4 more systems thinking techniques to advance your digital transformation

Learn how agent-based modeling, network analysis, scenario planning and systems dynamics modeling can help you reimagine your outdated business processes.

Digital transformation fails when it simply automates manual or partially automated processes. Some call that approach paving the cow paths.

Digital transformation succeeds when business processes are redesigned to benefit from digital technology. Redesigning processes is best performed using the systems thinking method, a holistic approach that reveals problems, bottlenecks and inefficiencies.

There are many systems thinking techniques that can help you plan your digital transformation initiatives, such as causal loop diagrams, RACI tables, process maps and the iceberg framework. Here are four more systems thinking techniques every engineer should know about.

Agent-based modeling (ABM)

Agent-based modeling (ABM) creates a visual representation of a complex system that models autonomous agents interacting with each other during the modeled process. Agents are individuals, contractors or suppliers.

The engineering applications of ABMs include manufacturing situations where the interacting variables are poorly understood, leading to unacceptable product quality variation. Examples include digital chips, high-value glass and steel, carbon fiber and nanoparticles.

Example of an agent-based model. (Image: AnyLogic.)

Example of an agent-based model. (Image: AnyLogic.)

Key benefits of ABM for digital transformation include:

  • Stakeholders like how simple it is to describe individual interactions
  • Realistic model behaviors enable better insights into process dynamics
  • Engineers can explore various scenarios and actions by simulating different process outcomes
  • ABMs can handle complex, nonlinear interactions among agents to reveal how small changes at the agent level can lead to significant shifts at the process level

Various software packages support ABM. The ones that are more general purpose with GIS and 3D capabilities include AgentScript, AnyLogic and MASON.

Network analysis

Network analysis illustrates relationships between nodes and the ties between nodes. Typical nodes are individuals, processes or resources, such as equipment or facilities. Ties or edges describe the type of relationship and the data exchanged between two nodes.

Network diagrams and program evaluation and review technique (PERT) charts are used for network analysis and planning larger and more complex projects. Data modeling tools that support graph databases are also used to capture network analysis work.

Example of a PERT chart. (Image: Lucidchart.)

Example of a PERT chart. (Image: Lucidchart.)

The value of network analysis for digital transformation is that it:

  • Offers the ability to examine quantitative network properties
  • Reveals how different steps or components influence each other and contribute to the overall behavior of the process

The engineering applications of network analysis include manufacturing complex products such as:

  • Electrical and electronic components
  • Diesel-electric locomotives
  • Supercomputers
  • Rockets, satellites and vehicles for space flight

Various software packages support network analysis. Examples include Adobe Express, Lucidchart, Miro, Visme and Visual Paradigm Online.

Scenario planning

Scenario planning analyzes many possible future events and alternative possible outcomes. Creating a scenario often uses political, economic, sociological, technological, environmental and legal (PESTEL) and strengths, weaknesses, opportunities and threats (SWOT) analysis for quantitative projections and qualitative judgments about the many time series variables interacting to determine alternative outcomes.

Example of a scenario planning dashboard. (Image: Anaplan.)

Example of a scenario planning dashboard. (Image: Anaplan.)

The value of scenario planning for digital transformation lies in the following:

  • Learning about the business process through the planning process itself
  • Identifying and revising implausible assumptions in the scenarios
  • Identifying and correcting missing variables and errors in the relationships among variables

The engineering applications of scenario planning include digital construction planning for major projects such as roads, bridges or skyscrapers. The technique is also applied to enterprise and macroeconomic modeling.

Scenario planning software packages are often included with financial planning and analysis software. Software packages for scenario planning include Adaptive Insights, Anaplan, Cube, Jirav, Mosaic and Planful.

Systems dynamics modeling

Systems dynamics modeling seeks to understand the behavior of complex systems over time. Many variables, nonlinear relationships among variables and multiple components characterize complex systems. The modeling:

  • Focuses on the concepts of stocks and flows, time delays and internal causality or feedback loops
  • Supports complex equations
  • Addresses the problem of multiple variables interacting simultaneously by changing variable values over small periods of time
  • Supports various interactions among subcomponents

Stocks are entities that can accumulate or be depleted such as parts inventories. Flows are entities that make stocks increase or decrease such as purchasing, manufacturing or sales.

Example of a stocks and flows diagram. (Image: Vensim.)

