How to Choose between Qualitative and Quantitative Risk Assessments in Cyber Security for SMEs?

Risk assessment is a key part of assessing potential risks to an organization’s assets and operations. It involves identifying risks, evaluating their likelihood, and assessing their potential impact on the business. Risk assessments are helpful in scenarios such as the emergence of new threats (e.g., cyber-attacks), significant changes in operations (like mergers or acquisitions), or when implementing new technologies. For Small and Medium-sized Enterprises (SMEs), the challenge often lies in understanding the different risk assessments and knowing how to apply them effectively with limited resources.

There are two main types of risk assessments: qualitative, which relies on subjective judgement (based on opinions and experiences), and quantitative, which uses numerical data and statistical models. Both assessments have their strengths, but the right choice depends on the SME’s needs, available data, and resources.

This blog will help SMEs understand the differences between these assessments and guide them in selecting the most effective assessment for their business.

What is Qualitative Risk Assessment?

In qualitative risk assessment, risks are identified and evaluated based on opinions and experiences rather than precise, measurable data. It typically categorizes risks as low, medium, or high based on their likelihood of occurring and the potential impact they may have on an organization.

When is it Best Used?

Qualitative risk assessment is useful when measurable data, such as financial records (e.g., revenue or cost breakdowns), is unavailable. It is also helpful when quick decisions need to be made or when the risks are hard to measure. This approach is a good option when precise numbers are difficult to obtain and when a simpler, faster assessment is needed. It is especially useful for assessing risks based on personal judgment, such as reputational damage from a security incident.

For example, a small marketing agency is concerned about the risk of a security breach that could lead to the loss of sensitive client data. The team gathers to discuss this risk. The agency currently has no cyber security measures in place. Additionally, a breach has occurred 5 times in the past year. As a result, they rate the likelihood of a breach as “high.” The potential impact is also rated “high.” A breach could lead to the loss of client trust, legal consequences, and reputational damage.

Qualitative risk assessment relies heavily on personal opinions, experiences, and judgment. This means that different individuals may assess the same risk in different ways based on their own perspectives or past experiences. For example, one team member might view a potential security breach as a high risk, while another might see it as a low risk, depending on their level of experience with similar incidents.

This variability can lead to inconsistent results, where different risk assessments of the same issue might produce conflicting outcomes. To address this issue, organizations can create standardized risk management procedures with clear guidelines and criteria. This helps ensure a consistent and unbiased risk assessment, helping all team members consider the same factors for more uniform decisions.

What is Quantitative Risk Assessment?

Quantitative risk assessment uses numerical data, metrics, and statistical models to evaluate and measure risks. By applying mathematical techniques, such as probability models (which help calculate how likely something is to happen) and historical data (including past performance, incident records, and failure rates). It provides precise numerical values to represent the likelihood and impact of potential risks.

When is it Best Used?

Quantitative risk assessment is most effective when measurable and reliable data is available. This data could include past performance records or incident history, which allows for precise calculations of risk likelihood and impact. It is especially useful when specific measurements are needed, such as estimating financial losses or assessing safety hazards. This approach is also crucial for high-value or high-risk projects. In industries like oil & gas, accurate risk measurement is vital due to the significant risks and costs involved.

For example, a small manufacturing company wants to assess the risk of equipment failure and its potential impact on production. The company collects historical data on machine breakdowns over the past year, including the frequency of failures and the cost of repairs. Using this data, they calculate the average downtime per month, the cost of repairs, and the potential revenue loss due to production delays. They can use a simple 1-2-3 scale to rate each factor: 1 for low risk, 2 for medium risk, and 3 for high risk, helping them make informed decisions about maintenance or replacement.

Quantitative risk assessment can be resource-intensive and time-consuming. It requires large amounts of measurable data and specialized knowledge to analyze. For example, if a company is assessing the risk of equipment failure in a factory, they would need detailed data on failure rates, maintenance history, and operational performance. Gathering and analyzing this data can take a significant amount of time. It also requires technical expertise. Organizations without the right infrastructure or expertise to handle complex data might struggle with quantitative assessments.

Choosing the Right Approach for an SME

When selecting a risk assessment, businesses should consider factors such as size, available resources, and the complexity of risks:

• Business Size and Resources: The resources available to a business will influence the choice of risk assessment. An assessment that requires fewer resources might be more suitable for businesses with limited budgets and staff.
  Example: A small retail shop with a limited budget might opt for a simple qualitative risk assessment to evaluate risks like supply chain disruptions. On the other hand, a larger corporation with more resources might choose a quantitative assessment to analyze detailed risks such as market fluctuations or financial downturns.
• Data Availability: The availability of data plays a significant role in risk assessments. Some require detailed, specific measurable data, while others can be based on expert opinions or general information.
  Example: A small online clothing retailer may have insufficient measurable sales data. As a result, they might rely on expert opinions or general industry knowledge to assess the risk of fluctuating demand during seasonal sales. This approach doesn’t use data-driven methods. In contrast, a large retail chain has years of sales history. With this data, they can use quantitative analysis to predict demand. This helps them identify the risks of inventory shortages or overstocking during peak seasons.
• Risk Complexity: The nature of the risks also matters. Some risks are easier to evaluate based on expert judgment, while others need detailed calculations and models to understand the potential impact.
  Example: A small e-commerce business might evaluate the risk of website downtime using a simple qualitative assessment. They would rely on past experiences and expert advice to make this evaluation. However, a large e-commerce retailer with a complex IT infrastructure would need a more complex approach. They would perform a quantitative risk analysis, assessing factors like server uptime, historical system failures, and the potential financial impact of downtime across their global customer base.

In conclusion, the choice of risk assessment depends on factors such as the availability of data, resources, and the complexity of the risks faced. Each assessment has its strengths, and it’s important to consider these factors when selecting the most appropriate approach for their business needs.