complex-systems

What Are Complex Systems? Complex Systems In A Nutshell

Complex systems consist of many elements interacting with each other in a disordered way. This disorder makes the behavior of complex systems difficult to predict. To understand complex systems think of them as a system is where the whole is more than the sum of its parts.

Understanding complex systems

Complex systems comprise the very fabric of life itself. They are seen in the way birds organize themselves into flying formations and in the emergent structures of plants, snowflakes, and galaxies. Complex systems also describe the formation of human social networks and the communication patterns and social capital that form as a result.

Despite the prevalence of complex systems, researchers cannot agree on a concise definition and there has been relatively little scientific study into the topic. Perhaps the most accepted descriptor of a complex system is one with “wholes that are more than the sum of their parts.” Importantly, the behavior of these wholes cannot be predicted or explained without looking at the interaction between multiple, interconnected components.

Properties of complex systems

Complex systems exhibit certain properties that arise from the dependencies and relationships existing between their constituent parts.

Some of these properties include:

  1. Emergence – from the interaction between individual elements arises the behavior of the system as a whole. In complex systems, this higher-order behavior cannot be created by aggregating behavior at the element level. In other words, higher-order behavior arises spontaneously.
  2. Transitions, tipping points, and non-linearity – complex systems also display non-linear dynamics, which means they may suddenly behave differently or exhibit a new regime. Similarly, complex systems may display a high degree of stability in one moment and become chaotic in the next. Examples of complex systems with these traits include revolutions, pandemics, and financial crises. 
  3. Unpredictability – since interactions are dynamic and non-linear, the behavior of a complex system cannot be predicted by inspecting its individual components. Unpredictability is related to emergence and so-called Black Swan events, which occur when small changes to a system become large effects over time.
  4. Evolutionary dynamics – complex systems are never at rest and do not move toward a knowable endpoint or equilibrium. The mechanism for evolution begins with variation in a few elements that flourish by multiplying in the system. These elements may change the external environment of the system. Conversely, the external environment is also able to change the system by introducing new variations.
  5. Adaptation – some complex systems are adaptive in that they can change and learn from experience. That is, they can organize or reorganize their internal structure in the absence of an external agent. Examples of these systems include the stock market, social insect colonies, the immune system, and the biosphere.

Implications of complex systems for organizations

Now that we have defined the characteristics of complex systems, let’s take a look at the implications of complexity itself in an organizational context. 

South African philosopher and complexity researcher Paul Cilliers defined seven.

1 – Relationships are fundamental 

For organizations to succeed, Cilliers suggested it was the nature of interactions between employees that drive innovation and company culture. 

Focusing on how people are proximally located and rethinking the way meetings are conducted should be prioritized over training individuals to be creative in isolation.

2 – Stable states are not desirable 

While many organizations favor stability and certainty, the truth is they become stagnant and uncompetitive without continuous improvement and the embracing of change.

3 – No organization can be understood independently of its context

Cilliers acknowledges that vision and mission are important, but they can inadvertently define the imaginary boundaries of a comfort zone. Successful organizations interact with their broad environment, which includes other organizations.

4 – The history of an organization determines its nature 

Two organizations with similar histories are not the same. The history of each is comprised of countless events and interactions distributed through the system. These interactions alone determine a unique evolutionary trajectory for both companies.

What’s more, decision-makers should never assume that a practice that works well in one context will do the same in another.

5 – Novel characteristics, desirable or undesirable, may emerge 

An undesirable characteristic may describe the plummeting sales in a previously popular product. Though the organization would prefer otherwise, it should not be surprised by emergence when it occurs. 

By the same token, more desirable characteristics should not be suppressed or ignored simply because they were unexpected. 

6 – Outcome magnitude is determined by the size of the cause and the context and history of the system 

This means the organization should be prepared for the unexpected and not underestimate the potential impact of an insignificant event. 

In a recent TED talk, entrepreneur and CEO Margaret Heffernan suggested companies transition from “just in time” to “just in case”. That is, the focus should switch from efficiency to resilience to counter the unpredictability of complex system outcomes.

