Systems Engineering and Soft Systems Methodology: A Comprehensive Approach

Posted on Jul 19, 2025 in Business Administration and Innovation Management

Jenkins Systems Engineering Methodology

Objectives of Systems Engineering

A system is defined as a complex grouping of people and machines with a defined objective. Systems Engineering is not a new discipline; it’s rooted in industrial engineering practice. However, it emphasizes overall system performance, as opposed to individual component performance. A key feature is the development of quantitative models to optimize system performance.

In Systems Engineering, “Engineering” refers to designing, building, and operating systems. Another feature is its methodology, solving problems across diverse fields like technology and management, emphasizing common characteristics through isomorphisms. Therefore, solving complex problems involves professionals from various fields, not just engineers.

Systems engineering involves planning, designing, building, testing, and operating complex systems. This aligns with the Greek meaning of “system”: put together. Systems Engineering is the science of engineering systems to achieve shared objectives more efficiently. Essentially, it focuses on the optimal use of resources (people, money, machines, and materials).

The importance of systems engineering in solving problems increases with the complexity of organizational challenges. Systems Engineering designs complex systems holistically, ensuring sub-components are designed, assembled, and operated to achieve global objectives efficiently. Many seemingly independent problems and systems require proper assembly for satisfactory solutions.

Beyond providing a methodology for analyzing and solving complex organizational problems, systems engineering structures contributions from diverse disciplines. Its interdisciplinary nature demands specialists (engineers, mathematicians, sociologists, economists, and behavioral scientists). Unlike specialists, the Systems Engineer is a generalist, trained in a comprehensive approach to problem-solving and responsible for overall objectives and efficiency. The systems engineer communicates effectively with specialists, stimulating creativity within this interdisciplinary approach, similar to a guidance and intervention specialist.

The systems group, including specialists and systems engineers, solves problems. The primary mission of the systems engineer is to identify what’s happening, what’s not, and how to improve actions. With specialists, the systems engineer ensures goals are met efficiently, minimizing time and cost, and presenting compelling arguments to decision-makers.

A Systems Engineering Methodology

A Systems Approach to Problem Solving

This section provides guidelines for how a Systems Engineer would approach and solve problems. The steps described represent a breakdown of the following four phases:

Phase 1: Systems Analysis

The Systems Engineer begins by analyzing what is happening, why, and how it can be improved. The system and its objectives are defined to address the identified problem.

Phase 2: System Design

This phase involves predicting the future environment, developing a quantitative system model for simulation, exploring different operating modes to create alternative solutions, and selecting the optimal solution based on assessment.

Phase 3: System Implementation

Results are presented to decision-makers for approval. Detailed system construction requires careful planning. After detailed design, the system is tested to verify performance, reliability, etc.

Phase 4: Operation & Retrospective Appraisal

After implementation, the system is released to operators. Careful planning is needed to avoid misunderstandings. System efficiency is assessed in a dynamic environment, potentially differing from the design environment. If unsatisfactory, Phase 1 is revisited.

1. Systems Analysis
  • 1.1 Identification & Problem Formulation
  • 1.2 Project Organization
  • 1.3 System Definition
  • 1.4 Supra-system Definition
  • 1.5 Supra-system Objective Definition
  • 1.6 System Objective Definition
  • 1.7 System Performance Measure Definition
  • 1.8 Data & Information Collection
2. System Design
  • 2.1 Forecasting
  • 2.2 System Modeling & Simulation
  • 2.3 Optimization of System Operation
  • 2.4 System Operation Control
  • 2.5 System Reliability
3. System Implementation
  • 3.1 System Documentation & Authorization
  • 3.2 System Construction & Installation
4. System Operation & Retrospective Appraisal
  • 4.1 Initial System Operation
  • 4.2 Retrospective Assessment of System Operation
  • 4.3 Improving System Operation Design

Phase 1: Systems Analysis Details

1.1 Identification & Problem Formulation

Systems engineers provide effective solutions to organizational problems. A problem arises when operations deviate from plans or when a decision requires higher-level approval. The systems engineer questions the manager and involved personnel to identify and solve problems.

1.2 Project Organization

After defining the problem’s scope, the approach is identified. Systems engineering is a group activity. An ad-hoc team of specialists from different disciplines and systems engineers is formed. The team handles project development, coordination, problem structuring, modeling, systems analysis, monitoring, and control.

