Enterprise Resilience Assessment—A Quantitative Approach

Enterprise resilience is a key capacity to guarantee enterprises’ long-term continuity. This paper proposes a quantitative approach to enhance enterprise resilience by selecting optimal preventive actions to be activated to cushion the impact of disruptive events and to improve preparedness capability, one of the pillars of the enterprise resilience capacity. The proposed algorithms combine the dynamic programming approach with attenuation formulas to model real improvements when a combined set of preventive actions is activated for the same disruptive event. A numerical example is presented that shows remarkable reductions in the expected annual cost due to potential disruptive events.

[1]  Y. Sheffi,et al.  A supply chain view of the resilient enterprise , 2005 .

[2]  Devanandham Henry,et al.  Perspectives on measuring enterprise resilience , 2010, 2010 IEEE International Systems Conference.

[3]  V. Cruz Machado,et al.  Supply Chain Resilience Using the Mapping Approach , 2011 .

[4]  Bilal M Ayyub,et al.  Systems Resilience for Multihazard Environments: Definition, Metrics, and Valuation for Decision Making , 2014, Risk analysis : an official publication of the Society for Risk Analysis.

[5]  L. Azeez,et al.  Available Online at www , 2010 .

[6]  F. Oliva,et al.  A maturity model for enterprise risk management , 2016 .

[7]  P. Schrimpf,et al.  Dynamic Programming , 2011 .

[8]  Raquel Sanchis,et al.  Enterprise resilience assessment: a categorisation framework of disruptions , 2014 .

[9]  M. O'hare,et al.  Searching for Safety , 1990 .

[10]  T. Chou,et al.  Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors. , 1984, Advances in enzyme regulation.

[11]  Adam Rose,et al.  Economic resilience of the firm: A production theory approach , 2019, International Journal of Production Economics.

[12]  R. Bellman The theory of dynamic programming , 1954 .

[13]  M S Belen'kii,et al.  Multiple drug effect analysis with confidence interval. , 1994, Antiviral research.

[14]  Rodrigo Reyes Levalle,et al.  Resilience by teaming in supply network formation and re-configuration , 2015 .

[15]  Steven Skiena,et al.  Who is interested in algorithms and why?: lessons from the Stony Brook algorithms repository , 1999, SIGA.

[16]  Yacov Y Haimes,et al.  On the Definition of Resilience in Systems , 2009, Risk analysis : an official publication of the Society for Risk Analysis.

[17]  R. Sanchis,et al.  Mitigation proposal for the enhancement of enterprise resilience against supply disruptions , 2019, IFAC-PapersOnLine.

[18]  Timothy J. Pettit Supply Chain Resilience: Development of a Conceptual Framework, an Assessment Tool and an Implementation Process , 2008 .

[19]  H. Boer,et al.  Supply chain integration, risk management and manufacturing flexibility , 2018 .

[20]  L. Comfort,et al.  Complex Systems in Crisis: Anticipation and Resilience in Dynamic Environments , 2001 .

[21]  H. Weingartner Capital Budgeting of Interrelated Projects: Survey and Synthesis , 1966 .

[22]  Keely L. Croxton,et al.  Resilience of medium-sized firms to supply chain disruptions: the role of internal social capital , 2019, International Journal of Operations & Production Management.

[23]  Christopher W. Zobel,et al.  Economic impact of production bottlenecks caused by disasters impacting interdependent industry sectors , 2015 .

[24]  Raul Poler Escoto,et al.  Definition of a Framework to Support Strategic Decisions to Improve Enterprise Resilience , 2013, MIM.

[25]  Fernando Sampedro Risk Ranking : Moving towards a Risk-Based Inspection and Surveillance System , 2020 .

[26]  Roland W. Scholz,et al.  Risk, vulnerability, robustness, and resilience from a decision-theoretic perspective , 2012 .

[27]  Azad M. Madni,et al.  Towards a Conceptual Framework for Resilience Engineering , 2009, IEEE Systems Journal.

[28]  Erik Hollnagel,et al.  Barriers And Accident Prevention , 2004 .

[29]  G. Nemhauser,et al.  Discrete Dynamic Programming and Capital Allocation , 1969 .

[30]  P. Ball,et al.  Local food supply chain resilience to constitutional change: the Brexit effect , 2019, International Journal of Operations & Production Management.

[31]  M. C. Holcomb,et al.  Understanding the concept of supply chain resilience , 2009 .

[32]  Anna Corinna Cagliano,et al.  An integrated approach to supply chain risk analysis , 2012 .

[33]  Mickael Guedj,et al.  Analysis of drug combinations: current methodological landscape , 2015, Pharmacology research & perspectives.

[34]  M. Parast,et al.  A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research , 2016 .

[35]  Keely L. Croxton,et al.  ENSURING SUPPLY CHAIN RESILIENCE: DEVELOPMENT OF A CONCEPTUAL FRAMEWORK , 2010 .

[36]  Kenneth K. Boyer,et al.  Supply chain information flow strategies: an empirical taxonomy , 2009 .

[37]  Didier El Baz,et al.  Solution of multidimensional knapsack problems via cooperation of dynamic programming and branch and bound , 2010 .

[38]  Louis Anthony Cox,et al.  Community resilience and decision theory challenges for catastrophic events. , 2012, Risk analysis : an official publication of the Society for Risk Analysis.

[39]  Matti Kaulio,et al.  Supply-side resilience as practice bundles: a critical incident study , 2016 .

[40]  E. Dalziell,et al.  Resilience, Vulnerability, and Adaptive Capacity: Implications for System Performance , 2004 .

[41]  Paul Talalay,et al.  Analysis of combined drug effects: a new look at a very old problem , 1983 .

[42]  Amanda J. Schmitt,et al.  A Quantitative Analysis of Disruption Risk in a Multi-Echelon Supply Chain , 2011 .

[43]  Jonas Hagmann,et al.  Measuring resilience: methodological and political challenges of a trend security concept , 2014 .

[44]  I. Mitroff,et al.  Preparing for evil. , 2003, Harvard business review.

[45]  C. S. Holling Resilience and Stability of Ecological Systems , 1973 .

[46]  H. Martin Weingartner,et al.  Methods for the Solution of the Multidimensional 0/1 Knapsack Problem , 1967, Operational Research.

[47]  J. L. Rouvroye,et al.  A comprehensive approach to assess operational resilience , 2008 .

[48]  M C Berenbaum,et al.  Synergy, additivism and antagonism in immunosuppression. A critical review. , 1977, Clinical and experimental immunology.

[49]  Neelke Doorn,et al.  Resilience indicators: opportunities for including distributive justice concerns in disaster management , 2017 .

[50]  R. Tallarida,et al.  Quantitative methods for assessing drug synergism. , 2011, Genes & cancer.

[51]  Joel Cord,et al.  A Method for Allocating Funds to Investment Projects when Returns are Subject to Uncertainty , 1964 .