What is business “truth”?
The subjects I read, debated, and synthesized during my PhD research still fascinate me. The concept of value remains intriguing and challenging; it cuts across academic disciplines and business functions. Epistemology was another engrossing subject. Epistemology is the philosophical analysis of the nature of knowledge, justification and belief. As a PhD researcher seeking to increase our understanding of (business) management – a social science — I had to answer several epistemic questions concerning scientific research.
What is “truth”? Can we actually know “truth”? How do we know “truth” scientifically (i.e. how do we come to “believe” something)? Can our knowledge ever be proven? If so, how do we best prove it (i.e. how do we justify our beliefs)? How much proof is needed (i.e. how do we convince the skeptic)?
By answering these epistemic questions, I could determine “how” best to conduct my research. Logic and methodology address these “how to” matters. Logic describes the correct (reasoning) needed to justify “truth”. Methodology describes the proper and relevant processes used to conduct research into “the truth”.
Emerging value-based management using systems thinking
Most management thinking is based on Cartesian logic — it is linear. This is reflected in the hierarchical / vertical organization charts originating in the late 1800s. The industrial revolution increased the modularization / specialization of work activities. Those activities were assigned to functional groups / departments whose managers could issue top-down “command and control” orders. Business academics then proposed and executives adopted a single objective function — maximizing shareholder value – for the firm.
Today’s dynamic, matrix-based, adaptive and market-driven organizations are very different, requiring a new management approach. Executives are now exhorted to coordinate intra- / inter-firm value activities for multiple stakeholders while simultaneously maintaining profitability. To do so amidst the disruption occurring in the global and technology-enabled value chains of the 21st century executives will need a “new way of thinking.”
Brain as metaphor / Cognitive neuroscience research
Recent advances in cognitive neuroscience and bio-psychology provide useful constructs for confused professionals. Cognitive neuroscience studies our bio-chemical-electrical mental processes at three different levels. It studies the brain as a single physical entity, as a combination of physically distinct regions (each with its own specialized activity / function), and as a web of discrete synaptic pathways. These three levels are also viewed through several disciplinary lenses: biology, chemistry, neurology, and psychology. As brain science evolves, our knowledge of the brain advances. In turn, new scientific discoveries support / refute previous cognitive theories and models. Understanding how the brain ‘knows’ / ‘learns’ / ‘thinks’ becomes more comprehensive, mandating scientists to synthesize / integrate the theories of many academic disciplines. Cognitive models grow more integrative.
Brain science provides a useful metaphor for business. Consider “collective intelligence” – what does a company “know”? To answer that question, one needs to study the system / network (e.g. the company), the interactions between groups in the company (e.g. its functions or departments), and the discrete activities of each of its members (e.g. the individual employees). Or consider value management – how does value flow across the value stream? One must again examine the system / network (e.g. the value chain), the interactions between groups across the chain (e.g. the participating companies), and the discrete activities of each of its participants (e.g. the function or department within each company)
A complex web of cognitive inter-relations / inter-dependencies exists in both the brain and the company / its value chain. Fortunately the fields of systems-thinking and complexity theory provide useful tools to analyze both. They provide non-linear and holistic ways to “think about thinking” on all three levels.
Systems thinking and complexity science / Non-linear and dynamic approach
Brian Castellani (2018) mapped the evolution of complexity science in the illustration above (go to link for higher resolution image). Systems thinking preceded complexity science. There are two types of systems. A household thermostat is a good example of the first – a “hard system”. The thermostat is a “closed loop” – it monitors the temperature and turns heating / cooling on / off to adjust ambient temperature to a pre-set level. In contrast, a Standard Operating Procedures (SOP) manual may be either “hard” or “soft” depending upon whether procedures / responses change with new circumstances. “Soft systems” employ “open loop” thinking whereby the underlying assumptions / rules might be rethought and more relevant / appropriate responses instituted. Imagine an SOP manual published on Wikipedia where employees edit / update the contents to reflect new working conditions or situations.
Complexity theory / science proceeds even further – imagine a Wikipedia-based manual “on steroids” that reflects the combined thinking of many individuals on adapting SOPs for existing or new business conditions. Unsurprisingly, complexity science often examines dynamic, adaptive, and chaotic systems. These systems have more “moving parts” with more influencers. Oftentimes, the “solution” emerges by observing the pattern of collective behavior over time. Such outcomes are generally not observable a priori.
Value (management) / Integrating the four intelligences
How do we know what we know in business? In Integrated Value Management: “Mind the flow!” I asserted that knowledge is the product of four types of “smarts”: conceptual / theoretical intelligence, encoded intelligence, experiential intelligence, and socio-emotional intelligence. To truly understand business value, I developed the Integrated Value Process (IVP) framework in An Empirical Framework for Evaluating, Implementing and Managing a Value-based Supply Chain Strategy (my PhD thesis accepted by the University of Bath School of Management — ProQuest publication number 3121355). IVP incorporates the four types of intelligence. It consists of (1) a conceptual framework illustrating the intra- / inter-firm value management process, (2) a methodology to ‘decode’ the ‘value gaps’ occurring in the value chain, (3) five value ‘first principles’ underlying value chain activities, and (4) a ‘meta’ definition of value to communicate effectively across functions within the firm and with the firm’s customers / suppliers.
Cognitive neuroscience has helped us better understand the brain by providing a system-based “way of thinking”. A similar way of thinking is needed for integrated value management . The Integrated Value Process (IVP) provides such a framework to manage value holistically across value chains in order to maintain competitive advantage and let value flow.
Andrew Swan, PhD is a multidisciplinary and cross-functional integrator of strategy, processes, and information technology. His focus and expertise center on helping executives increase value creation and optimize value flows in business. Dr. Swan holds four degrees in Management, Accounting & Finance, Information & Knowledge Strategy, and Computer Science from the University of Chicago Booth School of Business, the University of Bath School of Management, and Columbia University.
He frequently publishes articles on value chains, value streams / flows, and Integrative Value Management on his website www.andrewjswan.com. Dr. Swan created the Integrated Value Process (IVP) Framework to help companies optimize the flow of goods & services, funds, and information across their respective value chains for multiple stakeholders. He can be reached at firstname.lastname@example.org or at +1.773.633.7186. He lives in Chicago.