Complex Times, Simples Rules

Quentin Prideaux

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Reorganize. Optimize. Redesign. Organizations do it all the time. It’s all about improving efficiency, profitability, responsiveness, and competitive advantage. It touches all parts of all organizations at one time or another. Whether in customer-facing functions, back-office, production or administration, it’s a fact of life. And when the latest improvement project comes to an end, rules are inevitably created to ensure that the new design operates to plan. These new rules will relate directly to the results expected. Various incentives and sanctions will persuade employees to adhere machine-like to these new rules, and to these new rules alone. Unfortunately, this approach creates a number of difficulties.

First of all, any attempt to treat organizations as machines is ultimately doomed to fail. People are not machines, and they typically don't respond well when treated as machines. Over time, perfectly normal human behavior patterns will inevitably conspire to undermine any rigid process. Lazy employees will break the process to make their lives easier, ambitious ones will do so to advance their own reputations. Others will operate outside of the rules to compensate for perceived shortcomings, or simply to relieve their boredom. While these behaviors can be mitigated to some extent by threats, rewards and the endless attention of full-time supervisors, a rigid process is always waiting to fail, and will do so at the earliest opportunity.

In addition, even if an organization could behave like a machine, the rules of operation no longer apply when the environment changes. Efficient processes are highly environment-specific. When circumstances change, efficiency declines and recapturing that efficiency means new rules. Employees must either learn to follow the new rules, or leave the organization (voluntarily or not).

Furthermore, repeated or uncoordinated re-organizations also leave behind multiple sets of rules. Organizations are left with gaps between processes and departments, mis-aligned objectives, and overlapping rules that lead to redundancy and inconsistency.

Finally, all large organizations have rules that operate at different levels of generalization. Some rules deal with broad strategic objectives, others with day-to-day operational decisions. Most employees are recognized and rewarded for compliance with low-level, process-oriented rules. When there is a conflict between pay and promotion and the more strategic exhortations of senior managers most employees will respond to their immediate needs. This trend is reinforced when ‘vision’ and ‘mission’ statements are vague or lack sufficient detail to differentiate their organization from others. (One anecdote describes chief executives at several major firms who were presented with a selection of mission statements from various public companies. Many could not identify the mission statements of their own firm. Whether or not this story is true, many will be familiar with the symptoms.)

If the existing rules within our organizations are inadequate, then what is the answer? Do we need more rules, encompassing every facet of the organization? Or do we target our efforts to identify all possible scenarios and construct a rule for every situation? Do we invest in enhanced networks, technology, and software tools to keep everyone on course at peak efficiency, even if that means transforming the organization into a "big brother" environment where every move is monitored? Do we resign ourselves to a continuing stream of reorganizations and redesigns every time management comes up with a new plan to face new challenges? Do we rely on employees to manage multiple sets of rules simultaneously, choosing the correct trade-off in every situation and creating rules where none exist? Or do we construct hierarchies of decision-making authority with decisions and all their attendant data passing endlessly up and down?

Fortunately the answer to these questions is "none of the above," and ‘Complexity Theory’ provides some insights and approaches that can help us find an alternative.

The Science of Complexity Theory

Complexity Theory addresses, among other things, rules that apply to large numbers of autonomous elements. These elements are allowed to interact with each other and with their surroundings according to a given set of rules. Naturally occurring in living systems, where it has been developed over millions of years of evolution, this ‘theory’ is the driving force behind the highly efficient flocking of birds and the problem-solving ability of ant colonies. It is when we begin to think of employees as ‘autonomous elements’ within an organization that the relevance to writing effective business rules begins to emerge.

What we want to take fromour understanding of ‘Complex’ systems is two things: their ability to solve certain problems automatically, and their enormous efficiency.

Complex natural systems have the remarkable ability to automatically solve difficult problems without having any view of the problem itself. For example, an ant colony can work out which of two food sources is closest even though individual ants can't see the food, have no concept of distance, and have no idea how many food sources, if any, are even available.

The efficiency with which the ant-food and many other problems are solved in nature is extraordinary. Imagine trying to encode in an ant’s brain all of the detailed instructions that would be required for it to weigh all possible types and distances of food sources in all possible environments. Then imagine the effort the ant would have to exert to discover which exact food sources were available in which environments. By the time the ant had visited all surrounding areas, discovered all food sources, calculated all distances, weighed terrain, weather and harvest-ability the food would likely be gone or the ant would be dead. Even if the ant had the intellectual capacity and longevity to process such a complex problem, it would need some form of sophisticated communication to inform other ants of the discovery, not to mention a system for negotiating with ants that might have reached other conclusions, and a command hierarchy to resolve disputes and get the colony mobilized to retrieve the food. If we compare this overhead of structure, specialized communication, central data processing, and repeated decision making with a large business many parallels are apparent.