IJF Special Issue: Forecasting, Uncertainty and Risk Management

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IJF Special Issue: Forecasting, Uncertainty and Risk Management

Call for papers

Managing risk has gained prominence in the last two decade as governments, non-profit organizations and business firms are being confronted with new challenges, critical threats as well as great opportunities which increase the level of risks and raise the question of what to do to deal with them as effectively and rationally as possible.

Risks can be caused by completely unpredictable Black Swans, such as the 2004 tsunami that killed 250,000 people in Asia, preventable events as the pollution scandal that hit VW, causing huge direct and indirect losses estimated to more than $40 billion (its net profits for the last four years), possible losses from recessions that are known to affect societies, economies and firms, but whose exact influence as well as timing cannot be predicted but also great opportunities as those being exploited by start-ups like Uber and Airbnb. There are, therefore, many categories of risk, some known, some unknown, some statistically predictable, some not and some categorized as Black Swans. The big challenge is to evaluate all these risks of very different underlying nature and determine their overall influence in order to propose practical actions, both operational and strategic, to minimize their total negative impact or exploit the availing opportunities. In other words making sure that good things are happening and bad ones are avoided. But to do so requires not only to be able to predict the future, but also to forecast their specific impact, assess the uncertainty of such events materializing as well as their interaction, and finally, how they will all together affect the organization. Thus, managing risk is a highly complex and sophisticated activity that depends a great deal on the accuracy of forecasting, that in turn determines the extent of future uncertainty and eventually affects risks. In the management risk literature, however, the relationship of forecasting and uncertainty is not always clear. It is, therefore, a major objective of this special issue to clarify such relationship, explore its significance and practical implications and what can be done to deal with all aspects of managing risk.

Authors might like to consider the framework shown in Table 1 to explore the interrelationship of forecasting, uncertainty and risk, as it is clear that the accuracy of forecasting, the extent of uncertainty and the preparation to face risk are completely different in each of the four quadrants of Table 1. What is necessary is to move beyond the quadrant I of the known/knowns risks and cover adequately the additional three ones which, even though less frequent, they have a high potential impact, greatly influencing the entire organization. In addition, special effort needs to be placed on the quadrant III of the known/unknowns that includes behavioral issues and judgmental biases that also affect forecasting accuracy/uncertainty and therefore, risks.

Table 1: The Interrelationship of Forecasting, Uncertainty and Risk (varying in each of the four quadrants)

K N O W N U N K N O W N
I. Known/Knowns

(Knowing the events could occur as well as the related probability, or probability distribution, of the associated uncertainties)

Forecasting Accuracy: Reasonable (Depending on specific factors)

Uncertainty: Thin tailed and measurable

Risk Preparation: Risks are manageable through available risk frameworks such the US ISO 31000

III. Unknown/Known

(Judgmental, behavioral, and organizational influences)

Forecasting Accuracy: Can be very low (Due to judgmental biases, irrationality, wishful thinking and organizational issues)

Uncertainty: Large and immeasurable

Risk Preparation: Requires effort to avoid judgmental biases and organizational resistance

II. Known/Unknowns

(Real life situations under unusual/special situations)

Inaccuracy: Large to Great (Although history repeats itself, it never does so in the exact same way failing all efforts to accurately predict)

Uncertainty: Fat tailed, unable to measure quantitatively

Risk Preparation: Only possible by having implemented an effective monitoring system to provide warning signals as early as possible

IV. Unknown/Unknowns

(Black Swans: Unexpected, low probability high impact events with severe consequences)

Entirely Unpredictable (By definition Black Swans are unpredictable as they have not happened before and their arrival could not have been known)

Uncertainty: Infinite, no way to be known beforehand

Risk Preparation: Only possible by having adopted antifragile and similar strategies

Special Issue Goals and Topics

This special issue will cover but will not be limited to the following topics:

