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Complexity Science & Adaptive Supply Networks

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Complexity Science & Adaptive Supply Networks

  1. 1. Complexity Science and AdaptiveSupply Networks:One Answer to the Challengeof Sea Enterprise Major Kelly G. Dobson Commandant of the Marine Corps National Fellow IBM Business Consulting Services
  2. 2. Complexity Science 1Complexity Science and Adaptive Supply Networks: One answer to the Challenge of Sea Enterprise Major Kelly G. Dobson Commandant of the Marine Corps’ National Fellow IBM Business Consulting Services Supply Chain and Operations Solutions May 21, 2003
  3. 3. Complexity Science 2 Abstract The Challenge of Sea Enterprise calls upon the naval services to draw onthe lessons of the business world to make activities such as operating the supplychain cheaper, more efficient, easier to use, and less manpower intensive.Additionally, with an eye to future war fighting strategies, the naval services musttransition to anticipatory, more flexible logistics which leverage information andprovide needed support where and when it is most needed. Building upon bothevolutionary and revolutionary examples from the business world, the navalservices have the opportunity to leverage Agent-Based Modeling, aided bydynamic tracking technologies, into a truly anticipatory, responsive, and adaptivesupply network. This network could not only answer the challenge of SeaEnterprise, but also would adapt well to form the nucleus of the future joint supplynetwork.
  4. 4. Complexity Science 3 Complexity Science and Adaptive Supply Networks: One answer to the Challenge of Sea Enterprise The Challenge of Sea Enterprise “Among the critical challenges that we face today are finding andallocating resources to recapitalize the Navy.” (40) These are the opening wordsAdmiral Clark used to describe Sea Enterprise, an essential element of SeaPower 21. He went on to say that, “we will make our Navy’s business processesmore efficient to achieve enhanced warfighting effectiveness in the most cost-effective manner.” (40) Admiral Clark then sums up the means and the goals ofSea Enterprise: “Drawing on lessons from the business revolution, SeaEnterprise will reduce overhead, streamline processes, substitute technology formanpower, and create incentives for positive change.” (40) One response to the challenge of Sea Enterprise might be simply tocapitalize on the lessons learned from previous experience and incrementallyimprove current Navy business processes. However, as recent events suggest,Sea Enterprise must also promote the development of solutions capable ofsupporting emerging military tactics. President Bush, aboard the USS AbrahamLincoln, noted that: “Operation Iraqi Freedom was carried out with a combination
  5. 5. Complexity Science 4of precision and speed … Marines and soldiers charged to Baghdad across 350miles of hostile ground in one of the swiftest advances of heavy arms in history” When discussing the capabilities required to support concepts such asSea Basing and other emerging strategies, Vice Admiral Moore, Deputy CNO forFleet Readiness and Logistics, and Lieutenant General Hanlon, CommandingGeneral, Marine Corps Combat Development Command, asserted that the navalservices’ future logistics enterprise must: “leverage information to achieveefficiencies and provide support at the time and place of greatest impact.” (82)They went on to say that naval service logistics must “shift toward anticipatory,responsive logistics.” (82) Focusing specifically on the supply chain, the challenge of Sea Enterprisethen becomes three fold: First, given the recent glimpse at the future, how doesthe supply chain need to change in order to support a broader spectrum ofconflict? Second, what are the lessons from the business revolution? Finally, howare these lessons applicable to the naval services’ supply chain in order toreduce overhead and improve effectiveness? Accepting Admiral Moore’s andGeneral Hanlon’s description as a starting point for the future characteristics ofthe naval services’ supply chain, the next question becomes are there relevantlessons from the business revolution?