7 – Complex organizations cannot grow with excessive central control 

Lastly, it is suggested organizations distribute control through their systems. Too often, managers tasked with making unpopular decisions are keen to offload the responsibility to others and decentralize control. But when the decision is considered a popular one, control is highly centralized. 

As workplaces become increasingly autonomous, the opportunity for all employees to feel motivated and engaged in meaningful work is critical. To achieve this, they must be given some degree of decision-making power – or what we might call autonomy.

Key takeaways:

  • Complex systems consist of many elements interacting with each other in a disordered way. This disorder makes the behavior of complex systems difficult to predict.
  • Complex systems exhibit certain properties that arise from the dependencies and relationships existing between their constituent parts. Some of the core properties include emergence, non-linearity, unpredictability, evolutionary dynamics, and adaptation.
  • The implications of complex systems for organizations were researched by researcher and philosopher Paul Cilliers. The implications suggest relationships are fundamental and stable states are not desirable. Cilliers also found that desirable and undesirable novel characteristics may emerge at any time and that complex organizations could not thrive with centralized control.

Connected Analysis Frameworks

Failure Mode And Effects Analysis

failure-mode-and-effects-analysis
A failure mode and effects analysis (FMEA) is a structured approach to identifying design failures in a product or process. Developed in the 1950s, the failure mode and effects analysis is one the earliest methodologies of its kind. It enables organizations to anticipate a range of potential failures during the design stage.

Agile Business Analysis

agile-business-analysis
Agile Business Analysis (AgileBA) is certification in the form of guidance and training for business analysts seeking to work in agile environments. To support this shift, AgileBA also helps the business analyst relate Agile projects to a wider organizational mission or strategy. To ensure that analysts have the necessary skills and expertise, AgileBA certification was developed.

Business Valuation

valuation
Business valuations involve a formal analysis of the key operational aspects of a business. A business valuation is an analysis used to determine the economic value of a business or company unit. It’s important to note that valuations are one part science and one part art. Analysts use professional judgment to consider the financial performance of a business with respect to local, national, or global economic conditions. They will also consider the total value of assets and liabilities, in addition to patented or proprietary technology.

Paired Comparison Analysis

paired-comparison-analysis
A paired comparison analysis is used to rate or rank options where evaluation criteria are subjective by nature. The analysis is particularly useful when there is a lack of clear priorities or objective data to base decisions on. A paired comparison analysis evaluates a range of options by comparing them against each other.

Monte Carlo Analysis

monte-carlo-analysis
The Monte Carlo analysis is a quantitative risk management technique. The Monte Carlo analysis was developed by nuclear scientist Stanislaw Ulam in 1940 as work progressed on the atom bomb. The analysis first considers the impact of certain risks on project management such as time or budgetary constraints. Then, a computerized mathematical output gives businesses a range of possible outcomes and their probability of occurrence.

Cost-Benefit Analysis

cost-benefit-analysis
A cost-benefit analysis is a process a business can use to analyze decisions according to the costs associated with making that decision. For a cost analysis to be effective it’s important to articulate the project in the simplest terms possible, identify the costs, determine the benefits of project implementation, assess the alternatives.

CATWOE Analysis

catwoe-analysis
The CATWOE analysis is a problem-solving strategy that asks businesses to look at an issue from six different perspectives. The CATWOE analysis is an in-depth and holistic approach to problem-solving because it enables businesses to consider all perspectives. This often forces management out of habitual ways of thinking that would otherwise hinder growth and profitability. Most importantly, the CATWOE analysis allows businesses to combine multiple perspectives into a single, unifying solution.

VTDF Framework

competitor-analysis
It’s possible to identify the key players that overlap with a company’s business model with a competitor analysis. This overlapping can be analyzed in terms of key customers, technologies, distribution, and financial models. When all those elements are analyzed, it is possible to map all the facets of competition for a tech business model to understand better where a business stands in the marketplace and its possible future developments.

Pareto Analysis

pareto-principle-pareto-analysis
The Pareto Analysis is a statistical analysis used in business decision making that identifies a certain number of input factors that have the greatest impact on income. It is based on the similarly named Pareto Principle, which states that 80% of the effect of something can be attributed to just 20% of the drivers.

