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RISK MANAGEMENT IMPROVEMENT DRIVERS FOR EFFECTIVE RISK-BASED DECISION-MAKING

Purpose Most managers are not satisfied with the operations risk management tools they have got in their companies. This article addresses risk management enhancement within integrated risk informed decision-making. Methodology Three distinct and independent methods were used to analyze current practices and to find a solution: A) literature review, B) brainstorming, and C) structured interviews, achieving three lists of parameters that are integrated by using semantic technics and concept theory. Findings The result is a list of 66 risk assessment requirements which are going to be the success key for any new risk management system trying to fill the current gap. A new Risk Management solution is proposed fitting those requirements: The Visibility Factor method (Fv) and its risk summary method. Conclusion Risks should be managed in a better way and a list of key success factors and a concrete solution are provided to do it.


INTRODUCTION
New articles arise every year proposing new methods, algorithms, and studies related to risk management; and new articles also talking about the lack of academic research, risk management models and systematization (Sanchez-Cazorla et al.; Rodney et al.; Zio; Mantovani et al.). Companies are reluctant to accept innovations and typically continue to use their old methods which frequently rely on intuition and subjective evaluations, sometimes biased because of short-term approaches (Serpella et al.; Bello and Odusami). The lack of quantitative methodologies that are easy-to-use, universally applicable, and yield a quantitative value for the overall risk could be the root of this problem.
The articles studied stress the need to use risk indicators (Hamid and Kehinde; Renault and Agumba; Tanner and Hingorani; Tóth and Sebestyén) and overall ratings for decision-making (Murakami et al.). Many works present overall risk indicators devised for very specific scenarios (Orojloo et al.; Samantra et al., "Fuzzy Based Risk Assessment Module for Metropolitan Construction Project: An Empirical Study"; Shen et al.; West et al.); whereas others present methodologies that are probabilistic, fuzzy and multivariable (Cheng and Lu; Jung et al.); others apply neuronal networks (ANN) and multiple regression (Lam and Siwingwa; Lhee). Other works bring to light a lack of literature in complex scenarios and the difficulty that firms have when it comes to applying the sophisticated methods of scientific literature (Bromiley et al.; Deng and Smyth; Serpella et al.).
The most frequently used methodologies identify the risks and assess their impact and probability (or any other additional indicator) using Likert Scales (Likert). This qualitative assessment often turns into a semi-quantitative assessment, considering the product of the impact by its probability, hereinafter Risk Factor Fr (Alcocer-Yamanaka et al.). The value Fr makes it possible the comparison of a variety of risks among themselves. However, it is not very intuitive and has drawbacks owing to its lack of linearity and to the fact that it is the mean of a probabilistic distribution (Vegas-Fernández and Rodríguez-López). The sum total of the values of Fr for all the events analyzed (hereinafter, sum of products of probability times impact, SPTI) is considered the expected value of the project risk (Raftery), and it can either be regarded as an absolute value that measures the overall risk level, or it can be divided by the number of risk events to obtain the average Fr.
This practice is widespread (Zou et al.; Van Niekerk and Bekker; Rodney et al.; Carpio de los Pinos and González García) but it corresponds to the average value expected for a supposed Normal distribution of the overall risk value, which would require the applicability of the Central Limit Theorem (Raftery; Diekmann; Amade et al.); However, this theorem is not applicable to current projects because they do not fulfill the basic premises required by the theorem: a large number of independent (not correlated) risk events (>500) with no one component which contributes significantly (no Pareto effect) to the sum (Schuyler). As a result, the SPTI value is not suitable for estimating overall project risk or project risk cost (Vegas-Fernández and Rodríguez-López).