  6. 6. Complexity Science 5 Key Lessons from the Business RevolutionComplexity Science One of the applicable lessons from the business revolution is complexityscience. Complexity science is not a new field of study, but a new approach forstudying complex, adaptive systems. Adaptive systems consist of numerous,varied, simultaneously interacting parts, called agents. The goal of complexityscience is to uncover the underlying principles and emergent behavior of complex systems, often invisible using Birds Flocking The basic flocking model consists traditional approaches. of three simple steering behaviors which describe how an individual boid maneuvers based on the positions and velocities its nearby Separation The difference flockmates: between traditional Separation: steer to avoid crowding local flock mates methods of analysis Alignment: steer towards the average heading of local flock and complexity science mates Alignment involves a shift in focus Cohesion: steer to move toward the average position of local flock mates and methodology. Reynolds - Boids Traditional methods Cohesion rely on cause-and- effect analysis: byknowing all the factors that affect a situation, one can predict the outcome of thesituation. Conversely, complexity science holds that behavior is oftenunpredictable and analyzing the factors of a situation may not gain the requisite
  7. 7. Complexity Science 6insight. As an example, complexity scientists discuss the steering behaviors ofbirds: each individual bird maintains separation, alignment, and cohesion with theother birds in the flock. (Sidebar) Given these three factors particular to each birdin the flock, it is unlikely one would predict that the group of birds flock, but that iswhat they do as emergent behavior from their steering behavior interactions.Agent-Based Modeling (ABM) To capitalize on the insight offered by complexity science, scientists andcorporations have developed Agent-Based Modeling (ABM) which usescollections of autonomous decision-making entities called agents. Each agent inthe simulation assesses the current situation and makes decisions based uponits set of rules. The rules themselves are not the essential product of thesimulation; rather the benefit comes from the interactions between agents andthe emergent behavior these interactions produce. But to glimpse at emergent behavior requires numerous iterations – manytimes the number required for traditional simulations – and until fairly recently,there was insufficient computing power to make these multiple simulation runs ina cost effective manner. However, because of recent capabilities and productimprovements, analysts can run the simulations hundreds or thousands of timesto develop a distribution of emergent behavior while incurring only nominal costs.By comparing this behavior to historical data, the analysts validate the accuracyof the model. Once validated, the model provides something that most traditionalapproaches cannot: the ability to model changes to the system, such as
  8. 8. Complexity Science 7obstacles or bottlenecks, and predict how the real system agents would adapt tothese changes. This ability changes ABM from a purely analytical tool to apredictive tool. ABM offers the potential to accurately model not only the mainelements of the naval services’ supply chain, but all the interactions and“workarounds” that become such an integral part of the dynamic system. Thisability to extract useful information from agent interactions led Procter andGamble (P&G) to use ABM tools in an effort to reduce supply chain inventory.P&G Case Study: Evolutionary business rules In 1998, P&G had already achieved a 50% reduction in their inventory,and was looking for an additional 25% reduction in an effort to control costs.P&G’s desire to cut inventory seemed to run counter to their need to keepproducts such as Tide and Comet on the store shelf. Using ABM, P&G found thata “seemingly logical policy sending out only full trucks actually createddisruptions along the supply chain … [resulting in] supermarket shelves that wereempty of its key products.” (Bylinsky, 5) Supply chain agents within P&G’s ABMrecognized this self-induced obstruction and correctly modeled a new,evolutionary approach: “letting some trucks travel with partial loads and makingdelivery times more flexible.” (Bylinsky, 5) Not only did the proposed solutionmeet predicted results, it exceeded them. After implementing the ABMmodifications, “Procter & Gamble Co. saves $300 million annually on aninvestment of less than 1% of that amount” (Anthes, 1)
  9. 9. Complexity Science 8 While the return on investment of the P&G example is impressive, similarresults might have been attainable by traditional methods and are evolutionary innature. On the other hand, what Air Liquide did with AMB was truly revolutionary.Air Liquide Case Study: Revolutionary business rules Air Liquide is a Houston-based industrial gas firm, which supplies “liquid oxygen, nitrogen, and other gases to 10,000 customers from more than Radio Frequency Identification (RFID) 300 sources through 30 depots, This tag, approximately the size of a shirt button, is: using 200 trucks and 200 trailers.” a “smart object” implementation for item/object tagging that enables end-to-end (Mucha) The scope and complexity asset awareness. At its core, RFID uses tags, or transponders that have the ability to store information that can be transmitted wirelessly in of Air Liquide’s supply chain was an automated fashion to specialized RFID readers, or interrogators. This stored daunting with “3 trillion daily information may be written and rewritten to an embedded