1.3 System Definition

The team precisely defines the system, analyzing subsystems and their interactions. Subsystems are designed and engineered to achieve the overall objective. Systemic maps and block diagrams visually represent the system and its operation.

1.4 Supra-system Definition

Understanding the system’s role within its supra-system is crucial. The systemic map from step 1.3 is extended to show other interacting systems within the supra-system.

1.5 Definition of Supra-system Objectives

The systemic map helps analyze and formulate goals. Since systems are hierarchical, a system’s objectives are inseparable from its supra-system’s objectives. Supra-system objectives are crucial as they determine the operating environment. Changes in supra-system goals likely affect the system.

Defining supra-system objectives offers advantages:

  1. Aligns lower-level systems with higher-level objectives.
  2. Addresses conflicting objectives between systems at the same hierarchical level.
  3. Enables system adaptability to change.
  4. Increases efficiency through greater involvement in achieving supra-system objectives.
1.6 Definition of System Objectives

System objectives are often conflicting. Prioritizing potential objectives is essential. One or a few objectives will prove most important.

Issues in defining objectives:

  1. Resistance to defining clear objectives.
  2. Frustration if objectives are vaguely defined.
1.7 Definition of System Performance Measures

After agreeing on system objectives, a criterion for measuring the system’s efficiency in achieving those objectives is defined. This criterion is often, but not always, economic. Accurate goals facilitate quantitative performance measures; inaccurate goals may require subjective criteria.

A performance measure should be:

  1. Related to system objectives.
  2. Simple and direct.
  3. Measurable.
  4. Agreed upon by those involved in system operation.

Reconciling conflicting objectives in an economic criterion:

  1. Weighing the importance of conflicting objectives holistically (system performance, design cost, operating costs, reliability, capital costs, etc.).
  2. Imposing constraints on variables.
1.8 Data Collection & Information

This final, extensive stage involves collecting data and information for system modeling. Data informs system operation and future environment prediction.

Phase 2: System Design Details

The systems analysis phase concludes with problem identification, objective definition, and information gathering. The system design phase builds upon this foundation.

2.1 Forecasts

Accurate forecasts are essential for system design. For example, demand forecasts are crucial for production control systems and chemical plant design. Inaccurate forecasts cannot be rectified by later modeling and simulation.

2.2 System Modeling & Simulation

Predicting system behavior under different conditions requires a model. Models range from tables and graphs to sophisticated mathematical equations. Model design is iterative and adaptive.

Quantitative models are classified into four types:

  1. Descriptive (qualitative) and predictive (quantitative).
  2. Mechanistic (based on governing mechanisms) and empirical/statistical (data-driven).
  3. Steady-state (time-independent) and dynamic (time-dependent).
  4. Individual (subsystem) and global (whole system).

The working group should:

  1. Ensure the model serves a definite purpose.
  2. Involve all necessary specialists.
  3. Create a simple yet comprehensive model.
  4. Assess model adequacy.
  5. Foster effective dialogue between the workgroup and system users.

The model simulates behavior under various conditions and expected disturbances.

2.3 Optimization of System Operation

After simulation, system operation is optimized. Using the model, the performance measure is calculated for different operating modes. Optimization selects the mode with the most favorable performance. Clearly defined overall system objectives are crucial.

Sub-optimization (optimizing a subsystem independently, potentially worsening overall system performance) must be avoided. The optimization stage should:

  1. Avoid sub-optimization.
  2. Examine sensitive parameters in performance measures.
  3. Carefully consider regions near optimal operating conditions.
  4. Perform sensitivity analysis.
  5. Consider resource allocation for the final design.
2.4 Control System Operation

An optimized system requires a control system to maintain optimal conditions despite unpredictable disturbances. Control systems regulate variables (material flow, fluid levels, pressures, temperatures) to ensure optimal operation. Management control systems ensure production plan compliance.

Considerations for control systems:

  1. Integrate control into system design.
  2. Consider control broadly, not just mathematically sophisticated schemes.
  3. Justify control system costs.
  4. Consider the control system’s place in the hierarchy of control systems.
2.5 System Reliability

System reliability is crucial. A good control system enhances reliability, but other factors (uncertainty in environmental forecasts, equipment failure, resource unavailability) must be considered. The methodology addresses factors often ignored in design but impacting operation and cost efficiency.