DATA AND METHODOLOGY
The aim of this study is to define the basic parameters to improve risk management within the integrated risk informed decision-making process. The result, a list with 66 ranked parameters, will help new risk management system definition to be successful.
A new indicator and a new method for estimating overall risk are presented as a possible response to the improvement parameters identified. This new system is simple and effective and it is intended to remove the traditional barriers that separate academic publications from customary practice (Taroun).
To make it consistent with the approaches of Aven (Aven) the research undertaken gives precedence to professional experience with international projects and the studying and reviewing of methods, theories, principles, and frameworks of application. With a view to this, 3 different techniques have been chosen among the techniques ISO 31010 proposes to identify risks and to assess solutions (International Organization for Standardization (ISO), "Risk Management -Risk Assessment Techniques"). In this study, they were used to obtain ranked lists of improvement ideas, which are integrated later on into a single ranked list. Integrating these techniques allows a final, reliable conclusion to be obtained (Fernández Sánchez; Hruškovič; Leceta Ostolaza; Pérez Soriano). These techniques are: 1, reviewing the available scientific literature. ISO 31010 and most authors use this information source to obtain qualitative information, but this study makes a deep study applying a method to obtain a quantitative outcome.
2, brainstorming. A means of collecting a broad set of ideas and evaluation, ranking them by a team. Brainstorming involves stimulating and encouraging free-flowing conversation amongst a group of knowledgeable people.
3, structured interviews. Individual interviewees are asked a set of prepared questions from a prompting sheet which encourages the interviewee to view a situation from a different perspective.
ISO 31010 proposes these techniques among others to identify risks and to assess solutions. In this study, they are used to obtain a ranked list of improvement ideas, which are integrated later on into a single ranked list.

Literature Review
In the study conducted into the 272 references selected, the analysis of syntagmas (clauses or words) is used to identify the concepts sought, and their appearance is weighted using weights that consider the document type (standard or regulation, doctoral thesis, book, indexed journal, lecture source, unindexed journal, master thesis, website run by a renowned organization and standard website). The date and their scope have also been considered by adding +0.5 in documents after 2009 and by subtracting 0.5 when they are intended for a specific activity or a particular country.
By adding for each concept the number of references that contains it times the reference weight, the outcome is a value that indicates the relevance of that concept in the references selected. The maximum value is 857 and corresponds to "decision-making". In order to check a possible Pareto behavior, an accumulated percentage is also obtained for each concept by dividing the sum of the accumulated values in a ranked list by the sum of all the values. Figure 1 displays the distinct weights assigned to each type of document.

Figure 1: Publication Weights
The structured list of the characteristics studied is shown next, with their punctuation (Table 1). It is ranked according to the values, and the accumulated percentage is the sum of the own and previous concept values divided by the sum of values.

Brainstorm
The brainstorm session was held in Madrid at the Escuela Técnica Superior de Ingenieros de Caminos, Canales y Puertos, and the subject dealt with was "Difficulties experienced in the everyday practice of project risk assessment and when informing about the overall risk situation, aimed at effective decision-making". The conclusions were that risk management had to be aligned with the company´s strategy, that a systematic and objective method is required in order to quantify the risks, backed up by a system that collects information from the operational units, that simple and easy-to-understand indicators are needed that make it possible to compare risks and scenarios with each other and with the risk appetite and red lines, and that the system has to be automatic and cannot be manipulated.
Each idea was given a score considering the number of attendees supporting that idea and the number of times that concept was repeated. The higher score was 36, assigned to "Objectivity".
The analysis of the ideas, homogenized and rated according to the number of participants in agreement, is summarized in Error! Reference source not found.. In order to check a possible Pareto behavior, an accumulated percentage is also obtained for each concept by dividing the sum of the accumulated values in the ranked list by the sum of all the values.

Structured Interviews
The interviews were held separately with 21 professionals from different industries (most of them from the construction sector), using a complex questionnaire structured. The findings indicated the need to obtain a numerical result for the overall risk for a scenario and for each risk matrix, the allocation of impact and probability using a Likert scale, and the use of linear scales to assess the interpretation.
A list of 41 concepts was proposed to the interviewees, asking them to rate each concept from 0 to 3, being 3 the higher relevance. The first interviews revealed the need to enlarge the list of concepts, and the result was a final list with 50 concepts.
The maximum obtained value was 63 and corresponds to "Qualitative rating of the overall risk level for the project". In order to check a possible Pareto behavior, an accumulated percentage is also obtained for each concept by dividing the sum of the accumulated values in a ranked list by the sum of all the values.
The structured list of the concepts rated is shown below (Error! Reference source not found.).