chip in the RFID tag. When affixed to various objects, tags can be read when they combinations among all its detect a radio frequency signal from a reader over a range of distances and do not require line-of-sight orientation. The reader then sends constituent parts; it took 22 full-time the tag information over the enterprise network to back-end systems for processing. (Levine, 3) logistics analysts nearly half a day to Conceptually, the logistics supply chain could tag everything from pallets, boxes, generate a delivery schedule that even down to individual items if their size or importance demanded. This would provide the would get every product to its dynamic tracking visibility that so many other programs seek, but with a much higher degree of granularity in that each tag is able to know destination on time.” (Mucha) Using the contents of its attached container. Also, the cargo would now ‘know’ its destination, required delivery date, and associated cargo, which in ABM, the truck “agents” were not turn would allow en route synchronization and adaptive rerouting when tied with the proper only programmed to find the shortest ABM system. routes, but to remember those routes and compare them with other routes
  10. 10. Complexity Science 9found, optimizing short-cuts and compiling new routes from sections of previouslyoptimized routes. Most importantly, because of the power of ABM, “just one AirLiquide analyst is needed to create daily shipping and production schedulesacross its numbingly complex supply chain in about two hours.” (Mucha) With theproven cost savings and overhead reduction of P&G’s efforts and the manpowerreduction and adaptive supply chain of Air Liquide, ABM offers some potentiallyrevolutionary supply chain management lessons.Real Time Modeling The business examples demonstrated ABM’s ability to be bothevolutionary and revolutionary with its approaches to greater supply chaineffectiveness. But even in the Air Liquide example, the information optimized hadsome time delay inherent to it – the analyst based the schedule on the knownconditions at a certain point the day prior. While the analyst was able to veryrapidly respond to a bottleneck or an obstacle such as an interstate shutdown,the information he worked with was not the most current due to this time delay.What if it were possible to remove that time delay? While a powerful tool in itsown right, one can greatly enhance ABM’s power by supplying the model withreal time data from the actual supply chain. Several technologies, including RFID(sidebar) offer the potential for dynamic tracking. With the advent of low-costcomputing capacity, Agent-Based Modeling, and dynamic tracking technology,the naval services have the potential to develop a real time adaptive supplysystem.
  11. 11. Complexity Science 10 An Illustration of Military Applications As an example of ABM’s potential when supplied with dynamic trackinginformation from the naval services’ supply chain, let us look at a critical node inan existing supply chain: Sigonella, Italy. Currently, when ships deploy to theMediterranean, each group typically leaves an expeditor at Sigonella to rescuefrustrated cargo and ensure that all the cargo destined for the target groupactually makes it to that group. Expeditors rely on ship-to-shore communicationsfor priorities and a shore-based information system to know what cargo isinbound or is lost en route for what ever reason. Additionally, the expeditormaintains a list of priority cargo that takes precedence over other, lower prioritycargo. While the expeditor can be highly effective, he represents a manpowerintensive workaround to a supply chain problem. Additionally, the work of oneexpeditor may well prove counter to the work of another, adding greaterinefficiency to the system. Contrast the expeditor system with an ABM supply chain leveragingdynamic tracking. In this system, each piece of cargo becomes its own expeditor.Using RFID as an example, each tag retains knowledge of its host’s contents, itsdestination, its required delivery date, and even associated cargo necessary forthis cargo to be useful for the end user. Since this data is stored on the RFID tag,and not part of a remote system located at Sigonella, the loss of the facility or asystem at the facility does not destroy the required destination of the cargo.Additionally, by capturing all dynamic tracking data via remote interrogation andfeeding it real time to the ABM, the system constantly learns and optimizes itself,
  12. 12. Complexity Science 11even allowing cargo synchronization with partner cargo en route, relievingmanpower requirements on the end user. This capability alone might make ABMworth the cost of investment, but this new system really shows its strength whensomething goes wrong. Imagine that some terrorist faction detonates a bomb at Sigonella,effectively shutting down the node and putting all the expeditors out of action. Fora traditional supply chain to react to this situation, news of the bombing must firstmake its way back up the supply chain to the managers, potentially taking on theorder of minutes or as long as days. With the knowledge of the lost node, thesupply chain managers must determine alternate routes and enact those routes.Then, still in a reactive mode, they must assess the impact that changing toalternate routes has had on other nodes and adjust accordingly, potentiallyrouting too much cargo through ports with insufficient capacity. This furthercongests the supply chain and potentially leads to individual supply chainmanagers developing solutions that create even more congestion. Now, take that same scenario, but this time using ABM to manage thesupply chain. Because of the dispersed nature of the ABM and the visibilityprovided by dynamic tracking, the system could potentially recognize that there isa problem with the Sigonella node before anyone even finds out that a bombwent off. Recognizing the impact to cargo in the system, ABM considers the timesensitive nature of shipments and automatically reroutes critical shipments.Simultaneously, ABM down-grades the priority of items in the supply chain that
