Enhance business opportunities and reduce threats
Discover how your data can drive more effective risk management strategies for your organisation.
Data and Risk Management
Identifying, assessing and reducing risks
Risk management allows you to take advantage of strategic opportunities available to your organisation and reduce any possibilities of project failure. However, without timely and reliable data, risk management is unable to effectively manage uncertainties and support top-management decision-making.
- Establish the right measurement parameters to examine likely scenarios
- Better understand the potential impact of an internal or external risk
- Assess risks across your organisation and decide which one to manage and prioritise.
But how can you ensure that your organisation truly benefits from the role of data in risk management?
Enabling you to action quickly
Any collected data has little impact if it’s not readily available to the people who need it. Data held in silos prevents you from seeing the bigger picture and leads to impaired decision-making.
Data silos happen when relevant pieces of information are inaccessible or only made available to a few people. We’ve seen this happen in organisations where there are high barriers between individual departments or between senior leadership and other management teams.
When there’s a lack of data accessibility, reliable assessment of risk is compromised affecting your organisation’s future performance or profitability. Data silos could also cause you to look at a risk in isolation. This leads to:
- Poor understanding of how risks interact with one another.
- Duplication of risk mitigation efforts.
- Inability to create an effective unified risk management strategy that encompasses different parts of your organisation.
An accessible, discoverable and reusable data drives a more proactive risk management. You can spot potential risks and gain insights earlier, resulting in the development of strategic actions, instead of reactive solutions after the fact.
Building and maintaining an effective risk management strategy
Data is only useful if you’re able to convert it into valuable insights to guide your business decisions. This is where the critical role of a coherent data strategy comes into play.
Data strategy gives you the vision, principles, and the roadmap for successful data management and analytics. It allows you to understand the technologies and processes needed to ensure your data is always accessible, shareable and of high quality. (Learn more about the basic foundations of a data strategy and how to develop it here.)
Developing your data strategy enables you to develop your risk management capabilities as well. Reliable data supports true and accurate risk identification. While a robust data system with powerful analytical and reporting solutions supports a more detailed and targeted risk analysis and monitoring.
How data is used to drive risk management programs
Many organisations have seen the benefits of applying their data to enhance their assessment of emerging risks. They have implemented data strategies that let them approach risk in a proactive and profitable manner.
In the environment sector, organisations use data to identify and prioritise a range of risks in communities, infrastructure and natural environments. For example, CoastAdapt uses data visualisation to understand the risks coastal hazards may pose to coastal communities.
Sustainability Victoria meanwhile uses data analytics to understand current and future waste amounts in Victoria’s hazardous waste system. The insights they gain allows them to accurately and quickly determine the required investment, strategic development and infrastructure requirements for the management of hazardous waste in the State.
Enhance your risk management strategy with data analytics
Your data is one of your most valuable assets. With accurate data, you have the ability to develop a system that enables rapid response and decision making that reduces business risks. Connect with our data experts today to learn how you can better apply your data to your decision-making processes.