Integration
The analysis of the previous results shows that the Pareto effect is not present. So the idea of selecting just the top 20% concepts of each list is not suitable and all of them have been considered initially.
In order to integrate the findings, they were given a weight of 1.1 for the literature review, a weight of 1.0 for the brainstorm and a weight of 1.2 for the interview results. Priority is given to the interviews because the respondents were all practitioners, and much more time was devoted to this than to the brainstorm. An intermediate weight was given to the literature despite its great academic value, because of the distance between the publications and customary practice (Thamhain; Taroun; Deng and Smyth).
The different way the concepts were formulated for each one of these three study sources, a consequence of their different origin, makes it necessary to conduct a semantic analysis of the concepts announced in each one, with a view to establishing the equivalences that enable the findings to be integrated.
One single list of homogenized semantic concepts was then obtained, whose rating is the sum total, for each concept, of the scores for the semantically similar concepts in each source, using the previously defined weights. The list contains 66 results or basic improvement parameters, and it is displayed in Error! Reference source not found.. The accumulated percentage is showed one more time to confirm that the Pareto effect is not present even in the integrated results.

Discussing the Findings
The findings have been presented for the proposals for improvement of the risk management function in complex projects, both individually for each one of the study methods followed, but also for the view resulting from their integration. These findings are not consistent with the forecast of the Pareto rule, according to which 20% of the proposals (13) would attain 80% of the desired satisfaction (Leceta Ostolaza; Pérez Soriano), but 50% of them would make up 80% of the rating made.
An analysis of the 10 most important improvement parameters is significant when it comes to understanding the scope of the findings and showing that they are consistent with each other.
The best-rated aspect is "decision-making" and it reveals the importance of the risk management role in companies.
The second best-rated aspect, "Quantitative project rating", is a demand that has stood out in each of the three study sources, and it comes from lack of knowledge about the overall risk level of the projects when, for the analysis, a large number of risk events have been pinpointed (Institution of Civil Engineers and Institute and Faculty of Actuaries).
The "Need for objectivity" underlines the aforementioned parameters and demands a system that makes it possible to reduce subjectivity, pre-judgments and, even, decisions based only on experience.
The "Need to quantify (risks, groups, and matrices)" requires an analytical quantitative system to be able to conduct a detailed study of the risk situation affecting the project.
The fifth requirement, "Use of a risk indicator (KRI)", calls for a general indicator applicable to any type of risk and project, and demonstrates the lack of a general indicator applicable to all cases, essential for the analytical studies and the comparisons required by a decision-making system. A "Computerized system" is a basic requirement for achieving uniformity, reliability and an analytical view of risk management.
The seventh improvement parameter is "Qualitative project rating", and its presence among the most important is explained by the difficulties involved in quantifying many of the risks when using current methods and by the need to have a vision, even if it is only qualitative, of the risk level for the project as a whole.
The eighth and ninth requirements ask for "Uniformity" to standardize and compare situations, and for "Use of templates for risk assessment" to make it easier to work in a standardized way.
The tenth parameter "Importance of the risk analysis", rather than being interpreted as a guideline, has to be regarded as a call to attention with respect to the role that risk assessment ought to play in companies.
These 10 requirements, together with the remaining ones, are the improvement parameters that would make it possible to define a risk system to fulfill the needs explained, providing solutions to the current deficiencies.
The study concerning the parameters at the tail end showed that the proposals put forward for using the Fuzzy methods, the Neural Networks (ANN), multiple regression and forecasting were not generally accepted. It is also important to note that the concept of the 3 lines of defense (The Institute of Internal Auditors) received the poorest rating and is not associated with the strategy or the importance of risk management.
The fact that little importance is attached to using the Monte Carlo simulation (position 50) and considering the correlation between risk events (Position 51) also stands out. These parameters are interrelated, given that good modeling of the correlation is essential if the Monte Carlo method is to yield valid results (Rezaie et al.; Touran and Wiser).
SPTI is ranked 26 th in spite of yielding misleading values, mainly because the respondents to the questions in the interviews were not aware of the problems its use implies (see section "Current situation"). The use of Fr stands out too, in 29 th position, for the same reasons.  Bouayed; Hamid and Kehinde). This article defines key improvement factors that will ensure that practitioners will have the risk management system they need.

