When More Information Isn’t the Answer
Intelligence has become one of the more elastic words in modern business.
There is market intelligence, business intelligence, competitive intelligence and consumer intelligence. Retailers use increasingly sophisticated systems to predict what customers will buy. Streaming services anticipate what viewers might want to watch. Financial platforms collect, organize and analyze enormous volumes of market data. And artificial intelligence has introduced an expanding category of products promising some form of intelligence on demand.
Yet much of what is described as intelligence is, more accurately, information. And information, however plentiful, sophisticated or rapidly produced, is not necessarily intelligence.
The distinction is not semantic. It matters because investment professionals now have access to more data, research, transcripts, expert commentary, news, alternative data and machine-generated analysis than at any previous point in the industry’s history. The longstanding problem of gaining access to information is gradually being replaced by a different one: determining what, among everything available, actually matters.
For investors, the problem is increasingly not scarcity but abundance.
The question, then, is not simply how to obtain more information. It is how to turn information into something useful for judgment and decision-making.
Intelligence begins with a decision
I have spent much of my career working with intelligence in very different settings. I began as an intelligence officer and special operations intelligence officer in the Marine Corps and U.S. Marine Corps Forces Special Operations Command, and later worked in the private sector as a managing director at Veracity Worldwide, a global corporate intelligence firm. Today, my work at Enquire brings me into another information-intensive environment: investment research.
The contexts are plainly different. A military commander, a corporate executive and an investor face different questions, sources and consequences. But they share an important constraint. Each must make consequential decisions with incomplete information and under conditions of uncertainty.
That is the problem intelligence is intended to address.
There are formal doctrinal definitions of intelligence, some of which I will return to later in this series. A useful working definition is simpler:
Intelligence is decision-relevant knowledge, deliberately developed and placed into context in support of a specific objective, with the purpose of reducing uncertainty and enabling better judgment.
The important feature of that definition is purpose.
A fact can be accurate without being useful. A report can be meticulously researched without answering the question that matters. A database can contain every relevant datapoint and still leave its user uncertain about what to do.
Marine Corps intelligence doctrine draws much the same distinction. Data and information do not become intelligence simply because they have been collected. They must be focused, interpreted and placed in context for a particular decision.
Good intelligence work therefore begins before the search for information. It begins by defining the problem: the decision to be made, the questions that decision depends upon, the uncertainties that matter most and the evidence that might alter the current assessment.
Without that discipline, research can easily become an exercise in accumulation.
The danger of knowing more
One of the more counterintuitive lessons of intelligence work is that more information does not necessarily make a decision-maker better informed.
Sometimes it does the opposite.
When little intelligence is available, uncertainty is difficult to ignore. A capable commander knows that important things remain unknown and plans accordingly. Contingencies are developed, assumptions are identified and risk is treated explicitly.
A headquarters saturated with reporting can create a different problem. Imagery, databases, assessments and operational updates produce the impression that the answer must exist somewhere, if only enough material is reviewed.
The natural response is to keep looking.
More reporting is requested. More sources are consulted. Competing explanations multiply. The amount of information increases while the decision itself may become no easier to make.
This is not an argument for less information. It is an argument for discrimination. Information has value to the extent that it contributes to the decision.
In operational settings, that distinction was often stark. A single piece of decision-relevant intelligence could outweigh pages of supporting reporting. Sometimes the critical question was extraordinarily narrow: Was a target present? Had a particular condition been met? Had a key indicator occurred?
A single answer might determine whether an operation proceeded.
The surrounding information still had value. It provided context, supported analysis and could matter later. But at the point of decision, one piece of intelligence mattered disproportionately because it was directly connected to action.
That is one of the central functions of intelligence: not merely to tell a decision-maker what is known, but to distinguish what matters from what merely exists.
Military intelligence doctrine explicitly warns that presenting a commander with all available data can magnify uncertainty rather than reduce it. Irrelevant, incomplete and contradictory information can overwhelm the very person the intelligence function is meant to support.
The observation feels increasingly relevant outside the military.
From information scarcity to information abundance
Investment research has historically devoted considerable resources to solving problems of access.
Where can I find the data? Who has researched this market? How can I locate the relevant filing? Is there an expert who understands the industry? Can I search across transcripts, company documents and third-party research efficiently?
Technology has made many of these tasks dramatically easier. Generative AI can search large collections of documents, extract datapoints, summarize lengthy materials, compare companies, surface themes and assemble research products at remarkable speed.
These are meaningful advances. But faster access to information does not, by itself, solve the intelligence problem.
It may even make the distinction between information and intelligence more important.
As the cost of finding and producing information falls, the scarce resource shifts. The challenge becomes deciding what deserves attention, which questions are most consequential, where important gaps remain, how conflicting evidence should be interpreted and what uncertainty still cannot be resolved.
Those are not primarily retrieval problems.
They are intelligence problems.
The implication for investment research is significant. The most useful research technology will not simply make it possible to search more sources or generate longer reports in less time. Its value will increasingly depend on whether it helps investors structure the problem itself: to identify the questions that matter, separate signal from noise, recognize gaps in the evidence, test competing explanations and understand what would have to be true for an investment thesis to hold.
In other words, the objective is not to make the pile bigger, faster.
It is to transform what is available into something a decision-maker can use.
That raises a deeper question. What actually occurs during that transformation? How does raw data become information, information become knowledge, and knowledge become the kind of understanding that supports sound judgment?
That is where Part II begins.
Next: What Is Intelligence? Part II: From Information to Understanding