Comparable Analysis

comparable-company-analysis
A comparable company analysis is a process that enables the identification of similar organizations to be used as a comparison to understand the business and financial performance of the target company. To find comparables you can look at two key profiles: the business and financial profile. From the comparable company analysis it is possible to understand the competitive landscape of the target organization.

SWOT Analysis

swot-analysis
A SWOT Analysis is a framework used for evaluating the business’s Strengths, Weaknesses, Opportunities, and Threats. It can aid in identifying the problematic areas of your business so that you can maximize your opportunities. It will also alert you to the challenges your organization might face in the future.

PESTEL Analysis

pestel-analysis
The PESTEL analysis is a framework that can help marketers assess whether macro-economic factors are affecting an organization. This is a critical step that helps organizations identify potential threats and weaknesses that can be used in other frameworks such as SWOT or to gain a broader and better understanding of the overall marketing environment.

Business Analysis

business-analysis
Business analysis is a research discipline that helps driving change within an organization by identifying the key elements and processes that drive value. Business analysis can also be used in Identifying new business opportunities or how to take advantage of existing business opportunities to grow your business in the marketplace.

Financial Structure

financial-structure
In corporate finance, the financial structure is how corporations finance their assets (usually either through debt or equity). For the sake of reverse engineering businesses, we want to look at three critical elements to determine the model used to sustain its assets: cost structure, profitability, and cash flow generation.

Financial Modeling

financial-modeling
Financial modeling involves the analysis of accounting, finance, and business data to predict future financial performance. Financial modeling is often used in valuation, which consists of estimating the value in dollar terms of a company based on several parameters. Some of the most common financial models comprise discounted cash flows, the M&A model, and the CCA model.

Value Investing

value-investing
Value investing is an investment philosophy that looks at companies’ fundamentals, to discover those companies whose intrinsic value is higher than what the market is currently pricing, in short value investing tries to evaluate a business by starting by its fundamentals.

Buffet Indicator

buffet-indicator
The Buffet Indicator is a measure of the total value of all publicly-traded stocks in a country divided by that country’s GDP. It’s a measure and ratio to evaluate whether a market is undervalued or overvalued. It’s one of Warren Buffet’s favorite measures as a warning that financial markets might be overvalued and riskier.

Financial Analysis

financial-accounting
Financial accounting is a subdiscipline within accounting that helps organizations provide reporting related to three critical areas of a business: its assets and liabilities (balance sheet), its revenues and expenses (income statement), and its cash flows (cash flow statement). Together those areas can be used for internal and external purposes.

Post-Mortem Analysis

post-mortem-analysis
Post-mortem analyses review projects from start to finish to determine process improvements and ensure that inefficiencies are not repeated in the future. In the Project Management Book of Knowledge (PMBOK), this process is referred to as “lessons learned”.

Retrospective Analysis

retrospective-analysis
Retrospective analyses are held after a project to determine what worked well and what did not. They are also conducted at the end of an iteration in Agile project management. Agile practitioners call these meetings retrospectives or retros. They are an effective way to check the pulse of a project team, reflect on the work performed to date, and reach a consensus on how to tackle the next sprint cycle.

Root Cause Analysis

root-cause-analysis
In essence, a root cause analysis involves the identification of problem root causes to devise the most effective solutions. Note that the root cause is an underlying factor that sets the problem in motion or causes a particular situation such as non-conformance.

Blindspot Analysis

blindspot-analysis

Break-even Analysis

break-even-analysis
A break-even analysis is commonly used to determine the point at which a new product or service will become profitable. The analysis is a financial calculation that tells the business how many products it must sell to cover its production costs.  A break-even analysis is a small business accounting process that tells the business what it needs to do to break even or recoup its initial investment. 

Decision Analysis

decision-analysis
Stanford University Professor Ronald A. Howard first defined decision analysis as a profession in 1964. Over the ensuing decades, Howard has supervised many doctoral theses on the subject across topics including nuclear waste disposal, investment planning, hurricane seeding, and research strategy. Decision analysis (DA) is a systematic, visual, and quantitative decision-making approach where all aspects of a decision are evaluated before making an optimal choice.

