Data: A powerful tool for managing risk
06/10/2025
Clare Munro in our Specialty Lines claims team looks at how data is a powerful tool for managing risk with our colleague, Martin Clemmit, in Zurich Resilience Solutions.
In case you missed it, we looked at the importance of organisational values and behaviours and their impact on risk culture which you can read here.
In today's dynamic and often unpredictable business landscape, risk is an ever-present factor. From supply chain disruptions and economic downturns to evolving customer preferences and cybersecurity threats, organisations face a multitude of challenges and potential pitfalls. Navigating this complex terrain effectively requires more than just intuition or reactive measures. It demands a proactive, informed approach, and at the heart of this lies the strategic utilisation of data.
With the exponential growth of data and the sophisticated tools available to analyse it, organisations that embrace data-driven risk management can gain a significant competitive edge, enabling them not only to mitigate potential threats but also to identify and capitalise on emerging opportunities.
How can data help manage risk?
In its simplest form, data refers to raw, unprocessed facts, figures, observations, or measurements. When this raw data is collected, organized, analysed, and interpreted, it transforms into information and ultimately knowledge, which can then be used to make informed decisions about managing risk. Organisations can draw on a multitude of internal and external data sources, stored on the organisation’s premises or in the cloud, which, when analysed, allow an organisation to make data driven decisions. For example:.
Operational Data: Information from manufacturing processes, supply chain logistics, inventory management systems, sales and equipment maintenance logs. This can highlight potential bottlenecks, quality control issues, and asset reliability risks and, when properly analysed, might help inform decisions around prevention and mitigation of claims by third parties.
Human Resources Data: Employee turnover rates, absenteeism, training records, and employee satisfaction surveys. This can indicate risks related to talent management, skills gaps, and organisational culture and, when properly analysed, might help avoid employee fraud or a claim in negligence.
Customer Relationship Management Data: Records of customer interactions, feedback, support tickets, and purchase history. This can help identify customer dissatisfaction, potential churn, and reputational risks.
Social Media Data: Publicly available data from social media platforms, forums, and review sites. This can reveal brand sentiment, emerging trends, and potential reputational risks.
Supplier and Partner Data: Information on the financial health, operational stability, and compliance records of key suppliers and partners. This helps assess supply chain risks and, when properly analysed, might help avoid potential regulatory breaches or mitigate the fall out of any potential business interruption.
Data doesn't just help in identifying and assessing risks; it also plays a vital role in developing and implementing effective mitigation strategies. This will include the creation of proactive response plans based on potential risk scenarios identified through data analysis, allowing for swift and effective action when disruptive events occur, such as, the insolvency of a critical supplier.
Avoiding pitfalls
Whilst data is a powerful risk management tool, it is vitally important to be aware of potential pitfalls that can undermine the effectiveness of data in risk management. Incomplete, inaccurate and outdated data can all result in flawed analysis, inaccurate predictions and misguided decisions. Therefore, whilst recognising the huge value data plays in the decision-making process, it is equally important to have systems and processes in place which ensure that data driven decisions are based on ‘good’ data, in particular, data which is accurate, complete, valid and consistent. This includes:.
Establishing Data Governance Frameworks: Ensuring accountability for data quality throughout its lifecycle, from creation to deletion.
Developing Data Literacy: Equipping employees with the skills and knowledge to understand, manage and interpret data effectively.
Fostering Collaboration: Encouraging collaboration between different departments to share data and insights related to potential risks
Promoting a Culture of Continuous Improvement: Regularly reviewing and refining processes based on data-driven insights.
Human oversight plays a key role in determining whether the data is ‘good’. If the data set does not ‘look right’, organisations should interrogate the data further. The data may not be accurate and reflect reality. Therefore, it is important to ask where the data comes from, or the data may not match other data sources. It is important to check that the data is consistent. Being curious is important. If the data quality is high, then organisations are more likely to get trustworthy predictions and informative summary values.
Using technology
Organisations typically have access to office software which provides a platform to both manage and analyse data which combined with their familiarity, accessibility and versatility make them powerful assets in creating insight from data. The sheer pace of change in data analytics can make choosing the right software daunting to the uninitiated but, an application such as, Microsoft Excel offers many powerful functions for collecting and analysing data which enables organisations to do so much in the workplace and much more efficiently, such as, data entry, data summarising and automation. Organisations can get answers from their data by using a pivot table to summarise the data and can share a message to internal or external stakeholders by creating a powerful visualisation. Applications such as Microsoft Power BI create more opportunities to connect with a wide range of data sources and perform advanced analytics. If your organisation has these tools, we recommend that you explore their capabilities and see what can be achieved.
Conclusion
In an increasingly complex and volatile world, organisations that do not embrace the power of data in managing risk will be at a significant disadvantage. By leveraging data to identify, assess, mitigate, and respond to risks effectively, organisations can build resilience, protect their assets, and ultimately achieve sustainable growth.
If you would like to discuss in more detail the contents of this piece, please contact our Specialty Claims Team or if you would like to hear how Zurich Resilience Solutions can support you, please contact the Risk and Resilience Team who would be delighted to hear from you.
