SOLOMON

A Proposed Supply Chain A Proposed Supply Chain Risk Management Risk Management

FrameworkFramework

Adrian Solomon, Panayiotis Ketikidis and Alok Choudhary

15th Panhellenic Logistics Conference & 1st SEE Congress on SCMThessaloniki, Greece, 2011

1. City College – International Faculty of the University of Sheffield2. South East European Research Centre 3. The University of Sheffield

Adrian Solomon, Panayiotis Ketikidis and Alok Choudhary15th Panhellenic Logistics Conference & 1st SEE Congress on SCM

PERFORM A LITERATURE REVIEW ON ICT DEVELOPMENTS FOR SCRM

IDENTIFY LITERATURE GAPS

PROPOSE A SCRM FRAMEWORK WITH A DSS FOR RM

BRIEF AIM OF THE PAPER

• What is SCM and SCRM

• Current issues in SCM and SCRM

• SCM and SCRM Developments

• Current Requirements for Effective SCRM

• The Role of ICT Paradigms

• Literature Gaps

• The proposed framework


OUTLINE

• Supply chain management (SCM) is the management of the network of interconnected businesses involved in the provision of products and services required by the end customer.• Involves design, planning, execution, monitoring, control, synchronisation, etc.

• Supply chain risk management (SCRM) the intersection of risk management (RM) discipline with SCM and aims to deal with potential supply chain (SC) disruptions that affect the normal flow.


WHAT IS SCM AND SCRM ?

SCM

SCRM

• Increased competitive pressure

• Stagnating markets

• Decreased stocks

• Longer transportation

• Increased inter-dependency

• Disruptions

• Terrorism


CURRENT ISSUES IN SCM AND SCRM I

• Supplier failure

• Environmental instability

• Business network issues


SUPPLY CHAIN RISKS

“these uncertain variations affect the flow of information, materials or products across organization borders” (La Londe, 1997)

“the variation in the distribution of possible supply chain outcomes, their likelihood and their subjective values” (March & Shapira, 1987)

CURRENT ISSUES IN SCM AND SCRM II


RISK OUTCOMES

RISK SOURCES

RISK MITIGATION

• Environmental• Network • Organizational(Jutna et al., 2003)

• Endogenous • Exogenous (Zsidisin, 2003)

• Control• Avoidance • Flexibility• Cooperation(Miller., 1992)

• Identification• Analysis• Control • Monitoring(Enyinda et al., 2008)

THE SCRM ENVIRONMENT

TIMELINE


BACK IN TIME NOW

• Centralized frameworks• Local supply chain structures • Interaction among partners only through the main centre • Manual decision making

• Decentralized frameworks• Distributed partners on long distances • Heterogeneous actors • Heavy inter- partner interaction• Automated decision making

WHY ?

SCM AND SCRM DEVELOPMENTS I

DUE TO MANY FACTORS ...


GLOBALIZATION

ICT DEVELOPMENTS

PROCESS INNOVATION

PUBLIC DEMAND

MARKET COMPETITION

MARKET LIBERALIZATION

POLICY DEVELOPMENTS

and many others...

BUSINESS REQUIREMENTS

SCM AND SCRM DEVELOPMENTS II

• ICT developments had a great impact on the advancements of SCRM frameworks, aiming to achieve automated reliable decision making (Giannakis & Louis, 2011) .

• Relevant ICT paradigms:


Agent Based Systems

Decision Support Systems

Data Mining

THE ROLE OF ICT

• Agent = “a system/entity that operates without the direct intervention of humans and has certain control over its action and internal state as well as it has the ability to interact with other agents” (Genesereth & Ketchpel, 1994)

• Agents deploy collaboration, intelligence and mobility (Julka et al., 2002)

• Multi-agent systems (MAS) allow efficient interaction in decentralized environments among heterogeneous actors

• Deal efficiently with emergent and concurrent actions (Moyaux et al., 2006; Parunak, 1996 and Verdicchio & Colombetti, 2002)


AGENT BASED SYSTEMS I

In simpler words, agent systems are useful because:


AUTOMATICALLY SOLVE PROBLEMS

COLLABORATE AND SHARE INFO

ARE EFFICIENT IN DESCENTRALIZED ENVIRONMENTS

DEAL WITH REAL-TIME ISSUES

THEY PERFECTLY SUIT THE REQUIREMENTS OF NOWADAY’S SUPPLY CHAIN ENVIRONMENT AND ARE A

VITAL STRUCTURE FOR THE INTEGRATION WITH A RISK DSS

AGENT BASED SYSTEMS II

• DSS = interactive software based systems used for information compiling (that take advantage of data mining and knowledge and data discovery (Piramuthu, 2005) with the ultimate goal of reaching a decision for a specific purpose (Zarandi & Zarandi, 2008).

• Data is transformed in information and information in knowledge

• Knowledge is used for decision making – automated informed decisions for managers


DECISION SUPPORT SYSTEMS

• Data mining = the application of algorithms for extracting specific patterns from data

• In SCM, data mining is usef for: • market analysis• inventory scheduling• customer and supplier categorization (Chatzidimitriou & Symeonidis, 2009)

• abnormality detection• market opportunities identification• inventory control (Mileff et al., 2006)

• cost reduction (Thotappa & Ravindranath, 2010)

• MAS


DATA MINING

WHAT ABOUT DM FOR SCRM ?

• Little emphasise is given to SCRM, most of the focus being rather on SCM and optimisation to increase profit

• The concept of “risk” is not thoroughly defined

• Few MAS for SCRM that incorporate a DSS for RM

• DM is not used at its full potential in SCRM


GAPS OPPORTUNITY SOLUTION

LITERATURE GAPS


THE PROPOSED FRAMEWORK

Forecasting agent • generates scenarios for future supply chain working environments • foresees potential risks in all the possible configurations/scenarios and to send those scenarios to the risk DSS module.

Corporate Strategy Agent • deals with all the business goals• has a decisive role in any decision making process.

Scheduling and Optimisation agent• scheduling and optimisation • deals with transport issues • logistic tasks


BRIEF FRAMEWORK DESCRIPTION I

Learning agent• updates the knowledge and data base of the SC

Dispatching agent • order release and for the • execution of the schedule

Inventory agent • manages the inventory

• certain storage economy capabilities.

Production agent • assures minimum manufacturing cost• coordination/interaction of the SC partners


BRIEF FRAMEWORK DESCRIPTION II

Inter-business communication agent • strategic role for gaining competitive advantage• offering the SC certain back-up solutions • keeps track of prospective SC partners

Risk / KPI monitor agent • identifies potential risk situations through monitoring key performance indicators

The risk DSS module • Deals with the solution generation/risk mitigation


BRIEF FRAMEWORK DESCRIPTION III

• Highly modular KBDSS that allows efficient incorporation of patterns and risk avoidance solutions, complying in the same time with the business rules

• Uses past experiences, incorporates learning capabilities, knowledge sharing, knowledge reuse and consolidation

• Captures implicit knowledge which leads to explicit knowledge


FRAMEWORK’S MAIN STRENGTHS

• Investigation of potential risks and risk sources and the provision of specialized and optimized solutions for several types of those identified risks

• Further investigation of knowledge extraction and management methodologies

• Testing and refining the proposed model

• Development of UML diagrams for the revised mode

• Review of the best agent interaction models and their limitations


FURTHER RESEARCH I

• Identification of the best technologies for real-time risk pattern detection based on manufacturing data

• Identification of the best model implementation environments, model implementation

• Research on the effects of emerging technologies on the transformation of SCRM


FURTHER RESEARCH II


QUESTIONS ?

SOLOMON

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