During self-organization, internal entropy decreases and internal information content increases. Information parallels order increase and entropy decrease and is a reflection of the internal structure determining the efficiency of the processes. The principle of least action from physics states that every motion in nature happens with the least expenditure of the product of energy and time, which is the quantity of action. Therefore increasing action efficiency of those processes is obeying fundamental principles in science and leads to more advanced systems. We present results from our most recent simulations and data analysis of the positive and negative feedback loops between the characteristics of evolving complex systems. Those loops lead to exponential growth with sinusoidal oscillations which can be modeled with a system of coupled harmonic oscillators.  The solutions of this model provide an exponential equation superimposed with sinusoidal oscillations. The amplitude and frequency of those oscillations also grow exponentially with time.  This solution matches well data and gives us an insight in the feedback loops in evolving complex systems as a proposed mechanism for their observed exponential rates of self-organization and progressive development.