate those symptoms into actionable questions. Ask what keeps them up at night, what decision they are struggling with, and what would change if they had better information. These conversations also build relationships, which makes later clarification easier. When stakeholders feel heard, they are more receptive to refined requirements that may differ from their original phrasing. Intelligence requirements are a collaborative product, even if analysts are the ones who write them down.
To see this in action, imagine drafting a requirement for an executive worried about a new supply chain vulnerability. The executive concern is rarely about technical exploit details, but about business exposure and risk posture. A good requirement would frame the question around whether the vulnerability affects critical suppliers, whether exploitation is likely in the near term, and what mitigation options exist. It would avoid diving into proof-of-concept details unless those details directly inform a decision. By aligning the requirement with the executive’s concern, you set yourself up to deliver intelligence that feels directly relevant. The executive does not want a vulnerability briefing, they want clarity on what to do next. A well-framed requirement makes that possible.
A useful analogy is to think of a requirement as a precise order placed at a restaurant. If you say you want food, the kitchen cannot deliver anything meaningful. If you specify the dish, preferences, and constraints, the result is far more likely to satisfy you. Intelligence works the same way. Analysts are the kitchen, and requirements are the order ticket. The clearer the order, the better the result. This analogy also highlights responsibility, because if the order is vague, disappointment is predictable. Clear requirements respect everyone’s time and effort by setting expectations up front.
Well-defined requirements share common characteristics that distinguish them from poorly phrased requests. A strong requirement is specific about scope, audience, and timeframe, and it implies a decision context. A weak request is broad, timeless, and detached from action. Strong requirements can usually be answered with available sources or with a clearly defined collection effort. Weak ones tend to expand endlessly as new information appears. Learning to spot these differences quickly helps you intervene before work begins. It also gives you a language for explaining why a request needs refinement without sounding dismissive. Clarity is a service, not a barrier.
Not all requirements are equal in duration or urgency, and it is important to understand the difference between standing requirements and ad hoc requests. Standing requirements address ongoing concerns that need regular monitoring, such as threats to a critical asset or persistent adversary activity. Ad hoc requests are time-bound and driven by immediate events, such as a new vulnerability or an unfolding incident. Treating these two types the same leads to frustration, because their rhythms are different. Standing requirements benefit from repeatable processes and scheduled reporting, while ad hoc requests demand focused, rapid response. Distinguishing between them helps you allocate effort appropriately and set realistic expectations with stakeholders. It also helps you avoid interrupting long-term work unnecessarily.
Clear requirements save time in a very practical way by preventing collection of data that no one actually needs. Without a clear question, collection tends to sprawl, because it feels safer to gather everything just in case. That sprawl increases processing time, slows analysis, and dilutes conclusions. With a clear requirement, you can justify excluding sources that do not contribute to the answer. This discipline protects analyst attention, which is often the scarcest resource. Over time, teams that write good requirements spend less time sorting and more time thinking. That shift improves both morale and output quality.
As requirements accumulate, prioritization becomes unavoidable, and this is where the Priority Intelligence Requirements (P I R) framework becomes valuable. P I Rs help you rank requirements based on their importance to organizational objectives and decision-making. Not every question deserves equal attention, even if all are interesting. By identifying which requirements matter most, you ensure that limited analytical capacity is applied where it produces the greatest benefit. This framework also provides a transparent way to explain why some requests are addressed immediately while others are scheduled later. Prioritization is not favoritism, it is alignment with risk and mission. When stakeholders understand this, they tend to trust the process more.
Feedback is an essential part of requirement quality, and it should be sought deliberately. Asking stakeholders whether the intelligence helped them make a decision closes the loop and reveals whether the requirement was framed correctly. If the answer is no, that is an opportunity to refine how questions are written and interpreted. Sometimes the analysis was solid, but the requirement did not fully capture the decision context. Other times the requirement was clear, but the dissemination missed the mark. Regular feedback turns requirement writing into a learning process rather than a static skill. Over time, you begin to anticipate what different stakeholders need and phrase requirements accordingly.
Language matters, especially when intelligence is consumed by non-analysts. Refining your language to be concise and free of unnecessary technical jargon makes requirements easier to understand and easier to fulfill. Jargon can obscure intent and create ambiguity, especially across organizational boundaries. A requirement should be readable by anyone involved in the decision, even if the analysis itself becomes technical later. Clear language also makes it easier to revisit requirements months later and understand why they existed. Precision does not require complexity, and simplicity does not mean lack of rigor. The best requirements sound straightforward because they are well thought out.
Requirements drive the entire intelligence cycle, which means improving them improves everything downstream. When you write better requirements, collection becomes focused, analysis becomes sharper, and dissemination becomes more effective. The cycle moves faster because fewer adjustments are needed midstream. Your next step is to write one clear requirement for your most critical asset, framed around a real decision that matters right now. Keep it specific, actionable, and audience-focused. That single requirement can become the model for how your team approaches intelligence going forward. When requirements are crisp, the rest of the work starts to feel purposeful instead of reactive.