  • The Relationship of Forecasting, Uncertainty and Risk under various circumstances
  • Managing risks in each of the quadrants of Table 1
  • Forecasting and Uncertainty in Supply Chain Management and their implications to Risk
  • Forecasting and Uncertainty in Operational Risk and their implication to reputational and consequently Strategic Risks
  • Forecasting and Uncertainty in large, mega projects and how they affect risk as well as their implications to finish them on time and budget
  • Organizational complexity and emerging risks
  • Factors affecting forecasts and Uncertainty under different environmental conditions and their impact on Risk Management
  • The behavioural aspects of risk management, how to minimize their negative consequences and how to exploit the availing opportunities
  • Risk Management: From insurance and hedging to Resilience and Antifragility

The major purpose of the special issue is to show the interrelationship of forecasting/uncertainty and how to improve risk management by:

  1. Accepting the limitations of forecasting and exploiting as much as possible the available knowledge in the field
  2. Understanding that uncertainty exists practically everywhere and that must be accepted as such. Moreover, it must be acknowledged that there are different kinds of uncertainty, as shown in Table 1, and that some of them cannot be measured statistically.
  3. Distinguishing that managing risk is entirely different in each of the four quadrants of Table 1 and that a different approach is required for proposing ways of evaluating risk and deciding how to get prepared to face it depending on each quadrant.
  4. Provide practical advice to risk managers, concentrating on Enterprise Risk Management (ERM), as it affects a large number of companies eager to apply and benefit from new knowledge/ advice.

Submission Guidelines

To submit a paper for consideration for the Special Issue, please upload your paper online and include a cover letter clearly indicating that the paper is for the special issue on “Forecasting, uncertainty and risk management”. The webpage for online submissions is mc.manuscriptcentral.com/ijf. The deadline for receipt of papers is 30 June 2018. All papers will follow IJF’s refereeing process. Instructions for authors are provided at https://ijf.forecasters.org/authors

For further information about the Special Issue, please contact one of the guest editors.

Guest Editors

Spyros Makridakis

Following the attainment of a place in the Greek Sailing Team in the Olympics of 1960, Spyros Makridakis set sail for where he obtained a PhD in 1969. Since then he has advised numerous international organizations and government agencies and consulted worldwide.

Spyros has held teaching and research positions with several European and American institutions: as a research fellow with IIM Berlin, an ICAME fellow at Stanford University and a visiting scholar at MIT and Harvard.

Spyros is now a Professor at The University of Nicosia (UNCI) and the Director of the Institute of the Future. Previously, he was the Rector of the Neapolis University of Pafos and is an Emeritus Professor at the INSEAD business school. In addition to teaching and consulting expertise, he has also authored, or co-authored, 24 books including Forecasting, Planning and Strategy for the 21st Century (The Free Press), Forecasting: Methods and Applications, 3rd ed. and Forecasting Methods for Management, 5th ed. (Wiley, translated in twelve languages and sold more than 120,000 copies). He has also published more than 120 articles and book chapters. He was the founding chief editor of the Journal of Forecasting and the International Journal of Forecasting. Furthermore, he has won the “Best Teacher Award” at INSEAD twice.

Spyros’ current interest centers on the uses and limitations of forecasting and what we can do with the resulting uncertainty and risk given our inability to accurately predict a wide range of future events (e.g. the 2000 burst of the Internet bubble or the 2007-2009 major financial crisis). In addition, he is interested in medical decision making by comparing the costs and benefits of treatment. These and similar issues are dealt with in the book Dance with Chance: Making Luck Work for You (co-authored with Robin Hogarth and Anil Gaba) and in a special issue of the International Journal of Forecasting on “Decision Making and Planning Under Low Levels of Predictability” (co-edited with Nassim Taleb).