Example of a stocks and flows diagram. (Image: Vensim.)

Systems dynamics modeling provides value for digital transformation by:

  • Enabling insights into the structure and behavior of complex systems and processes
  • Revealing how processes are affected by changes in various factors or variables

Engineering applications of systems dynamics modeling include digital simulation of complex products such as turbines, aircraft assembly and petrochemical plants.

Software packages for systems dynamics modeling include ExtendSim, Powersim Studio, Insight Maker, iThink, Simcenter, Stella Architect and Vensim.

The value of diagrams for systems thinking

Most systems thinking techniques produce highly visual deliverables, often diagrams, as they illustrate the work for review and stakeholder communication better than text.

Often, engineers employ more than one systems thinking technique. The challenge is to select the best techniques for the situation. If the technique is too simple, the value is limited. The team bogs down if the technique is too complicated. Overwhelming stakeholders with complex techniques risks not completing the analysis.

Specific systems thinking techniques are not linked to particular diagram types. Teams will gravitate to preferred diagram types based on experience and relevance to process characteristics. The more frequently used diagram types include:

  • Bill of materials – A hierarchical list of the raw materials, parts, components, sub-assemblies and related quantities needed to manufacture an end product or deliver a service
  • Cause and effect diagram – A “fishbone” diagram used to explore and display the possible causes of a particular effect or observation
  • Conceptual model – A diagram of the logical activities required to achieve a system purpose
  • Context diagram – A high-level diagram of a system that defines the boundary of the system of interest and its environment
  • Influence diagram – A diagram that illustrates significant relationships or influences that exist between the elements of a system
  • Input-Output diagram – A high-level representation of the inputs and outputs of a system
  • Functional model, process model or sequence diagram – A diagram that illustrates system functionality through its processes and their logical interconnections
  • Systems map – A high-level diagram of the situation under investigation showing the system boundary and its major components

Selecting the best diagrams to describe the planned digital transformation work depends on the characteristics of the business processes and the analytical maturity of the stakeholders involved in the analysis. It’s common to begin with a high-level conceptual diagram and then develop more detailed, structured diagrams.

Systems thinking diagrams assist engineers with a wide range of engineering tasks, including root cause analysis, conceptual prototyping and process improvement.

Diagramming software ranges from simple electronic whiteboards or sketching software that captures unstructured graphics to more structured modeling software. Software packages for diagramming include Fresco, Illustrator, Paint, Sketch and Visio.

Example of a functional model, process model or sequence diagram. (Image: Burge Hughes Walsh.)

Example of a functional model, process model or sequence diagram. (Image: Burge Hughes Walsh.)

Best practices for performing systems thinking

Apply the systems thinking method to your digital transformation work by following these steps:

  • Introduce a current process problem with a story
  • List the actors involved in the current process
  • Draw the actor names and show their interactions as arrows using the most appropriate systems thinking techniques
  • Explore the issues in the current process in more detail
  • Craft a digital transformation opportunity statement
  • Identify and diagram or simulate potential digital transformation solutions using the most appropriate diagram(s)
  • Select the optimum digital transformation solution
  • Plan to implement the digital transformation solution
  • Perform the implementation
  • Evaluate the performance of the digital transformation solution

While these steps look linear, the systems thinking method is more iterative in practice. Expect to cycle through these steps or a subset of them multiple times.

Systems thinking techniques and related diagram deliverables advance your digital transformation by better understanding current process problems and crafting comprehensive solutions that improve processes with digital systems.

Yogi Schulz has over 40 years of Information Technology experience in various industries. He also writes for ITWorldCanada and other trade publications. Yogi works extensively in the petroleum industry to select and implement financial, production revenue accounting, land & contracts, and geotechnical systems. He manages projects that arise from changes in business requirements, from the need to leverage technology opportunities and from mergers. His specialties include IT strategy, web strategy, and systems project management.

Written by

Yogi Schulz

Yogi Schulz has over 40 years of Information Technology experience in various industries. He writes for ITWorldCanada and other trade publications. Yogi works extensively in the petroleum industry to select and implement financial, production revenue accounting, land & contracts, and geotechnical systems. He manages projects that arise from changes in business requirements, from the need to leverage technology opportunities and from mergers. His specialties include IT strategy, web strategy, and systems project management.