Hierarchical and Evolving Systems
In short Formal org charts show who is authorized to decide; they do not show who actually decides. Rakitov and co-authors add a political lens: every level of a hierarchy has its own elite, and organizations evolve in ways that can shift suddenly. For an analyst this means mapping real power at each level and tracking a few key parameters instead of everything.
Based on: A. I. Rakitov et al., Systems Analysis and Analytical Research: A Guide for Professional Analysts (in Russian), sections 1.4–1.5.
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Key ideas#
Hierarchy comes from power#
A hierarchy arranges parts from higher to lower by power, meaning the ability of some to direct others. The authors stress that size or complexity alone does not create hierarchy; a beehive or an ecosystem is complex without anyone holding power. In human organizations, power is what produces the levels.
Every level has an elite#
On each level of a hierarchy there is a group with authority, significant resources and influence over the rest of that level. The authors call it the elite of that level. Elites can rest on law and position, on tradition or religion, on wealth or unique know-how, or be hidden altogether. Across cultures, the authors argue, elites form around power and wealth, which convert into each other easily.
The practical warning: an analyst who ignores this structure risks wrong forecasts and solutions that will not work, because elite decisions can be unpredictable and break the expected course of events. This does not replace stakeholder analysis. It adds a dimension: not only how people feel about a change, but who can actually affect the outcome, regardless of formal role.
Size is a poor measure of complexity#
For social systems, the number of elements says little; how the system is organized matters more. Companies that began with one or two people can grow rapidly.
System and environment over time#
The authors propose a simple matrix. Both the system under study and its environment can be in one of two states over a period: no significant change, or significant change. Change can be positive or negative. The analyst’s job is to keep the system in the state of significant positive change, whatever the environment is doing. That requires continuous monitoring of the environment, even when it looks chaotic.
Self-organization and bifurcation#
The authors draw on synergetics (H. Haken, I. Prigogine), an interdisciplinary framework for open, self-organizing systems from molecules to societies. Structure is not imposed from outside; it emerges from cooperation among parts while energy or resources keep flowing in. A system that runs steadily can reach a bifurcation point, where its path changes abruptly; the authors cite the break-up of large states as historical examples. To see such turns coming, synergetics suggests tracking a few order parameters, the quantities that capture the essence of the process, rather than collecting data on every variable.
How to apply it#
- For each level of the organization in scope, list the formal decision makers.
- Next to them, list who actually shapes decisions on that level and what their influence rests on (position, expertise, relationships, resources).
- Add this “real power” column to your stakeholder map and plan engagement accordingly.
- Describe the current state of the organization and its environment with the change matrix, and agree how you will monitor the environment.
- Choose three to five order parameters that capture the essence of the process you are changing, and track them regularly.
- When an order parameter moves sharply, treat it as a possible turning point: revisit forecasts and options.
Example#
At The Workshop, the org chart says workshop managers approve parts orders. Interviews show that in most shops a senior mechanic decides what to order, because the manager relies on their know-how. That senior mechanic is the elite of the shop level. The analyst adds senior mechanics to the stakeholder map as key influencers and invites them to design the new reorder rules. For monitoring, the team picks a few order parameters: share of bookings made online, parts stock-outs per week, and median turnaround. When a competing chain opens nearby (environment change), the team checks these parameters weekly instead of monthly.
Pitfalls#
- Mapping only the org chart → find who really decides at each level.
- Treating elites as a problem to bypass → engage them; their support often decides adoption.
- Tracking dozens of metrics → pick a few order parameters that express the core process.
- Assuming steady trends will continue → watch for signs of a turning point.
Sources and further reading#
- A. I. Rakitov, D. A. Bondyaev, I. B. Romanov, S. V. Egerev, A. Yu. Shcherbakov. Systems Analysis and Analytical Research: A Guide for Professional Analysts (in Russian). Moscow, 2009, sections 1.4 and 1.5.