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A Risk Management Software: Usefulness, Commercial, and Examples

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A Risk management software (RMS), is enterprise software that is designed to help businesses manage, and ultimately reduce the impact of risk. RMS may use data from existing operations or work on a predictive basis using future projections, to help organizations better manage and improve the quality of their data while identifying and minimizing the effect of potential risks. There are different types of RMS, all of which can be categorized depending on what criteria an organization seeks to use the software for. RMS can be broadly categorized, by the industry it can be utilized by, such as banking or energy and utilities. It can also be split into more specific categories, for example, the scope of risk covered e.g. from compliance risk (making sure the firm follows all the legislation that covers its practices), all the way to operational (e.g. system failures) or financial risk.

The usefulness of these sorts of tools in today’s working climate goes beyond ‘reducing risks’. When software is available to help an organization better manage their data, and assure both the firm and the clients of the quality of such, this lends itself to an array of benefits for the company. As previously stated, RMS can be used to keep on top of compliance with regulations that govern not only the accounting world, such as the Sarbanes-Oxley Act, or ensure successful audits (both internal and external), but also those that govern the wider world, for example, environmental compliance for things like monitoring and reporting emissions. RMS can help assess for risks normally associated from the data and identify any issues for the business. This collection of data also helps organizations with more effective and quicker decision-making, by allowing the data to be more efficiently organized and easily accessible. For example, assessing future possible outcomes is one way an organization may choose to make decisions of certain business aspects e.g. should a business expand? There are many external and uncertain factors that can intervene and affect the outcomes of business decisions like this. RMS often supports the Monte Carlo Simulation feature, which takes into account these random variables to provide a forecasting model that reflects these risks, meaning the decisions made by an organization can also reflect this risk. These improvements through RMS can lead to overall more efficient data management and improved quality of work, which will hopefully be reflected in performance and turnover. Although these benefits may not all be easily quantifiable, the costs of RMS are. Some RMS are available for free online, but for large businesses looking to assess a lot of data or have a heavy price to pay should risk turn into reality, more advanced software can be expensive. Moreover, this license may only cover a single user, and should numerous people/hardware in the organizations need to use the package, more than one license will need to be bought. Packages are regularly updated with new features that cover the ever-growing risks involved with running a business, but more often than not to access this a user would have to pay to upgrade every license they own. More than just these initial costs, when a new RMS is introduced, staff may need training to fully understand how the interface works and how to use more complicated features. It may even be found that certain members of staff can be reluctant to adapt to new ways of managing risk or sorting data, especially the older generation who may resist accepting these sorts of changes.

Two popular commercial risk management software is the ‘Risk Industrial’ and ‘Quantum XL’ packages. Risk Industrial is one of the very first RMS packages to be released online, in 1987, while Quantum XL is a newer release, 2010. Although more established, Risk comes with a hefty price tag at £2075, with upgrades only being free if you have purchased the maintenance plan at £415 per year, while Quantum XL comes in at a much lower price of £419.95 (converted from $549.99 at the current exchange rate), with upgrades being £152. These costs cover a single user perpetually, although both packages are offered with substantial discounts and benefits should multi-user licenses be purchased. The license gives the users access to a magnitude of features that can be accessed through Excel-add ins, with Quantum XL suitable with any version of Excel 2000 (SigmaZone B, 2019), while the latest version of Risk Industrial is only compatible with versions released after 2007. Both packages are suitable for a diverse range of industries, with Risk supporting clients from ‘PWC’ (accounting industry) all the way to ‘KEWPIE’, in the food safety industry. More often than not, employees tasked with using these types of packages may be handling this type of software for the first time, so ease of understanding is crucial for the RMS to be implemented successfully within an organization. Each package has its own help tools built within the software to guide new users, and offer online technical support, which can be easily accessed through their websites should users face any technical issues. Quantum XL also offer in-depth training courses, usually set over days, to get to grips with specific aspects of the software, like their ‘Design of Experiments (DOE)’ training, which teaches users how to implement Monte Carlo Simulations to help understand the outcomes and risks any future projects may hold. However, this training is not offered online, thus not accessible for everyone. Although Risk do not offer in-person training, they have help files linked to the software and available online, as well as videos and training all available online as well. The delivery choices for training that the packages choose to target different client groups, with online training potentially secluding clients who are not naturally tech-savvy, whereas face-to-face training is only available to those who have the means of attending.

Price Waterhouse Cooper (PWC) was hired by Post Danmark (Denmark’s national postal service), when the service wanted to ensure that the correct and accurate calculations, in relation to the risk undertaken by the company, were being used by insurance companies to compute the premiums offered. PWC used a model created on Risk, to input all the previous data regarding past events at Post Danmark that related to possible future risks, including instances like: accidents regarding the postmen and women, theft of mail, and also damage to any of Post Danmark’s property. A Monte Carlo Simulation was then used to take this data to show all potential future scenarios relating to possible incidents, and predict the likelihood of these events occurring. The accuracy of such results given from the Risk software meant Post Danmark could check the premiums offered by insurance companies were a true reflection of the risk Post-Danmark faced, and as a consequence, the premiums paid went down. Risk has been, and continues to be, a successful investment by PWC in helping Post Danmark. However, as far as current RMS go, a Monte Carlo Simulator is a standard feature and thus there are many RMS available that could successfully run this type of analysis. A Quantum XL license would allow for the same type of predictive simulations, but at a saving of £1,655.05 (on the basis of only a single user license being bought). With this point in mind, in spite of the fact Risk fulfilled its purpose, it could be argued that just as successful simulations could have been run with other, cheaper RMS. The price associated with Risk does give those with the license access to a lot of advanced features and as previously stated a vast amount of online help for new users. However, it’s unlikely employees working in the risk consultancy sector at PWC would need access to this extensive training, specifically in this case study. So, in this instance, I would argue that other RMS would have been able to handle this risk analysis, and have been just as successful in helping Post Danmark manage their risk and reduce premiums.  

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