The Visibility Factor
An example of the application of these findings is the Visibility Factor method (Vegas-Fernández, "Sistema de Información de Riesgos: Factor de Visibilidad."; Vegas-Fernández and Rodríguez-López). Its design is the consequence of considering the proposed improvement parameters; it is an innovative solution that is easy to implement and provides a new risk indicator (Fv) and a method for summarizing risk events that allow for the quantitative and analytical processing of the basic impact and probability data (Vegas-Fernández, "Factor de Visibilidad. Nuevo Indicador Para La Evaluación Cuantitativa de Riesgos").
The Visibility Factor (Fv) is a linear indicator from 0 to 100 that uses the existing impact and probability definitions made using Likert scales to obtain an automatic value for the risk level. The method incorporates a risk summary system that enables the user to obtain a significant summary for any set of risks of any type expressed in terms of its impact, probability, and Fv; this calculation can be recursive, which makes it possible to obtain summaries at a higher level such as matrices, projects, countries, divisions or companies.
The suitability of the Fv method has been checked by being actually implemented in a construction company where it has been proved its applicability, versatility, and effectiveness when compared to traditional systems. It enables its users to control the risk involved in all the projects at the tendering phase, to define the risk appetite, and to incorporate the red lines definition into the system. It also makes possible to break down the risks as much as is thought necessary (Institution of Civil Engineers and Institute and Faculty of Actuaries) and to obtain a homogenized system that can be applied to all the projects, and that is more objective and enlargeable, with analytical capacities.
This system was presented as a project at the Project Management Institute Conference held in Valencia in 2015 (Vegas-Fernández, "Gestión de Riesgos.") and has been successfully implemented in a multinational construction company with headquarters in Spain. This implementation enabled its users to control the risk involved in all the projects at the tendering phase, to define the risk appetite, and to incorporate the red lines definition into the system (Vegas-Fernández, "Sistema de Información de Riesgos: Factor de Visibilidad."). Its simplicity also enables it to be easily programmed on spreadsheets so it can be incorporated into risk assessment templates at a very low cost.
Adopting this solution enables the user to break down the risks as much as is thought necessary (Institution of Civil Engineers and Institute and Faculty of Actuaries) to obtain a homogenized system that can be applied to all the projects, and this system is more objective and enlargeable, with analytical capacities.
The summarizing capability and the compliance with parameter #13 "Global impact and probability of the project" makes it possible to build risk maps such as figure 2, where the project risk is summarized by countries and the overall ("Total") risk is identified with its own impact and likelihood ( Figure 2).

CONCLUSION
This article provides highly significant guidelines for improving risk management, based upon thorough research that has taken into account the academic literature and the work of risk managers, and proposes a specific solution that meets the needs considered.
Three independent lines of research were used yielding a single rated list with 66 basic improvement parameters.
The 10 main parameters have been analyzed in detail because these are representative of the whole to understand the main guidelines for taking action. This information is important when it comes to devising any new indicator or system aimed at achieving the desired improvement.
A practical example has been given showing a new risk management system that has been designed by following the main parameters of the list and it is being used in a construction company.
Literature and practitioners claim for better and more useful tools for risk management daily practice. Companies are frequently not up-to-date with the latest methodologies and do not possess the skills necessary to apply them. For that reason, practitioners ask for simple and effective solutions. This article presents improvement drivers to succeed in developing new risk management solutions that meet practitioners' needs.