Why “Good” Doesn’t Mean Anything Anymore

Benchmarking has long been treated as a cornerstone of good decision-making in hiring. It offers a sense of objectivity in what can otherwise be a subjective process, giving businesses a way to measure candidates, salaries, and performance against a wider market. On the surface, it provides reassurance: a feeling that you are making informed, competitive choices.

However, from a recruitment perspective, benchmarking is often far less reliable than it appears. The issue is not with benchmarking itself, but with how it is commonly applied—flattened, decontextualised, and overly dependent on comparison rather than understanding.

In practice, what many businesses refer to as “benchmarking” is simply pattern-matching. They look for candidates who have worked at similar companies, delivered against familiar metrics, or operated within recognisable environments. While this can create a sense of alignment, it rarely interrogates whether those experiences genuinely translate into the context of the hiring business. This is where the limitations begin to surface.

Performance metrics, which are often used as the backbone of benchmarking, do not exist independently of the environments in which they are achieved. A strong return on ad spend, an efficient customer acquisition cost, or a high revenue per employee can only be properly understood when viewed alongside the business model, growth stage, margin structure, and strategic priorities of the organisation.

For example, a candidate who has delivered exceptional growth within a well-funded, high-burn eCommerce business may have done so under conditions that are fundamentally different from those of a more capital-efficient or operationally constrained company. The same metric, viewed in isolation, may appear impressive, but without context it offers little insight into how that individual will perform elsewhere.

This challenge becomes even more complex when businesses attempt to benchmark across industries. While there is value in learning from different sectors, the metrics that define success in one industry are rarely directly comparable to those in another. A recruitment firm, for instance, will focus on placement ratios and revenue per consultant, while a marketing agency may prioritise utilisation rates and client retention. A logistics operator, by contrast, is more likely to measure performance through cost efficiency and delivery accuracy.

Each of these metrics reflects the commercial realities of the business in question. Attempting to standardise them into a single benchmarking framework risks oversimplifying the very factors that drive performance.

What is required instead is a more nuanced approach—one that moves beyond comparison and towards interpretation. Rather than asking how a candidate performs against an industry average, businesses need to understand how that performance was achieved, under what conditions, and whether those conditions bear any resemblance to their own.

This shift has important implications for hiring.

When benchmarking is approached in a more contextual and deliberate way, it allows for a broader and more relevant talent pool. Candidates from adjacent industries or different business models can be properly evaluated based on the substance of their experience, rather than dismissed due to superficial differences. This not only improves the quality of hire but also supports more accurate salary benchmarking, as compensation can be aligned with actual value creation rather than generic market positioning.

From a recruitment standpoint, this represents an evolution in the role itself. The value of a recruiter is no longer defined solely by access to candidates, but by the ability to interpret and translate experience across different contexts. This involves understanding the commercial drivers behind performance, recognising the constraints within which candidates have operated, and identifying where genuine alignment exists.

Encouragingly, there are signs that this more practical form of benchmarking is beginning to take shape. As businesses gain access to richer data and more transparent market insights, there is a growing opportunity to build benchmarking frameworks that are grounded in real-world performance rather than abstract averages.

Ultimately, benchmarking remains a valuable tool, but only when it is used with care. It should not be treated as a definitive measure of quality, nor as a shortcut to decision-making. Instead, it should act as a starting point for deeper analysis—one that recognises the complexity of performance and the importance of context.

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