To exist today is to be connected. Inter-industry, supranational integration of supply chains is the field of active research. Large old consulting companies, such as IBM, Microsoft or EY, as well as new independent projects are already integrating their solutions into public platforms. For example, Microsoft announced the launch of an identification system based on the Bitcoin blockchain, with Civic being one of its partners; Amazon extends its service from IBM’s platforms to Ethereum.
Until now, there has never existed a supranational platform where participants of long supply chains could plan everything from start to finish. When tracking & accounting systems are compatible-by-default, transactions are not to be made spontaneously, and not necessarily in a local-interaction-points logic. Every business transaction is to be an act of the activity being registered in the complete supply chain. An act of planning gives birth to the transaction; it starts to fully exist before it actually happens. Each individual actor now depends not only from direct partners (buyers, suppliers, and capital providers), but also from all other participants in the supply chain, along its entire length.
Since your failure becomes the failure of others, everybody suddenly cares about you.
Illustration: Stochastic Method vs Analytical or Why Could Free Market Lose to Plannable Supply Chains
Let’s determine the area of this figure cut from a piece of cardboard.
1. Stochastic Method (aka Free Market)
We have no theory and no idea about planimetry. We have no ruler, no scales, no beakers. We cannot measure distances and angles, we cannot weigh the cardboard and compare the mass with one of the known-area samples of the same material and the same thickness, we cannot put the figure in water and calculate the displacement volume.
Without a ruler, we must start with obtaining the unit figure whose area is exactly 1 unit. It doesn’t have to be a square, but it needs to fit the measured figure completely, with minimum margins, like this:
Then we wait for rain and — once it’s raining lightly, only a little — put the two-layer sandwich under it. We let the drops cover the boards, but only as long as we can distinguish the individual drops. Then we count the number of drops inside the figure and divide by the total number of drops. The ratio is the wanted area, measured in units. The more drops (statistical set) we collect, the more accurate the result. This is the simplest interpretation of a very popular Monte Carlo method.
The described approach allows us to obtain a very approximate answer, but considering the level of ignorance and a state of being without tools for research, it’s a great compromise.
Every transaction in the free market is like a drop of that rain. The free market relies on the natural flow of natural incentives; it simply waits for decisions of market participants and voters on all issues and averages the results, in the form of equilibrium prices and democratic management decisions. To function better, the free market “needs a bigger board”, to involve as many countries as possible.
Of course, there are elements of planning and regulation but, globally, free markets do not represent a sufficiently coherent and sustainable system; ultimately, the system lacks a solid scientific basis. Although Nobel prizes in economics are given on a fairly regular basis, including those for theories that contradict each other, people do not live in accordance with any “universal laws of nature” and do not obey any rules that would serve all of humankind.
This disarray system is quite attractive: it postulates the goal of avoiding violence and stimulates initiative. The system was tested by life in a statistically significant number of cases over a long time period. There are drawbacks as well. While based on the belief of the equality of all, the system rolls down to an excessive economic inequality, both among people and among regions. The system is weak when faced with urgent or very large tasks, such as the global energy shortage.
2. Analytical Method (aka Plannable Supply Chains)
If we have a long enough ruler, our approach to area measurement changes:
- Choose a reference point and a step;
- Mark the entire field with two angled sets of parallel lines (the grid);
- Count how many parallelograms (elements) get inside the target shape and add half the number of crossed (boundary) elements.
Compared to the previous method, this method is more accurate and the role of luck is almost null. Of course, the choice of reference point and the angles of the grid affects the results, but with sufficient resolution of the measurement, this dependence is insignificant.
Many companies don’t rely solely on the natural market; they have long-term plans. In fact, sometimes they even artificially create demand. Since the basic material needs of people in rich countries have been met decades ago, there is no real sense in many things a typical modern consumer basket contains, less so in their periodic renewals.
Planning is natural for humans; however, although it’s reasonable, it’s not easy. Even basic planning tasks may puzzle. For example, manufacturing bolts, nuts, gaskets, and spring rings takes different technologies that spend different amounts of energy per mass and per product unit, and create different relative amounts of waste. That is, with a change in the volume of production of complete sets, the energy and waste utilization change non-linearly. In relation to the total number of different products in the sub-economy under consideration, the number of arithmetic operations to calculate a balanced production plan is growing faster than the degree of 3. Until now, the tracking systems and computing power necessary for accurate transnational production planning have never been combined into a sufficiently powerful single fist.
Suppose that, in addition to the ruler, we got a pair of dividers, a protractor, and most importantly — a miracle of planimetry knowledge. From the height of such wisdom, we can select regular parts inside the figure (triangular and elliptic elements, the area of which can be calculated by simple formulas) and apply the previous method to the remaining “chaotic” boundaries. Accuracy is up, labor costs are down.
Planned economy is not a command economy!
The “laws” of economics, even if they exist in the truly scientific sense, can hardly be changed, but they can be tamed, just as a carefully constructed dam does not cancel gravity, but turns the threat of flooding into a source of light and heat.
In a conventional economy, the consumer (chaotic, irregular) sector is dominant and everything is based on it. Personal consumption and personal income determine the limits of the possible. If the economy turns around a small amount of money, the large-scale transformation that requires huge investments is impossible.
It doesn’t have to be that way. The physical limits lie elsewhere. In our analogy, the consumer sector is an outside contour area, the “irregular boundary”. The inner core of the system can be scientifically managed; it can be based on the “laws” (that we don’t know just yet) and corresponding formulas, making it fully predictable.
Just as we can distinguish analytically computable areas in our figure — “ellipses” and “triangles” — we can reserve “regular” sectors in the economy. Vital and comprehensive industries, such as energy, can be taken care of in “analytical” circuits, independent of the market forces, the institution of ownership, and the construct of “money” itself.
If you spend three hours to collect firewood in your deep-forest off-grid cabin, and then spend three hours reading a book by the fireplace, do you value these activities equal? In supply chains, the order in which things happen is important. Without energy, nothing can be created. In a city where there is no electricity, within a few days there will be no functioning municipality. Just summing up the contribution of energy to the GDP, on the same grounds as sales of a mobile app store, is neglecting common sense. If we were to observe the true value of the sector, our attitudes towards regulating it would be way stricter.
Money in such a sub-system serves only as a means of accounting; it creates no profits. In the “regular” sectors of the economy, planning will provide added value to the extent the society is willing to contribute to its survival. The amount of effective spendable demand of the population will cease to be a physical limitation, as it is in the quantitative theory of money.