Not all risk management processes are created equal.
Coffee company Kopi Kenangan, for example, faced high risks related to poor hiring decisions and overspending, especially as the company grew its online retail division. Scattered data sources made it impossible for company leaders to make decisions that were both quick and effective at mitigating those risks. The answer was a business intelligence solution that is fueled by real-time analytics and equips executives with the information they need to make data-driven decisions. This solution has streamlined processes, reduced costs, and automated the matching of applicants to open positions. In other words, the solution has not only improved the company culture, but has mitigated multiple, significant risks.
Business intelligence tools are a critical part of managing modern businesses’ risks. Not only are companies that leverage business intelligence five times more likely to make intelligent decisions faster than those that do not, but companies with CEOs who make data-driven decisions are 77 percent more likely to succeed than companies with CEOs who do not.
Business intelligence tools can improve risk management processes in several key ways. For example, some of the primary challenges to effective risk management include failing to use accurate risk metrics, assessing risks incorrectly, and poor communication of identified risks. Business intelligence can address each of these components of risk management by identifying key data sources, providing valuable data analytics, and creating visualizations that communicate identified risks clearly.
Failure to implement a data-driven risk management process can lead to low employee morale, customer atrophy, financial losses, or even regulatory action. As businesses leverage BI tools in each stage of their risk management processes, they can reduce the chances of those negative outcomes and better manage the risk their companies face.
Consider how successful companies have effectively used business intelligence solutions in the four stages of risk management: risk identification, risk assessment, risk treatment, and risk monitoring and reporting.
Without related data, risk identification ends up becoming a largely subjective task. Business leaders may discuss a project or product and identify the lessons they have learned, what they felt worked well and what did not, and what constraints they experienced. While these valuable conversations can lead to important revelations, they are also limited without the inclusion of hard data.
With business intelligence tools, companies can strengthen their risk identification processes through data analytics. Take the Bank of India, for example. As a fast-growing enterprise, the Bank of India wanted to spend its capital on developments like new products and services to offer to customers. Instead, they found themselves needing to hire more staff members who could identify and manage operational risk manually.
Bank of India decided to try a SAS business intelligence solution that would free them from unnecessary staffing, eliminate their dependence on spreadsheets, and improve their capacity for identifying risk. Rather than needing individuals to check in with their 4,892 branches, the Bank of India now collects loss data directly via technology. They also receive key risk indicators from the banks through an automated process, which strengthens the bank’s risk identification measures.
The bank’s business intelligence tool reduced risk in and of itself by eliminating the need for overstaffing and decreasing the risk of human error in manual risk management. And when it specifically comes to risk identification, data sources — such as the automatically reported key risk indicators — improve that stage of the process considerably.
One of the greatest assets of business intelligence in risk management is the ability to visualize data quickly, specifically, and on a regular basis. This is especially useful when it comes to assessing risk. Companies face a myriad number of risks each day. Some risks have a higher likelihood of occurring than others, and some risks carry the potential for more damage than others. Big data analysis and visualization made possible by business intelligence tools can help key stakeholders make data-driven decisions about which risks they should prioritize mitigating.
Mitsui Leasing, an automotive finance company, faces risks when it comes to extending credit to customers. Each customer carries a different level of risk and the company’s livelihood depends upon making wise decisions about loan applications. Determining a customer’s risk level used to take longer than the company wanted. In the case of a customer defaulting on their payments, the company lacked the infrastructure for an effective corrective action plan that could be tracked and assessed for risk itself.
The company now uses a business intelligence tool, Tableau, to assess credit risk in customers and potential customers. Assessments that used to take seven days are now instantly available. The 177 visualizations made possible by Tableau help Mitsui Leasing’s leaders and employees make quick, effective decisions when conducting a risk assessment.
Beyond identifying and assessing risk, business intelligence tools can help mitigate or eliminate risk.
One of the greatest risks to many companies in the data economy is data loss. Typically, human error leads to loss of data as employees manually work with data and may accidentally manipulate data in detrimental ways. The use of a business intelligence solution that acts as both a storage system and a suite of tools for user-friendly data manipulation and visualization mitigates this risk by reducing the amount of human error that could affect a company’s data.
For example, mattress producer Ortobom faced a high risk of data loss or compromise. The company had a high, growing volume of data to process, and the data was increasingly complex. Their IT manager was spending 40 to 80 hours per month on database management and ensuring that their data was continually backed up.
The company decided to implement Oracle business intelligence tools. Now, the backups their IT manager spent so much time conducting are performed automatically. Company leaders know that their data is safe and recoverable at all times. And the benefits don’t stop there: the company also increased the speed of its ordering processes, has greater security, and makes more effective and efficient decisions.
Risk Monitoring and Reporting
When it comes to risk monitoring and reporting, companies have long relied on manually updated spreadsheets and the occasional slide deck to display their findings. But such tools are inherently limited. They require constant manual adjustments, which uses up employee time and increases the possibility of errors in reports.
A business intelligence solution that provides data visualization tools can transform the risk monitoring and reporting process for companies. Such a solution not only helps businesses to conduct risk analysis but also empowers leaders in risk management to present their findings in ways that are palatable for key stakeholders in other departments.
Woodbridge, a global leader in integrated systems manufacturing, underwent such a transformation. As a large company with more than 7500 employees in more than 63 facilities across 21 countries, the company needed to elevate its reporting system. They were using a spreadsheet-based tool, which was time-consuming and rife with potential for errors.
The company turned to SAP App Center for a better solution. The business intelligence tools they implemented streamlined their risk management processes and automated their risk score reporting. The solution offered customizable scorecards and analytical reporting tools, as well as transparent reporting in areas like quality, hazards, and behavioral and environmental risk factors. Thanks to business intelligence, Woodbridge now has a streamlined global risk management process, higher employee morale, and maximized safety in the workplace.
Become a Data-Driven Risk Management Leader with a DBA in Business Intelligence
Do you want to become a leader in risk management who knows how to leverage business intelligence tools at every stage of risk management processes? Are you interested in data analysis, identifying key insights, and creating data visualizations that can communicate how to mitigate the potential risks a company faces? If so, the Online Doctorate of Business Administration in Business Intelligence at Marymount University will equip you with the skills and tools you need to manage risk using business intelligence throughout your professional career.
The fully online DBA in Business Intelligence features in-depth coursework in data visualization and data strategy.
For example, Using Data for Business Intelligence is a course that covers:
- The technological and management aspects of using data to support advanced decision-making.
- How to use business intelligence to optimize business operations.
- Developing a data strategy for an organization of the student’s choice.
- Building a platform to create data-driven business intelligence.
- The phases of data exploitation including collection, storage, analysis, and visualization using state-of-the-art tools.
In a course entitled Maximizing Digital Transformation, students learn:
- How to manage digital transformation efforts in business and government settings.
- The key components of business intelligence, data strategy, and business transformation.
- The relationship between technology and business.
- How to develop and implement effective digital strategies.
The online DBA in Business Intelligence is a cost-effective program that can be completed in as few as three years. Students can tailor their coursework to their professional goals with the support of experienced mentors and supportive faculty members.
Learn how you can become a BI expert with an online DBA in BI from Marymount University.