Richard Kirkham

Kirkham is a Senior Lecturer in Engineering Project Management. Prior to his appointment at the University of Manchester, he held the post of Lecturer in Quantity Surveying and Construction Management (Liverpool John Moores University, 2004-2008), Research Officer (School of Industrial and Manufacturing Science, Cranfield University, 2002-2004) and Research Assistant (School of Architecture, University of Liverpool, 2001-2002). He obtained a PhD in the application of stochastic methods in whole-life cost modelling at the University of Liverpool in 2002, and a BA in Construction Management in 1998. Dr. Kirkham has published widely in the fields of whole life costs, stochastic service life prediction and quantitative techniques in performance measurement, and is co-author of two texts on building/engineering cost modelling. He is scientific secretary of CIB-TG62 Complex Systems and the Built Environment, and co-managing editor of RICS Research Innovation in the Built Environment. In 2005, Dr. Kirkham was appointed as Visiting Research Fellow at the University of Liverpool. He is a Fellow of the Royal Statistical Society and immediate past-chair of the Liverpool Centre Chartered Institute of Building.

Terry Williams

Professor Terry Williams, former Dean of Hull University Business School, has 30 years’ experience in Operational Research (OR) modelling the behaviour of complex systems. Prior to Hull he was Professor in Risk then Director of Southampton University’s Management School, and prior to that at Strathclyde University.

He spent 9 years in industry building up a successful practice in non-military OR in engineering consultancy YARD, covering logistics, forecasting and availability, later specialising in Project-Risk Management (PRM) of major projects, including acting as Risk Manager for some major defence projects. His work later included supporting major post-project litigation claims, totalling over $1.5billion in Europe and North America, and he has participated in a number of research projects, some multi-£m. He has written around 80 Project Management / OR journal articles, with a Google h-index of 38, and a number of books. He spent ten years co-editing Journal of the Operational Research Society; he is a Fellow of the Institute of Mathematics and its Applications (and Chartered Mathematician); a Fellow of the Operational Research Society; and a qualified project manager (PMP).

He has now stepped down from the position of Dean to concentrate on research and consulting, and in particular to set up a University-wide Risk Institute.

Maria Papadaki

Maria Papadaki obtained her first degree in Business Economics from Salford University. Part of her undergraduate study was carried out in IPAG University in Nice (France). Maria completed her MSc in Management of Projects from The University of Manchester (UoM) in 2005. As an internship, Maria undertook an economic study into the viability of establishing Formula 1 racing in Crete. In 2006, she joined the UoM PhD programme and also worked as a research associate and teaching assistant for the school of Mechanical Aerospace and Civil Engineering (MACE). In 2008, she conducted an internship with the Risk Function in Rolls-Royce plc.. In 2009 was appointed as an Enterprise Risk Management Professional at Rolls-Royce’s. In 2011 she joined Rolls-Royce plc. Supply Chain Function as a Risk Manager in order to work cross functionally and across all Rolls-Royce plc sectors (Civil, Defense, Energy, Nuclear and Marine) to design, develop and implement integrated and standardised tools and processes to enable the business to proactively identify, manage and mitigate delivery risks across the global supply chain. In 2013, she completed her doctoral studies in the field of risk from The University of Manchester. In 2014, Dr Maria Papadaki was seconded as an Interim Head of Risk, leading the risk management for the UK Nuclear Restoration (UKNR), a joint venture between AMEC, Atkins and Rolls-Royce plc bidding for the largest nuclear decommissioning project in UK. In 2015, Maria initiated the idea and led the development of the first innovation Hub (H2B) in Crete, Greece on behalf of the Heraklion Chamber of Commerce. In 2016 Dr Papadaki joined the University of Manchester working as a Senior Relationship Manager for the British University in Dubai and the UK Alliance Universities and also acted as the Head of the Programme Management office and the DCRI (Dubai Centre for Risk and Innovation). She is now working as the Management Director for the DCRI and an Assistance Professor for BUiD. Her research is now focused on Blockchain, Artificial Intelligence, Enteprise Risk Management and Virtual and Augmented Reality. Dr Maria Papadaki has published numerous papers in the field of Enterprise and Portfolio, Programme and Project Risk Management.

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By |August 10th, 2016|Forecasting News|