DESTEP Analysis

destep-analysis
A DESTEP analysis is a framework used by businesses to understand their external environment and the issues which may impact them. The DESTEP analysis is an extension of the popular PEST analysis created by Harvard Business School professor Francis J. Aguilar. The DESTEP analysis groups external factors into six categories: demographic, economic, socio-cultural, technological, ecological, and political.

STEEP Analysis

steep-analysis
The STEEP analysis is a tool used to map the external factors that impact an organization. STEEP stands for the five key areas on which the analysis focuses: socio-cultural, technological, economic, environmental/ecological, and political. Usually, the STEEP analysis is complementary or alternative to other methods such as SWOT or PESTEL analyses.

STEEPLE Analysis

steeple-analysis
The STEEPLE analysis is a variation of the STEEP analysis. Where the step analysis comprises socio-cultural, technological, economic, environmental/ecological, and political factors as the base of the analysis. The STEEPLE analysis adds other two factors such as Legal and Ethical.

Activity-Based Management

activity-based-management-abm
Activity-based management (ABM) is a framework for determining the profitability of every aspect of a business. The end goal is to maximize organizational strengths while minimizing or eliminating weaknesses. Activity-based management can be described in the following steps: identification and analysis, evaluation and identification of areas of improvement.

PMESII-PT Analysis

pmesii-pt
PMESII-PT is a tool that helps users organize large amounts of operations information. PMESII-PT is an environmental scanning and monitoring technique, like the SWOT, PESTLE, and QUEST analysis. Developed by the United States Army, used as a way to execute a more complex strategy in foreign countries with a complex and uncertain context to map.

SPACE Analysis

space-analysis
The SPACE (Strategic Position and Action Evaluation) analysis was developed by strategy academics Alan Rowe, Richard Mason, Karl Dickel, Richard Mann, and Robert Mockler. The particular focus of this framework is strategy formation as it relates to the competitive position of an organization. The SPACE analysis is a technique used in strategic management and planning. 

Lotus Diagram

lotus-diagram
A lotus diagram is a creative tool for ideation and brainstorming. The diagram identifies the key concepts from a broad topic for simple analysis or prioritization.

Functional Decomposition

functional-decomposition
Functional decomposition is an analysis method where complex processes are examined by dividing them into their constituent parts. According to the Business Analysis Body of Knowledge (BABOK), functional decomposition “helps manage complexity and reduce uncertainty by breaking down processes, systems, functional areas, or deliverables into their simpler constituent parts and allowing each part to be analyzed independently.”

Multi-Criteria Analysis

multi-criteria-analysis
The multi-criteria analysis provides a systematic approach for ranking adaptation options against multiple decision criteria. These criteria are weighted to reflect their importance relative to other criteria. A multi-criteria analysis (MCA) is a decision-making framework suited to solving problems with many alternative courses of action.

Stakeholder Analysis

stakeholder-analysis
A stakeholder analysis is a process where the participation, interest, and influence level of key project stakeholders is identified. A stakeholder analysis is used to leverage the support of key personnel and purposefully align project teams with wider organizational goals. The analysis can also be used to resolve potential sources of conflict before project commencement.

Strategic Analysis

strategic-analysis
Strategic analysis is a process to understand the organization’s environment and competitive landscape to formulate informed business decisions, to plan for the organizational structure and long-term direction. Strategic planning is also useful to experiment with business model design and assess the fit with the long-term vision of the business.

Related Strategy Concepts: Go-To-Market StrategyMarketing StrategyBusiness ModelsTech Business ModelsJobs-To-Be DoneDesign ThinkingLean Startup CanvasValue ChainValue Proposition CanvasBalanced ScorecardBusiness Model CanvasSWOT AnalysisGrowth HackingBundlingUnbundlingBootstrappingVenture CapitalPorter’s Five ForcesPorter’s Generic StrategiesPorter’s Five ForcesPESTEL AnalysisSWOTPorter’s Diamond ModelAnsoffTechnology Adoption CurveTOWSSOARBalanced ScorecardOKRAgile MethodologyValue PropositionVTDF FrameworkBCG MatrixGE McKinsey MatrixKotter’s 8-Step Change Model.

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