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Emergence is a phenomenon where complex patterns, behaviors, or properties arise from the interactions among simpler entities, without these characteristics being present or directly predictable from the individual entities themselves. This process results in novel outcomes that are more than the sum of the system's parts, often observed in complex adaptive systems across various fields.

Throughout my career, I have seen databases grow from tens of thousands of records to hundreds of billions of records. With each order-of-magnitude increase in size new insights emerge.

What makes emergent abilities intriguing is two-fold:

  1. Sharpness of Transition - the seemingly instantaneous switch from boring to deep insights. From mundane operational reports to high-impact decision support.

  2. Their Unpredictably - the rate of enterprise knowledge graph insights is unpredictable, appearing at seemingly unforeseeable as knowledge graph models scale. Getting accountants to place a value on future insights is a challenge.

Within the framework of systems thinking and complex adaptive systems, emergence refers to the phenomenon where larger entities, patterns, and behaviors arise through interactions among smaller or simpler entities that themselves do not exhibit such properties. This concept is central to understanding how complex systems evolve and adapt over time, often in unpredictable ways. The interactions among the system's components can lead to the emergence of new properties and behaviors that are not inherent in the individual components but are a result of their collective interplay.

In the context of building centralized enterprise knowledge graphs, emergence plays a crucial role in shaping strategic thinking for several reasons:

  1. Understanding Complexity and Interconnectivity: Enterprise knowledge graphs aim to represent and store complex information in an interconnected, accessible manner. Recognizing the emergent properties of the system can help in understanding how different pieces of information relate to each other and influence the whole system. This understanding is critical for accurately mapping relationships and dependencies within the knowledge graph.

  2. Adaptability and Evolution: As enterprises evolve, so do their knowledge needs and the structure of their knowledge graphs. Emergent properties highlight the need for these graphs to be adaptable and capable of evolving. This adaptability is essential for incorporating new information, relationships, and patterns that arise as the organization grows and changes. Strategic thinking, in this case, involves planning for flexibility and scalability from the outset.

  3. Innovation and Discovery: The concept of emergence encourages a strategic approach that is open to innovation and discovery. As new patterns and insights emerge from the data and relationships encoded in the knowledge graph, organizations can identify unforeseen opportunities or challenges. This can lead to innovative approaches to problem-solving and decision-making, based on insights that were not apparent without the holistic view provided by the knowledge graph.

  4. Decision-making and Strategy: Emergent properties can significantly impact decision-making and strategic planning. By understanding and anticipating how certain inputs or changes might affect the larger system, leaders can make more informed decisions. For instance, recognizing potential emergent behaviors might influence the design of the knowledge graph, such as incorporating mechanisms for real-time updates or feedback loops to capture dynamic changes.

  5. Risk Management: Identifying and understanding emergent properties can also help in risk management. By analyzing how different elements of the knowledge graph interact, organizations can anticipate potential issues or bottlenecks and develop strategies to mitigate these risks before they escalate.


The bottom line is that systems thinking can be difficult for newcomers. They often don't see the light at the end of the tunnel when they are knee-deep in building their first integrated views of a customer and untangling the web of entity resolution.

However, the concept of emergence in systems thinking and complex adaptive systems underscores the importance of considering the non-linear, dynamic interrelations within an enterprise knowledge graph. Strategic thinking, in this context, involves planning for adaptability, embracing innovation, informed decision-making, and proactive risk management, all aimed at leveraging the emergent properties of the system to achieve organizational goals.