Phase 3: System Implementation Details

A well-designed system is useless without proper implementation. This phase has two stages.

3.1 System Documentation & Authorization

The project’s end product is a report with concrete action proposals. Effective communication is crucial. Recommendations:

  1. Agree on report format and content with those involved in implementation.
  2. Reports should be simple, straightforward, and logical.
  3. Develop a separate summary highlighting recommendations and an implementation plan.

This stage is crucial for decision-making on system implementation. The team must convincingly support the proposal.

3.2 System Construction & Installation

Some projects require constructing special equipment. For example, a chemical plant project requires building process equipment, buildings, ordering, and installing equipment.

A systems approach ensures:

  1. Clear and unambiguous system details.
  2. System builders understand design and operation.
  3. Proper planning for construction, installation, and implementation.

Phase 4: System Operation & Retrospective Appraisal Details

After design, construction, and installation, the following steps are taken.

4.1 Initial System Operation

Collaboration between users and designers is essential. Successful implementation involves:

  1. Providing documentation and training.
  2. Involving a user in the project.
  3. Clarifying any doubts or misunderstandings.
4.2 Retrospective Assessment of System Operation

After a period of operation, the design team and users perform a retrospective analysis. If the system operates as planned and achieves objectives, the design is considered successful. Otherwise, causes of malfunctions are investigated for improvement or redesign.

Retrospective analysis may reveal:

  1. Important aspects ignored in the original study.
  2. Operation in an environment different from the design environment.

Re-optimization and redesign may be necessary.

4.3 Improving the System Operation Design

System operation improvement is needed if:

  1. Performance is below expectations.
  2. Parameters were unknown during design and optimization.

Soft Systems Methodology (SSM)

Purpose of SSM: SSM supports and structures thinking and intervention in complex organizational problems.

SSM Thought Process: SSM guides the process of organized action, managing and implementing action in response to changes affecting that action. SSM acknowledges differing individual worldviews, leading to varied understandings and assessments of situations and actions. Checkland noted that logical correctness alone rarely provokes action.

Organizations have complex and dynamic cultures and political structures. Differing views lead to unclear objectives. SSM aims for consensual action, fostering understanding through thinking, negotiation, argument, and evidence.

1. Introduction to Soft Systems Methodology

West Churchman and Russell Ackoff pioneered social systems science. Churchman developed a philosophical base for methodological principles, inspiring critical systems heuristics. Ackoff’s practical work with INTERACT emphasized subjective assessments in complex problems.

Emerging in the 1970s, Soft Systems Methodology (SSM), inspired by Churchman, was developed by Peter Checkland. It applies systems engineering to less-defined managerial problems, addressing situations where the problem itself is unclear. SSM prevents premature, poorly reasoned solutions based on preconceived ideas.

SSM is redundant where there’s agreement on what to do, but not how. In coercive contexts, mutual understanding is impossible, hindering SSM’s effectiveness. SSM thrives in pluralistic contexts with compatible interests and values, where beliefs diverge but commitment and involvement are possible. SSM addresses complex, pluralistic issues of process and organizational structure.

2. Emergence of SSM

Gwilym Jenkins broadly interpreted “Engineering.” He initially focused on systems engineering (engineering well-defined systems), but collaborated with Checkland to apply the methodology to less-defined problems. Action research, involving real-world problem situations and reflection, was employed.

3. Philosophy of SSM

Churchman’s emphasis on subjectivity suggests that maximum participation guarantees intervention results. A systems approach involves recognizing the limitations of individual worldviews. Churchman’s work focused on ethical considerations for future generations. SSM explores the subjectivity of perceptions in problem situations, generating learning.

Werner Ulrich also focused on Churchman’s ethical line of thought, developing an approach suitable for contexts with political forces. Checkland’s findings include:

  • Hard systems approaches are based on means and ends.
  • The concept of “system” organizes thoughts on problem situations, not reality.
  • Two paradigms exist: hard and soft, with contrasting assumptions and methodological principles.

SSM breaks with the hard systems view of problems as real and solvable with objectively definable ends. SSM acknowledges contrasting views in problem situations, accepting multiple significant problems. SSM rejects the means-ends approach, focusing on “what should be done?” and exploring diverse views in decision-making.

