In order to analyze this assumption we must think about some terms. The initial one is control.
Control needs feedback. Many dynamic systems are not stable if we do not feedback our actions with information of their states. This affirmation is not an opinion, it is a fact. A system can become more stable with feedback, and it is not strange for economists. Economists have learnt to smooth the behavior of the economic cycles as their actions depend on the national accountancy.
Another concept to analyze is complexity. There is not a shared, generalized and
accepted meaning of complexity. Politicians have only an intuitive idea about the meaning of complexity and its importance in economy management. It is important to get a quantitative focus for complexity control.
If we think about complexity as a property of the economic system, we will be able to answer the initial question. A system is characterized by a set of state
variables. As there are some relationships among them, we only need feedback from a subset of the variables that we can define to maintain the system under control.
In previous situations we could preserve the stability of the system measuring well-known variables as GDP, unemployment, rate of interests, etc. But nowadays, these variables cannot predict the future because of a complexity increase. They could not be sufficient to control the system in the actual turbulent state.
Quantitative complexity is related to manageability of the system. If we use a measure of complexity to analyze an economy we can know if the actions that we predict from the feedback with well-known economic variables can be adequate.
Governments must understand that a complex world cannot be controlled with old feedback. It is necessary improve the control systems and reduce complexity in order that they can do their work effectively.
But if, now, the first objective is to maintain complexity under control, we will need a measure of it to feedback and notice that we are approaching a better or worse situation.