CIPS highlights that damage to brand reputation and financial loss are two major risks of failing to manage supply chain risks effectively. Legal issues such as lawsuits arise from illegal activity, which is separate from general risk exposure.

The two most important factors when assessing supply chain risks are Severity and Likelihood. These are typically measured on a scale [e.g., 1–5], with the product of the two giving a risk score.

Severity measures the potential impact on the organisation if the risk materialises. For example, supplier insolvency may severely disrupt operations.

Likelihood assesses the probability of the event occurring.

The combination of severity × likelihood determines whether a risk is low, medium, or high, and informs mitigation strategies.

Other options are less central:

Location may influence likelihood but is a sub-factor.

People involved is not a formal assessment criterion.

Cost can be a consequence but is part of severity, not a separate factor.

Using severity and likelihood ensures risks are prioritised based on both impact and probability, allowing category managers to allocate resources effectively.

[Ref: CIPS L5M6 Study Guide, p.40 – Risk assessment and mitigation protocols]

Line item details provide specific transactional information about a purchased product, such as the quantity ordered and the price paid. This information is critical for category managers who rely on spend data to analyse patterns, negotiate supplier agreements, and benchmark costs.

Other details such as functionality or components are not typically captured in line item data. These relate more to specifications and technical design documents rather than financial records.

By analysing line item data across multiple purchases, category managers can identify trends such as bulk-buying opportunities, price fluctuations, and supplier performance. It also assists in spend analysis, which is a fundamental step in category management for mapping categories and identifying cost-saving opportunities.

[Ref: CIPS L5M6 Study Guide, p.134 – Line item detail in spend analysis]

In category management, reliable decision-making depends heavily on the analysis of historical spend data. According to CIPS, the key forms of usable historical data include:

Spend analytics: consolidated information showing how much has been spent, on what items, and with which suppliers.

Line item details: transaction-level data that provides specific insight into products or services purchased.

Ledger codes: financial classifications that group expenditure for reporting and control purposes.

These data sets allow category managers to identify trends, supplier dependency, opportunities for consolidation, and potential cost savings. In contrast, inflation rates and spend forecasts are forward-looking metrics, not historical data. Using accurate historical information is critical for preparing budgets, supporting negotiations, and identifying anomalies in expenditure. Organisations that fail to utilise this data often struggle to align their category strategies with financial realities, leading to overspending or missed opportunities.

Supplier power is strong when buyers have fewer choices and suppliers have leverage. This occurs where:

No substitutes are available [A]: Buyers are locked into what suppliers provide, increasing supplier power.

Supplier’s customers are fragmented [B]: When customers are fragmented [many small buyers], they cannot collectively negotiate, so suppliers hold more power.

Forward integration is possible [D]: Suppliers can bypass buyers and sell directly to the end customer, which gives them negotiating strength.

Options C and E relate more to buyer power:

Switching costs are low [C]: This reduces supplier power as buyers can easily move.

Undifferentiated products [E]: This strengthens buyer power since products are interchangeable.

[Ref: CIPS L5M6 Study Guide, p.116 – Porter’s Five Forces model]

Pareto Analysis identifies the “vital few” issues that cause the majority of problems, usually presented as the 80/20 rule. While it is useful for prioritisation, its limitation is that it only highlights the frequency of issues and not the root causes behind them. In James’s example, identifying that “website errors” are the top cause of complaints is useful, but it doesn’t explain why the errors occur. Therefore, further investigation such as root cause analysis or process mapping is required to implement corrective action. Another limitation is that Pareto analysis is based on quantitative data only, not qualitative, meaning it cannot capture customer perceptions or subjective insights. This reinforces the need to use Pareto in conjunction with other diagnostic tools for effective problem solving. In practice, category managers must use Pareto as a screening tool to highlight priorities and then follow with more detailed analysis to ensure improvements are sustainable.

Direct costs are those directly attributable to the production of goods or services. For BikeFace, raw materials such as rubber (used in tyres) and labour (workers assembling bicycles) are direct costs because they contribute directly to finished products. By contrast, advertising spend and IT systems are indirect costs as they support operations but do not directly form part of the bicycle. Category managers must distinguish between direct and indirect costs to design effective sourcing strategies. Direct categories often warrant closer supplier collaboration and longer-term contracts due to their critical role in production.

Forecasts must be dynamic and updated when major internal or external changes occur. Losing a key customer significantly reduces demand, meaning forecasts must be lowered accordingly. Similarly, if a key supplier ceases trading, supply constraints may alter procurement strategies, requiring adjustment to supply and spend forecasts. Likewise, significant price inflation impacts both demand planning and budgeting, as organisations must reassess affordability and potentially seek alternatives. On the other hand, relocating operations or new health and safety legislation may change processes, but they do not directly influence demand, supply, or pricing forecasts. For category managers, regularly reviewing and amending forecasts ensures procurement strategies remain relevant and aligned with market realities. Without this adaptability, organisations risk supply disruptions, overestimation of needs, or financial misalignment.