Making sense of the world in the age of information overload can be daunting. If you’re lucky enough to know where to begin, the overabundance of information can easily paralyse your efforts, and keep you from making a decision or completing your task. There’s too much available information to sift through, too many ways to interpret whatever you gather and too many ways to share what you found. This is where the Intelligence Cycle comes in.
What Is the Intelligence Cycle?
The Intelligence Cycle is a method intelligence analysts use to process raw information into intelligence products decision-makers use to inform their judgements and actions. It typically consists of five phases: Collection, Analysis, Dissemination, Feedback & Review and Direction.
Developed in the 1940s, the mental model is still one of the first concepts you learn as a budding analyst. Closely followed by reasons why the whole model is flawed and outdated. Which doesn’t keep organisations around the world from relying on the process. So there must be something useful to it.
While the Intelligence Cycle has its origins in the world of military intelligence and psychology, it’s a form of guided sensemaking everyone can use. Whether you’re asked to write a paper, provide recommendations to support a decision or plan your next travels. To find out how we’ll first look into the phases of the cycle before giving the mental model a thorough reality check.
The Five Phases of the Intelligence Cycle
Granted, there’s no consensus on how many phases there are and what exactly they entail. For our purposes, we distil them down into the five stages mentioned above: Direction, Collection, Analysis, Dissemination, Feedback & Review. Let’s dive in.
The Intelligence Cycle starts by giving the analytical endeavour a direction and goal. This would typically come from what analysts call their customers. Customers can be a political decision-maker, police commander or business manager. We can apply it to anyone giving out the task at hand, though. The direction itself might be the analysis of media reports, an assessment of a national security threat, or a Deception Detection Analysis in a business intelligence context.
Phase one also includes the planning stage. It’s vital as it outlines how the goals are intended to be achieved and what is needed to do so. For instance,.analysts would draft a collection plan to establish what data and information they need, where they can get it and how. It’s advisable to consider a wide variety of reliable sources. The concept of garbage in, garbage out applies as the quality of your input determines the quality of your output. So it’s worth putting some thought into it right from the start.
If you’re not an analyst, you might get direction from a supervisor, manager or spouse. Not too much difference there. With the Intelligence Cycle in mind, you’d first define the problem and articulate what you intend to do as accurately as possible. In a best-case scenario, this is a collaborative process with those who give the direction. The goals will certainly move along the way. But it’s better to aim badly than not aim at all.
In terms of planning, applying the Intelligence Cycle can make your work more efficient. If you know where the journey is going, you’re more likely to know what you need to get there. This is your chance to make sure you are on the right track early and that your input is of the highest quality. So plan for your collection carefully and go beyond the first two pages of a Google search.
Phase two of the Intelligence Cycle is all about gathering data and information from the sources detailed in an analyst’s plan. Though, bear in mind: Whether the collected data will eventually be useful in achieving the goal is yet to be determined. At this stage, you’re only collecting, categorising and making sure you have covered all relevant sources. Start with the known knowns, that is whatever data you already have on file. Then consider the information that needs to be more actively collected.
There are many types of potential sources of information. If you don’t have an agency behind you, there’s a lot you can gather from open sources or by just picking up the phone and talking to people with the expertise. Depending on what you’re trying to do, here’s a handy open-source intelligence (OSINT) framework that might at least give you an idea of what’s possible.
Regardless, this is where your goal and plan come in handy again. It keeps you from collecting too little information. Or anything that you happen to come across. There’s no point in gathering material for the sake of it. It should be vetted continually to ensure it has potential relevance for your task at hand.
Here we are at the heart of the sensemaking process. It’s where an analyst turns data and information into actionable knowledge. But before you get to work, your collected data likely needs processing. Spreadsheets need to be cleaned and qualitative data categorised and synthesised. Perhaps you’re discovering duplicate, incorrect, or contradictory information. This is also the time to re-evaluate the relevancy of what you have collected.
Now on to the actual analysis. Sometimes you have large amounts of data and you need to uncover patterns and extract the meaning from them. This is the case when you have location data of burglaries and you’re tasked to find out in what area they mostly occur. Sometimes you have very little information and need to extrapolate. Asking the right questions is key to choosing the appropriate method. Remember the first step of the cycle. What you are trying to do: Describe a phenomenon, explain or evaluate it or predict what’s going to happen next?
Picking an analytical technique to run your data through is probably the hardest part. Depending on your goal, a simple SWOT Analysis might do to determine the strengths, weaknesses, opportunities and threats of a competitor. If your purpose is more evaluative or predictive, structured analytic techniques may be for you. If you’re looking to anticipate potential problems with a decision, a Premortem Analysis might be right. Or perhaps you’d like to evaluate satellite imagery.