  13. 13. Complexity Science 12depend on other items unavoidably delayed. Finally, ABM, leveraging itspredictive nature and emergent behavior analysis capabilities, anticipates theimpact of routing changes on the entire system, preemptively eliminating thepotential bottlenecks. If cargo is somehow isolated from the master ABMnetwork, it still retains all of its destination information. Similar to mission specificorders and commander’s intent, the cargo assesses the situation at the nextnode and continues toward its intended objective. Turning Supply Chains into Supply Networks Lieutenant General Van Riper, USMC retired, spoke at a conference titledPreserving National Security in a Complex World in September of 1999. Duringhis comments – A General Perspective on Complexity – General Van Riperreminded his listeners, “if you do not cast your net widely and look at places thattraditionally Marines wouldn’t look, you are not going to find the right answers …”(Van Riper, 179) Using complexity science and Agent-Based Modeling tomanage the naval services’ supply chain would definitely be a wide cast of thenet. However, the question remains: while the potential of cheaper, moreefficient, simpler, and less time consuming alternatives appear successful in thebusiness world, is it too great a hope to believe that they could produce the sameresults for the naval services? P&G was so impressed with the transformation of their supply chain, theyrenamed it a supply network. According to Larry Kellam, P&G’s director of supplynetwork, “Chain connotes something that is sequential, that requires handing off
  14. 14. Complexity Science 13information in sequence … we believe it has to operate like a network …” whereall the parts are dynamically interacting. The payoff from successfully applyingthis new way of thinking about logistics – the challenge of Sea Enterprise – holdstremendous potential in both cost and effectiveness. By recognizing this potentialto transform how the military thinks about supply, the naval services have theopportunity to lead the transition to the supply networks needed to properlysupport tomorrow’s warfighting requirements. And this technique would adaptwell to cut across the bounds of the traditional service specific supply lines toform the nucleus of a joint supply network.
  15. 15. Complexity Science 14 ReferencesAllan, T. (Consultant). (2003). The Adaptive, Automated Supply Chain. [Microsoft PowerPoint Presentation]. Tampa Bay, FL: IBM.Anthes, G. H. (2003, January 27). Agents of Change. ComputerWorld. Retrieved May 8, 2003 from the World Wide Web: www.computerworld.com/softwaretopics/erp/story/0,10801,77855,00.htmlBergonzi, C. (2001, September). Thriving in the econosphere. Continental, 75-79.BiosGroup Complexity Science Overview and Toolkit. (2002). BiosGroup, Inc. 4.Bush, G. W. (2003, May 1) [Full text of speech aboard the USS Abraham Lincoln]. Washington Post on the Web. Retrieved from the www: http://www.washingtonpost.com/wp-dyn/articles/A2627-2003May1.htmlBylinsky, G. (2000, November 27). Look who’s doing R&D. Fortune Industrial Management & Technology. [Excerpt] 5.Clark, V. (2002, October). Sea Power 21. Proceedings, 33-41.Giordano, A. A. (2003, April). Make the supply chain combat ready. Proceedings, 40-42.
  16. 16. Complexity Science 15James, G. E. (1996). Chaos Theory: The essentials for military applications. Newport, RI: Naval War College Press.Levine, R. (Director of Emerging Business Technologies). (2003, February 24). Smart Chip & Automated Technology Solutions from IBM. [Microsoft PowerPoint Presentation]. Chicago, IL: IBM.Magruder, C. B. (1991, May 1). Recurring Logistic Problems As I Have Observed Them. Washington, DC: U.S. Government Printing Office.Marine Aviation Weapons and Tactics Squadron One. (2000, May 5). A Marine Expeditionary Brigade in 2010: An analysis of operational potential and logistical capabilities.Moore, C. W., Hanlon, Jr. E. (2003, January). Sea Basing: Operational Independence for a New Century. Proceedings. 80-85.Mucha, T. (2002, November). The wisdom of the anthill. Business 2.0. Retrieved May 14, 2003 from the World Wide Web: http://www.business2.com/articles/mag/print/0,1643,44528,00.htmlReynolds, C. (1995, June 29). Boids (Flocks, Herds, and Schools: a Distributed Behavior Model). Retrieved May 13, 2003 from the World Wide Web: http://www.red3d.com/cwr/boids/Roston, E. (2001, May). Nature’s bottom line. Time Bonus Section: Your Business, pp. Y9, Y10.
  17. 17. Complexity Science 16The making of a futurist: an interview with Simon Ellis. (2003, January 1). [Interview with Simon Ellis]. Supply Chain Management Review. Retrieved May 8, 2003 from the World Wide Web: http://www.manufacturing.net/scm/index.asp? layout=article&articleid=CA276608&text=agentVan Riper, P. (1999, September 13). A general perspective on complexity. [Address to Preserving National Security in a Complex World Conference, Cambridge, MA. September 12-14, 1999]. Conference Summary brochure.Waldrop, M. M. (1992). Complexity: The emerging science at the edge of order and chaos. New York: Touchstone.

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