Summary
The ongoing challenge of deploying supply chain management (SCM) technology to generate better decisions as a path to better outcomes is as Peter Lyon observed in the 1990s a journey that in 2020 is referred to as the digital transformation journey. The purpose of a vision in this journey (for example digital supply chain twin) is to create a focus on the implementation of decision technology as tools to overcome inherent organizational cognitive limitations of bounded rationality and uncertainty bias to improve SCM – especially a tighter coupling across the decision grid. Conceptually no different from the use of tools to improve farm productivity. Success in implementing decision technology requires work in the trenches to nudge the organization from one comfort zone to a new one. This results in an adjustment in the social order, where agents of change (AGC) are critical for success. One of their key tasks is to reduce confusion. This blog provides some critical lessons to protect a firm’s investment in technology.
Introduction
Each year “trend watching organizations” identify and promote a “new vision” for best in class supply chain management. A few years ago, artificial intelligence was the dominant topic. Recently the term “digital supply chain twin/transformation” has been a dominant theme. One of the themes for 2021 is “self-healing” supply chains associated with decision levels. This last “vision” appeared to be a replay of the Kempf-Sullivan decision tiers from the 1980s and Dr. Harpal Singh’s (Arkieva CEO) emphasis on the importance of replanning. My initial reaction was ‘nothing new’, then I decided I should sketch out a few lessons for success in the ongoing challenge to leverage technology to improve organizational performance – making the investment.
- Why is there a “new, but not new,” vision each year?
- The need for a vision as a goal serves as a counterweight to organizational cognitive limitations and bias that results in fractured or loosely coupled decisions.
- Understanding the organization
- is a cognitive entity of loosely coupled decisions that happens to generate products and/or services for consumption!
- these decisions, although in a network, are best viewed in a decision grid.
- Successful technology implementation requires work in the trenches.
- The importance of agents of change (AGC) in implementing technology that upsets the social order.
- All of the data required can only be identified once the implementation is started.
- Dormant periods between surges in technical success is not unusual.
This blog will briefly describe each of these and their role in the ongoing challenge.
Organizational Cognitive Limitations
Understanding a few basics of organizational and human cognitive limitations is critical to understand the ongoing challenge and the need for a “yearly vision”. Much of the critical work in this area was done from the late 1950s to the early 1970s.
Herbert Simon in Administrative Behavior (1957) observes, “As humans, we have ‘bounded rationality’ and break complex systems into small manageable pieces.” In 1974 Tversky and Kahneman in Judgment under Uncertainty: Heuristics and Biases added bias to limits on rationality. To adjust for these limits, Galbraith in Designing Complex Organizations (1973) suggests the use of “slack” (for example excess inventory) to reduce information load in managing interconnected operations in the absence of information and decision support (in 2020 terms technology).
The challenge for any extended organization is to integrate information and decision technology (analytics) into an effective “decision calculus” (Little, Models, and Managers: The Concept of a Decision Calculus, 1970) in a decision support system (Keen, Interactive Computer Systems for Managers – A Modest Proposal 1976) to extend the boundaries of rationality and limit bias to improve the responsiveness (reduce slack) of the entire demand-supply network (DSN). The challenge comes in two components: initial success and sustained success.
The Organization as a Cognitive Entity
Most organizations, from health care facilities to manufacturing giants to restaurants, can be viewed as an ongoing sequence of loosely coupled decisions linked in a complex network where current and future assets are matched with current and future demand across the demand-supply network at different levels of granularity ranging from placing a lot on a tool to an aggregate capacity plan across a five-year horizon. Often the Arkieva decision grid works well to keep track of players in the game.
Work in the Trenches – Agents of Change – New Social Order – Stamping Out Confusion
The vision is of no value if the technology cannot be successfully implemented, where success is defined as being an integral part of the day to day management process such that no one can imagine life without these new functions. Who best to work the trenches – a small team of Agents of Change (AGC). This team will have a large collection of technical skills: programming algorithms and database extracts, data science of extracting insights from flawed data, deciding on the right combination of methods or creating new ones, etc.
The distinguishing skill for an AGC team is the nuances of nudging an organization out of its current comfort zone to a new social order. The key is to stamp out the confusion. A successful AGC must learn to spot a confused look on a client’s face—though it might show for only a moment—to explain away the confusion or open a conversation. Key users need to understand the basic logic generating the results (though they may not comprehend all technical details and from time to time will ask for explanations of solution results). Over time, they grow to appreciate the model’s ability to tackle complexity and develop confidence. This reduces confusion.
However, left unprotected AGC teams will be eradicated. Such teams have no “regular” home. . This happens easily—despite the mantra of “competing on analytics” —especially since the impact is often delayed as the organization survives on past efforts with manual workarounds and/or economic circumstances temporarily cover the limitations in responsiveness. Regardless of the delay, the challenge remains.
Work in the Trenches – Sporadic
A key question is why are successful applications of analytics to overcome organizational cognitive limits sporadic and not sustained? One can find parallels with the American frontier at the eastern boundary of the Great Plains from 1820 to 1875 (Gwynne, 2011) — forward progress is sporadic—bursts forward are followed by reversals, forts built in isolation, and lessons lost. Perhaps the best example is the revolver: used with success, abandoned, and then rediscovered.
Conclusion
As noted by Kempf in his 2015 SIAM presentation, “Over the past 200 years our view of human rationality has moved from perfect (Adam Smith) to bounded (Herbert Simon, Nobel Laureate 1978) to biased (Daniel Kahneman, Nobel Laureate 2002). Unfortunately, the Laureates left many practical questions unanswered – including how to make better decisions. The starting point is the effective use of tools from databases to algorithms to overcome cognitive limitations. The purpose of a vision is to create a focus on the implementation of decision technology as tools to overcome inherent organizational cognitive limitations to improve supply chain management decisions – especially a tighter coupling across the decision grid. Success in implementing decision technology requires nudging the organization from one comfort zone to a new one. This results in an adjustment in the social order, where agents of change (AGC) are critical for success. One of their key tasks is to reduce confusion. Their second task is survival. “There is no more delicate matter to take in hand, nor more dangerous to conduct, nor more doubtful of success, than to step up as a leader in the introduction of changes. For he who innovates will have for his enemies all those who are well off under the existing order of things and only lukewarm support in those who might be better off under the new. (Machiavelli)”. The 2015 paper by Horst Zisgen and John Milne has a detailed description of the work by agents of change.
