For the record: my current work

Well just an "extended abstract" of it ... Later posts will elucidate (I hope)

Symbiosis as an Alternative View for Identifying Strategic Positioning Potential for the Enterprise

Enterprises do not operate in a vacuum. Their connection to a value stream beyond their boundaries is largely recognized but when it comes to guiding enterprise strategy, the prevalent perspective is adversarial. For industries that are prone to cyclical behavior, this handicaps the potential of implementing strategies that can lead to dampening of the cycles. We suggest that in the strategy design phase of Enterprise Transformation the decision-makers can consider what we call symbiotic strategies, actions that may provide long-term stabilizing effects and therefore long-term strategic advantage even in the face of tactical disadvantages.

The Enterprise of Enterprises (EoE) framework aided by a hybrid of agent-based and system dynamic models permits us explore a set of strategies with the potential to lead to symbiotic ends by avoiding costly boom-bust cycles in the related industries. We apply our approach in the notoriously cyclical commercial aviation related industries.

Hypotheses and Contributions
The objective of this paper is to show that the costly boom and bust cycles that have beleaguered commercial aviation can be dampened using sets of symbiotic strategies that have a Pareto efficient impact on the stakeholders involved. We use framework and modeling innovations to identify those strategies and to study their impact.

Cyclicality: Costs, Causes, and (Potential) Solutions
Cyclical behavior in the airline industry has been identified by (Jiang and Hansman 2004) and (Weil 1996) among others. Similar instabilities of varying degree have been observed in shipping (Dikos 2004), telecommunications, oil refineries (Weil and Stoughton 1998), and other industrial markets.

In a manifestation of the ‘bullwhip effect’ observed in supply chains, the cyclical instability faced by airlines increases the severity of variation in the demand that is faced by the airframe manufacturers. While the cycle can be observed ipso facto, attempts to predict it are faced with significant uncertainty and high stakes since erroneous forecasts may result at the very least in loss of ground to competitors. Given the unpredictability and high stakes, cyclical instabilities are associated with concomitant costs.

For the private sector that is faced with highly cyclical profitability these costs range from liquidity constraints to vulnerabilities to bankruptcy, hostile take-over, or market-share loss. Attempts to adjust by following the cycle that involve employee dismissal can result in knowledge hemorrhaging and ill-will towards the firm. On the other side of the cycle, they may lead to unsustainable growth, upward creeping unit costs, and overcapacity. The society at large is also affected due to labor distress, tax payer assumption of defaults, and a general sub-optimal use of resources.

The existence of such critical industrial cycles has spurred research into their causes. The list below summarizes some of the identified potential causes of cyclical behavior as expounded in the economics, operations research, and industrial organization literature:
Macroeconomic cycle.
Uncertainty.
Imperfect financing.
Irreversibility.
Intertemporal substitution.
Input variability.
Labor hoarding.
Inventory.
Lead times.
Technology
Decision making:
Bounded rationality,
Investment exuberance,
Strategic optimism.

Starting from a large set of potential causes, the set of strategies to counter their effect is similarly large. A sample of such strategies is given here:
Transparency
Information sharing
Uncertainty management
Lead time reductions
Output stabilization
Capacity constraining
Price stabilization (demand management)
Technical/operational product improvements
Extensive use of leasing (for capacity flexibility)
Off-cyclical behavior (buy low, sell high – shipping)
Capacity constraining
Less aggressive revenue management
Mergers
Subsidies / long-term financing
Total subsidy withdrawal
Re-regulation (price or market capping)

In the paper we discuss the more promising strategies in the context of the stakeholders that can implement them and, more importantly on their impact. The intent of investigating these strategies is to promote “symbiosis.” We define symbiotic strategy to connote an action taken by one or more EoE constituents that improves aggregate EoE system performance over a long-term horizon. Ideally, this action is Pareto efficient and not detrimental to the short-term interests of the actor(s) but not necessarily so.

The Enterprise of Enterprises Framework, Experimental Modeling, and Expected Results
Empirical evidence suggests that even in the absence of most of the procyclical factors, ‘bullwhip’ behaviors can still be observed (Croson, Donohue et al. 2004). This makes the task of symbiotic strategies to offset the causes hard enough but what makes it even harder is the need to anticipate their impact on the stakeholders and on the EoE given the high levels of system complexity involved.

To address these difficulties we use the EoE framework as a tool for distilling the critical behavior of the stakeholders and a hybrid agent-based and system dynamics modeling methodology to build corresponding model platforms. Once validated, we can then use these models to test the proposed symbiotic strategies under different scenarios and identify those strategies that lead robustly to improvements in the desired performance metrics on a stakeholder by stakeholder and on an EoE basis.

The EoE concept stems from the System of Systems (SOS) literature (Maier 1998) as currently expanded by Shah. EoEs, like SOS, exhibit purposeful, sometimes self-organizing behavior while their constituents (or components) have disparate or even competing value functions. Distilling the value functions of the constituents and the character of their interactions (couplers) provides a way of modeling the system disregarding much of the constituents’ internal complexity.

Using this structure of value functions and couplers as basis, we construct a hybrid agent-based and system dynamics model which because of its disaggregate nature (each constituent enterprise is an agent with potential diverse strategies and characteristics) allows us to examine how a potential symbiotic strategy implemented only by a subset of the constituent enterprises can affect the system behavior in the long term and of course its impact on the actor(s). This disaggregation on the level of the enterprise, rather than on the level of the industry for existing models, is a particularly useful feature when it comes to setting the macro-level enterprise strategy and accordingly the goals of enterprise transformation.


References

Croson, R., K. Donohue, et al. (2004). "Order Stability in supply chains: Coordination Risk and the role of Coordination Stock." ESD Working Papers Series.
Dikos, G. (2004). Decisionmetrics: Dynamic Structural Estimation of Shipping Investment Decisions. Dept. of Ocean Engineering. Cambridge MA, Massachusetts Institute of Technology: 101.
Jiang, H. H. and R. J. Hansman (2004). An Analysis of Profit Cycles In the Airline Industry. M. Massachusetts Institute of Technology Cambridge, MIT International Center for Air Transportation. Report No. ICAT-2004-7.
Maier, M. W. (1998). "Arichitecting Principles for Systems-of-Systems." Systems Engineering 1(4): 267-284.
Weil, H. B. (1996). Commoditization of Technology-Based Products and Services: A Generic Model for Market Dynamics. Cambridge MA, Sloan School of Management. Massachusetts Institute of Technology.
Weil, H. B. and M. D. Stoughton (1998). "Commoditization of Technology-based Products and Services." Sloan Working Papers.