Just be careful that you don’t overanalyse or overthink. Keep your goal in mind and acknowledge the possibility of Black Swans; improbable events that are unpredictable but might change everything. Check out my post about books on intelligence analysis if you’re looking to dive deeper into such methods.
The penultimate phase of the Intelligence Cycle is about telling people what you’ve discovered. This comes with its own challenges. In Greek mythology, Cassandra was a Trojan priestess of Apollo who had the gift of prophecy. Unfortunately, while Cassandra’s predictions were always true and accurate, nobody ever believed her. Likewise, the question for an analyst is: How can I make sure my findings have an impact?
If you’re left with the burden of choice, consider as many appropriate formats to disseminate your findings as possible. Will writing an email suffice or do you better publish it as a paper? Is it a matter of penning a report, or do you have to, god forbid, put together a PowerPoint presentation? Maybe it’s best to tell it as a story, write a strongly-worded “Dear Colleague” letter or get the puppets out. It all depends on your audience.
It’s useful to bear in mind who your audience is and what they best respond to in relation to what you want to achieve. The level of their data literacy is one criterion, their attention span is another. You’d want to avoid jargon nobody understands while limiting your delivery to the absolute minimum necessary information. If you don’t want to end up like Cassandra, you may also want to think about the marketing aspect of your findings. Truth and wisdom do not always speak for themselves.
This is especially true if your task involves making recommendations for decision-making, which is an art form in and of itself. It certainly helps if you have a good personal relationship with the ones you’re trying to influence. So if you do have an open communication channel, your best bet might even be to have a face-to-face meeting. Use the art of negotiation to figure out what your counterpart really wants and how your work fits in.
5. Feedback & Review
The final step in the Intelligence Cycle is to get feedback from your customer about your product. Frankly, there are not too many differences between an analyst’s world and yours. How useful was your work for the customer? What changes would they prefer next time? This phase can also involve a personal self-evaluation and a reflection on lessons learned about how to approach your customer the next time.
The Reality of the Intelligence Cycle
It’s time to give the Intelligence Cycle a reality check. Because the utility of our mental model is being hotly debated among analysts and academics alike. The most notable criticism comes from former intelligence officer and professor Arthur Hulnick.
Broadly speaking, the Intelligence Cycle is often criticised for not adequately reflecting the real world. The process, its critics say, isn’t really cyclical in practice and sensemaking would be anything but linear anyway. In reality, analysts would always be at the drawing board to reduce unknowns. They wouldn’t sit around waiting for anyone to give them a direction either. With that being said, here are some caveats we should consider when using the Intelligence Cycle:
- Direction is indeed not always the starting point. Perhaps you never really get a proper direction. Or you get one and it’s vague and useless. Whoever gave it to you has no clue what they want or they act on the assumption that they know what they want when they see it. So you might wind up at the collection phase as your de-facto first step.
- When was the last time you focused on collection alone? If you’re an academic or writer, you’re probably always gathering and processing information — without a clue if and how you’ll use it. Discovering something new might spark your interest in pursuing a new project. Then, as you stumble upon more resources, you might have to dismiss your whole endeavour again.
- Analysis is also not such an isolated step of course. You might be under time constraints and clean your data on the go or not at all. You’ll also most likely identify gaps in your collection so you have to go back to gathering more data or review your goal altogether. Maybe you even have to skip analysis and dissemination proper by just providing some raw data and you’re done.
- There’s a problem with the Dissemination phase, too. You wouldn’t be the first person to produce a powerful report for your audience to completely ignore. For various reasons: Maybe the need for your manager has changed. Maybe your customer just wanted their existing beliefs validated. You failed to read between the lines, or your spine got in the way.
- That’s also why the Feedback phase can be an act of wishful thinking. Your customer might be cherry-picking what suits their narrative and have no time to give detailed feedback. Neither have you because you’re already on to the next project.
In sum, the reality is that many phases of the supposed cycle happen simultaneously, in reverse order, or not at all. Regardless, any attempts to replace the Intelligence Cycle have been in vain. More interactive and complex conceptualisations of the process such as the Web of Intelligence never caught on. Most likely because of its simplicity, the Intelligence Cycle just won’t die.
Sensemaking is a mess. Of course, the Intelligence Cycle cannot reflect life’s complexity in its entirety. But we could argue that that’s the whole point. It seems like this mental model is so popular precisely because it’s highly simplified. Very much like DODAR and the OODA Loop, its close relatives in the family of decision-making tools.
Ultimately, the Intelligence Cycle is a tool to navigate the discovery of knowledge. A guide to finding a start when you don’t know where to begin or to get you unstuck when you’re unsure what to do next. If the phases only serve as anchor points in your work process, the Intelligence Cycle has done its job.