Why are some resources (in the US, at least) managed by government, while others are managed by the private sector (that is, business)? Simply put, some resources are public by nature—roads, for example, and the armed services—and are therefore managed collectively. Other resources—manufacturing, for example—are best run by private enterprise.
Intelligence is conducted both in the public sector (by the government), and in by private sector (by businesses and other private organizations.) Intelligence in the public and private sectors, though similar in many respects, operates under very different sets of “value” assumptions and rules, respectively. In the public sector, it is the case that everything has been mandated or otherwise agreed to be in the public, collective benefit. You must do it, it’s the law. Although fiscal responsibility is certainly important, it is not the overriding goal of government to turn a profit.
Business on the other hand, must turn a profit. That is really its only “mandate”. Without profits, businesses—in the classic capitalistic sense, at least —would not exist. And each component function or “process” within a business must contribute to that profit. There is a whole discipline called business process re-engineering devoted to systematically identifying business processes that do not contribute sufficiently, and finding ways to fix that.
When I was a science student, physics lectures would sometimes begin with the teacher’s saying, “Assume for a moment there is no gravity, and no friction.” We all know these forces do exist, but in understanding the principles of elementary physics, they tend to make things seem overly complex. By assuming temporarily that they are not there, we can gain insights into how the physical world works that, absent these assumptions, we could not have gained. (Before anything is attempted in the real world, of course, gravity and friction need to be re-introduced into the model.)
In the “world of knowledge”, a similar thing occurs. It may be useful for a moment to assume that we do not need profits—but before any real decisions are made, we need to factor that inevitable need back in.
The US government’s intelligence cycle model does not directly address the need for creating value (economic or otherwise)—primarily because its value is assumed to be self-evident. The intelligence cycle does not consider the customer/user benefit in any detail. In fact, government intelligence operations are by design separated from, and operated at arm’s length from, the user operations of “policy-making”. The intention in designing the government intelligence system that way was to ensure that intelligence production would not be biased by the needs and assumptions of users. Intelligence operations were conceived of as “pure knowledge”, apart from the concerns, desires, and preconceptions of policy-makers.
In business, however, it is rare that intelligence is assumed to be both necessary and immune from strict accountability. In most cases, intelligence must answer to the same kinds of ROI demands that other business processes are also subject to. A positive “return on intelligence” is not just a nice-to-have bonus—it is necessary if the intelligence function is to survive and thrive.
Excerpt from the Introduction to The Knowledge Value Chain Workbook by T.W. Powell.