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Managing risk in a volatile business environment: The role of integrated risk quantification

Managing challenges requires identifying and addressing your vulnerabilities to build a more resilient organisation. Find out how integrated risk quantification can help.

Uncertainty has become a persistent feature of business operations globally – affecting all industries. The challenges posed by geopolitical risks, market fluctuations, regulatory requirements, and environmental and sustainability expectations, make managing uncertainty a critical task for organisations. Emerging and evolving challenges require identifying and addressing specific vulnerabilities to build resilience into your organisation.

Integrated risk quantification (IRQ)

An IRQ model is a risk quantification tool that aligns with the business structure and is informed by the forward-looking financial and operational plans. IRQ enables businesses to evaluate the impact of risks to their organisation via various financial metrics simultaneously.

Amidst ongoing external challenges and evolving stakeholders demands, traditional enterprise risk management (ERM) may face limitations in fully assessing uncertainty. While heatmaps or risk matrices still serve a purpose, they offer a simplistic representation of risk exposure – failing to capture how risks may be interconnected or how they impact various financial and operational objectives.

However, embracing risk quantification and stochastic modelling can enable organisations to gain a comprehensive understanding of their entire risk landscape. The main elements of an IRQ-based approach, include:

  • The dynamic baseline, with interdependencies created between the income statement, cash flow statement, and balance sheet, provides a comprehensive view of the effect of key risks on the major financial ratios and key performance indicators.
  • Income Statement elements, in turn, are based on the corresponding operational plans, enabling businesses to breakdown revenue and costs into business segments and/or products. Representing the value chain in such a way enables attainment of the required level of granularity.
  • Each risk is then assessed, based on the combination of stakeholder inputs, industry benchmarking data, macroeconomic and market trends, and other available risk-specific information. ERM data, enriched through comprehensive risk interviews conducted with subject-matter experts and subsequently detailed using the bowtie or similar methodologies, can also be effectively utilised.
  • Risk portfolio analysis serves as an additional perspective when scrutinising different outlooks of the future, specifically in the context of forward-looking financial and operational performance.
  • Risks interconnectivity is also incorporated into the model and correlations are added, where applicable. Risks are rarely considered to be isolated events, as they tend to move together. For example, different macroeconomic variables and stochastic pathways from adjacent years.

Benefits of IRQ

Risk-based planning models provide a more realistic understanding of risk exposure – crucial for developing comprehensive and informed response and risk management strategies. Organisations that will benefit from using a risk-based planning approach vary in terms of size and industry. Full-scale IRQ would be useful for large companies with robust risk management approaches in place. Businesses must be willing to comprehensively evaluate the impacts of wide-scale challenges like macroeconomic, geopolitical, or commodity prices risks, as well as, more specific operational and financial risks.

More specific benefits of IRQ, as well as, wider stress testing, include:

  • Comprehensive risk exposure evaluation: Isolated and single-dimensional risk quantification, such as losses in terms of only (unspecified) costs, may fail to provide a thorough view on risk and what it actually means for businesses. Losses can be expressed in a variety of metrics – loss of a revenue opportunity, decrease in a market share, increase in cost of goods sold, operating expenses or interest, capital expenditure, or additional liabilities. With a dynamic baseline – where interconnectivity was established between the financial statements trio – any modelled risk can be expressed via multiple financial metrics, such as revenue, debt/equity ratio, or earnings before interest, taxes, depreciations, and amortisation.
  • Improved operational efficiency: IRQ allows identification of bottlenecks and areas for improvement in the financial and operational plans before their approval by internal and/or external stakeholders. This can provide opportunities to introduce potential amendments and improve the probability of reaching the targets.
  • Informed capital planning: IRQ modelling effectively determines the adequacy of capital buffers and prioritises capital allocation to ensure that sufficient resources are planned to manage and mitigate risks effectively.
  • Enhanced business continuity: Simulation of shocks and extreme scenarios such as natural disasters, labour strikes, or geopolitical risks enables organisations to understand the potential consequences of different risk events and develop appropriate strategies to mitigate them. Ongoing monitoring – by regularly updating and refining risk models based on new data, inputs, or changing circumstances – helps maintain the readiness level and adequate responsiveness to potential disruptions.

Common barriers to effective IRQ

There are various challenges faced during the development of risk-based planning models. These issues, common to all model-informed solutions, include:

  • Data and assumptions: Accurate reliable data, such as detailed financials, historical data, and risk incidents information, may not be readily available or accessible. Quality inputs lead to quality outputs – ensuring the model’s reliability.
  • Stakeholder engagement: Multiple stakeholder departments are usually involved in various capacity in the IRQ development and availability of all colleagues may be limited due to ongoing operational tasks. Advanced planning and proactive engagement are highly recommended, ensuring that the benefits of IRQ for each concerned department are clearly and explicitly articulated and discussed.
  • Longevity and incorporation into business-as-usual processes: The development of IRQ requires specialist knowledge on risk management and financial planning. It is essential that detailed training is available to ensure clarity on IRQ’s structure, operational characteristics, interpreting outputs, and process of updating inputs.

Conclusion

An IRQ approach goes beyond static financial forecasting – where metrics are defined by a single number – to provide a more comprehensive understanding of uncertainty. By challenging the viability of financial forecasts regarding the risk landscape that the business is facing, the risk-based model enhances the strategic planning approach – including prioritisation of risk mitigation solutions and associated budgets.