Introduction
Many organizations have recognized the need for Enterprise Risk Management (ERM) as an essential management tool used in creating value and continuously sustaining business processes. Risk management practices are prone to frequent evaluations to ensure that they remain effective with the advancing level of technology (He, & Lu, 2018). Risk management is enhanced by the application of software tools to ease workflow processes through data manipulation.
Software selection for evaluation
Business Intelligence has given the business a deeper understanding of the business environment by analyzing the risks that affect the organization from the internal and external environment. This application analyses big data through various data analysis techniques and give managers a better insight based on human resource management, sales, production and finance (He, & Lu, 2018). The major role that has been played by software and technology is the management of the information supply chain, assimilation, and conversion into meaningful details. This means that this system controls the collection, storage, recording, analysis and transfer from one point to the other.
This technology has facilitated the transfer of information easily and in a reliable manner to the managerial time when they need it to make important business decisions. Risk management software is designed to track and manage critical risks affecting the business in different areas such as finance and legal compliance. The three major risk management software includes; Qualys, Resolver, and CURA.
Review of the selected software
Qualys
This tool is most appropriate when dealing with different projects with different timelines to counter various vulnerability. This software is made up of a set of security solutions such as IT security, Web app, cloud security access, asset management and policy compliance (Wynn, Turner, Grube & Irizar, 2019). It has a high efficacy of vulnerability scanning, remediation tracking, and malware detection.
Resolver
This is the major tool used in constructive planning and preparation to prevent the sudden eruption of a risk that is hard to manage, resulting in the jeopardization of the project. Resolver supports risk identification in the early stages of the project development where the regulatory requirements are yet to be met. This software is utilized with differently sized organizations for effective assessment and provision of customized reports. The major advantage of using this tool is that it offers products that are specific to the organization.
CURA
CURA is a risk management tool that provides services of continuous monitoring of risks that hide or recur. The software works to supervise each risk to ensure that the probability and impact are in check (Kliem & Ludin, 2019). Industries using this software include banks, telecommunication and utility firms, healthcare, insurance, and other firms that deal with incident risk management. Many organizations around the world including Kellogg rely on CURA to manage risks and the provision of reliable expertise solutions.
Criteria for evaluation
Risk identification
This is a commonly used criterion that enables users to identify software that can offer regulatory requirements of the project as well as identify probable risks before they occur (Kliem & Ludin, 2019). In the case of financial management, a suitable risk management software should be able to determine the fall out of a project budget to allow users to sort and control unnecessary expenses using simple editing options.
Time management
When selecting the software for risk management, it is important to consider whether it contains features that are responsible for time tracking to enable the users to complete tasks on the required deadlines. These features include due date options, weekly summary, and instant alerts to monitor time spending on particular tasks (Leite, Pedrosa, & Bernardino, 2018). This feature ensures that the project does not fail to deliver the set targets as it keeps reminding the users of the used and remaining time.
Risk impact assessment
Risks can be unpredictable but a quality risk management software should assess the impact that an identified risk can cause to a department (Sangaiah, Samuel, Li, Abdel-Basset & Wang, 2018). Through these criteria of assessing the severity of the risks, the project stability is assured to remain intact as the management deals with the most urgent risks.
The software is more suitable if it can enable the formulation of reports in the form of graphs, tables or lists as facilitated by the program dashboard. These reports can easily be transferred to a third party through email in the form of PDF, spreadsheets or word documents s(Kliem & Ludin, 2019). This feature is useful in the provision of fast and reliable information to the team members when the need arises. This feature is also be enhanced by specificity, where each risk is aligned to a specific risk owner who is accountable for resolving the issue.
Weighting criteria
This is a method of evaluating the criteria used in software selection to rank the software to their importance in decision making (Wu, Zhu, Wan, Bao & Li, 2019). Different methods are used to score using a numerical scoring method and spreadsheet tools. Scoring is usually done using numerical digits with different meanings as understood by the evaluators.
In this case, the scores range from 1-5 with the following meaning;
Score 1- not important
Score 2- poor enhancement
Score 3- suitable implementation
Score 4- good
Score 5- Excellent
Evaluation matrix
An evaluation matrix is a tool used to evaluate a list of potentials software options against a list of factors of different weights (Thuong, Zhang, Li, & Hong, 2018). This matrix helps to determine the importance of the selected criteria scoring each option against each criterion as shown in the table below;
| Criteria | Rating scores |
| Risk identification | 4 |
| Time management | 5 |
| Risk impact assessment | 3 |
| Risk reporting | 5 |
When different evaluators score against the criteria, an objective discussion is formed against the criteria, to sort the different views. For example;
|
Criteria |
Rating scores | ||
| Candidate A | Candidate B | Candidate C | |
| Risk identification | 4 | 2 | 3 |
| Time management | 5 | 5 | 5 |
| Risk impact assessment | 3 | 3 | 2 |
| Risk reporting | 5 | 4 | 3 |
The final step is to multiply the candidate scores against the weightings of each criterion as shown in the table below;
| Criteria | Rating | Candidate A | Candidate B | Candidate C |
| Risk identification | 4 | 16 | 8 | 12 |
| Time management | 5 | 25 | 25 | 25 |
| Risk impact assessment | 3 | 9 | 9 | 6 |
| Risk reporting | 5 | 25 | 20 | 1 |
In the table above table, candidate C, for example, gets a 12 in risk identification (4 multiplied by 3) where 4 is the weighting of the criteria while 3 is the candidate’s score.
Justification of the weighting criteria
The 25 rating of time management criteria is interesting as it shows a common view among the candidates who must have come from different cultures, background and have different maturity levels. This means that there are key differences between the candidates (evaluators) but one criterion still stood out as an excellent method for software evaluation. A software that cannot track time adds no value to a risk management project
References
Kliem, R. L., & Ludin, I. S. (2019). Reducing project risk. Routledge.
Wu, D., Zhu, X., Wan, J., Bao, C., & Li, J. (2019). A Multi-objective Optimization Approach for Selecting Risk Response Strategies of Software Project: From the Perspective of Risk Correlations. International Journal of Information Technology and Decision Making, 18(1), 339-364.
Sangaiah, A. K., Samuel, O. W., Li, X., Abdel-Basset, M., & Wang, H. (2018). Towards an efficient risk assessment in software projects–Fuzzy reinforcement paradigm. Computers & Electrical Engineering, 71, 833-846.
Thuong, N. T. H., Zhang, R., Li, Z., & Hong, P. T. D. (2018). Multi-criteria evaluation of financial statement quality based on hesitant fuzzy judgments with assessing attitude. International Journal of Management Science and Engineering Management, 13(4), 254- 264.
Wynn, M. G., Turner, P., Grube, M., & Irizar, J. (2019). New technology deployment in SMEs: towards a process-based approach.
Leite, N., Pedrosa, I., & Bernardino, J. (2018, June). Comparative evaluation of open source business intelligence platforms for SMEs. In 2018 13th Iberian Conference on Information Systems and Technologies (CISTI) (pp. 1-6). IEEE.
He, C., & Lu, K. (2018). Risk management in SMEs with financial and non-financial indicators using business intelligence methods. Management, 16, 18.
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