Checkland observed that “system” is used to organize abstract thought, not describe reality. Interpretive thinkers like Checkland understand social situations through concepts of action (words describing action), social rules and practices, and essential meaning (reasons for actions). Social dynamics are explained as interplay between human interpretations, forming cultures with shared rules, practices, and purposes. Performances are open to change. Mutual understanding is possible, a key principle of SSM.

Checkland’s findings on means-ends and systems led to the identification of two paradigms: the hard paradigm (real world as systems, methodologies as systematic) and the soft paradigm (real world as problematic, methodologies as systemic). This shifts systematization from the world to the research process. SSM rejects assumptions of hard, machine, organic, and neuro-cybernetic views of social reality, favoring a soft, cultural viewpoint.

4. SSM Principles

Four major principles guide SSM use: learning, culture, participation, and two modes of thought.

SSM is a learning system using purposeful action in a continuous cycle. Learning involves perception and evaluation before action, creating a continuous cycle. Progress is determined by importance, cultural feasibility, and systemic desirability. Cultural feasibility is a key SSM element, considering social and organizational constraints and potential changes.

Participation is crucial; without it, SSM applications are invalid. The variety of perceptions necessitates participation for successful, justifiable, and implementable results.

SSM uses two modes of thought: abstract/ideal systems and real-world contexts. One stream is logic-based; the other is culture-based. These should remain distinct while developing models for discussion. Experienced users move between these modes while remaining aware of the shifts.

5. Soft Systems Methodology in Practice

Basic Shape of the SSM

Humans attribute meaning to observations and experiences. Purposeful activity (A) is an expression of intention (B) by someone (C), affecting someone (D) within a restrictive environment (E), potentially stopped by someone (F). This simple model represents purposeful action.

SSM develops relevant models for real-world situations, comparing them to real-world insights. This comparison initiates discussion, leading to action to improve the situation. SSM models are human activity systems, more elaborate than the simple model but based on the same principle.

Problems are either structured (formulated in a language involving a solution theory) or unstructured (manifested as anxiety, not easily formulated).

Global Process Overview

The SSM is a 7-stage process (Checkland, 1975).

Flow-Based Inquiry Logic

Users familiar with the situation may directly enter the logic-based thought flow.

Stages 1 & 2: Expression

These stages reveal possible and relevant selections. Structure (physical distribution, power hierarchy, communication patterns) and process (core activities, decision-making, monitoring, corrective action) are established.

Stages 3 & 4: Root Definitions & Conceptual Models

Appropriate System Selection: An appropriate system is a human activity system considered for discernment. Root definitions and conceptual models are created for each relevant system. System relevance is subjective; choices are made, and their logical implications are explored.

Two types of choices:

  1. Main Task Relevant Systems: Organized purposeful action in the real world, potentially coinciding with a notional human activity system.
  2. Relevant Systems Based on Controversy: Debates about core purposes and resource allocation. Institutionalized versions may not exist.

Relevant System Appointment: Root definitions express the core purpose of a purposeful activity system as a transformation process (input transformed into output).

Relevant System Modeling: Modeling uses verbs, structuring activities necessary for the transformation process (CA2E). The goal is to express main operations in a limited number of activities (around 7 ± 2).

Transformation success is assessed at three levels:

  1. Effectiveness: Do the means generate the output?
  2. Efficiency: Are minimal resources used?
  3. Long-term Goal Achievement: Does the transformation achieve the ultimate goal?

Complex models enrich debate but can lead to focusing on model parts rather than the real world. Models are not valid or invalid but sustainable or unsustainable, depending on whether every aspect derives from the root definition.

Model Comparison with Perceived Reality: Comparison methods include informal discussion, formal questioning, scenario writing based on model operation, and modeling the real world using the same structure as conceptual models. Questioning is common; models are used to generate questions about the real world, and responses initiate debate.

The Flow of Cultural Inquiry

Although the facts and logic are part of human affairs, their felt texture derives equally (or more) from the myths and meanings that people attach to their professional (and personal) entanglements with their peers.

Enriched Images
A characteristic of fluid SSM users is that they will see them throughout the work drawing pictures and diagrams, as well as making notes and writing prose. The reason is that humans reveal a rich exposure in the movement of relationships, and images are a more effective means for recording relationships and connections than prose.

The representation of root definitions plastically is an example of the use of images in SSM, but the best-known example is the politics of representing the same problem situation in the form of so-called detailed images. There is no formal technical or classic form for this, and in no way is drawing an essential skill for the generation of images, which has been very useful.

Intervention Analysis
The methodology was maintained to help make sense of difficult problems, which contain their own internal contradictions.

Many projects have failed as a direct result of their failure to take into account the several perspectives, motives, and interests at stake in human organizations.

SSM contains a structure which was designed to deal with these difficulties.

What is an intervention in SSM?

In SSM, the organized structure of intervention is used to deal with the complexity of an organizational problem.

While SSM has a clear structure, it is suitable for practitioner use in a flexible and intelligent manner.

SSM intervention involves:

  • Finding out about the situation;
  • Thinking about systems that are or may be employed in the situation;
  • Comparing the thinking of those systems that exist in the real world;
  • Taking action according to what has been learned.

There is a simple matter of performing these four steps, after which a correct answer occurs.

Rather, it seeks to take these four steps as bases for action, where each of these should be kept in mind.

Early in the development of SSM, it was found to be useful to conceive of an intervention in a situation as problematic in itself. It was observed that it was very useful to conceive of intervention generating structurally three roles. The role of the customer is the person or people who cause the survey to be carried out. There will always be a response to the real-world question: who is in the client role?

In the role of the candidate problem solver who will want to do something about the situation in question, it would be better if the intervention is defined in terms of perceptions, knowledge, and readiness to make available the resources of the publisher(s) addressing the role of the problem owner. No one is inherently the problem owner. The problem solver must decide whom to consider as potential holders of the problem. The analysis carried out in this part is Analysis 1.

The Social System Analysis
The images will be further enriched by drawing and editing throughout the use of SSM, and the new occupants of the roles of problem solver and problem holder may emerge. A problem in the analysis may emerge in the course of the study, so there is no definitive analysis. Nor is there a study of the problem situation considered as a social system, using that phrase with its sense of everyday language. The social science literature does not generate an easily usable model, and there has been the need to develop an experimental model for use in the analysis of SSM DOS.

The model in question assumes that what constitutes a social system continuously changes between three elements: roles, norms, and values. The purpose is to understand the social position that people in the situation identified as a significant problem. A role is characterized by the expected behavior in it, rules. Finally, the true performance of a role will be judged according to local standards or values. These are beliefs about what is humanly good or poor performance by the holders of the role. Figure 7 shows the model of this phase.

The Political System Analysis
Three analyses on the flow of cultural analysis agree that any human situation will have a political dimension, and you need to explore it. As in the case of Analyses 1 and 2, this is done via a general model, in this case, a political system. For practical purposes, the three analyses will assume that politics is a process by which different interests are accommodated, a view that could be supported with reference to the literature of political science.

Responding to questions directed to power in the three analyses enriches the assessment culturally constructed in Analyses 1 and 2. The three analyses complement the work of selection, appointment, and modeling of relevant human activity systems that is carried out simultaneously in the flow of thought based on logic.

Making Desirable & Achievable Changes
Whether SSM is used by an individual to help them deal with their daily work, or if this is the methodology adopted in a prominent study, the objective of SSM is to do something about the situation considered somewhat unsatisfactory. The two streams of thought and action in SSM converge in a structured discussion held on the changes that would help dissatisfaction disappear. But beyond the definition of change, the user of SSM is responsible for implementing them.

This implementation is in itself, of course, a situation not uncommonly addressed by SSM. We could conceptualize and implement model systems for changes, and do that according to some relevant Weltanschauungen. Finally, we could pinpoint a system for the activities whose changes can then become real-world action. We can say if we do the activities of the final model in the real-world situation.

The changes themselves are usually described as systemically desirable and culturally viable, and it’s worth delving briefly into these statements because if we see them, we understand SSM.

The system models with purposeful human activity that are built into SSM are selected hoping they are relevant to the problem situation. They are not intended to be models of the situation. It is because of this reason that changes from the debate initiated by comparing the models with the real situation are (only) arguably desirable, not forced. The changes are systemically desirable if it is perceived that they are pertinent in these systems and relevant factual truth.

The implementation of the changes is carried out within a human culture, and it amends the culture, at least in the short term and possibly to a large extent. But the changes will be implemented only if they are received as significant within the culture and within the worldview of that culture.