In today’s dynamic business environment, the survival and success of companies often depend on various forms of innovation. Some innovations may be improvements to existing products/services (incremental innovation), while others may be novel products/services or major technological breakthroughs (radical innovation). These innovations can be encouraged and/or facilitated by appropriate performance measurement systems. For example, Amazon is known for using real-time data generated from automated algorithm-driven systems to manage and enhance productivity in its warehouses. Streaming services such as Netflix rely on streaming metrics to help them gain more insights into consumer demand and engagement.


But while greater and better use of performance metrics may help enhance innovation by offering valuable feedback and guidance to managers, inappropriate use of metrics can cause problems. For example, the focus on efficiency metrics may inadvertently discourage creativity and innovation and damage organizational culture, particularly when those metrics are linked to monetary or nonmonetary rewards, as they usually are.


To explore this topic, we conducted a study of small and medium-sized organizations (SMEs) to better understand both the extent to which managers of SMEs rely on formal performance metrics to run their businesses and the extent to which the metrics used serve the creativity and innovation needs of these organizations.


Our Study and Findings


In our research (Metric Intensity and Innovation Dependency, Contemporary Accounting Research, January 2023), we recognized that not all businesses have the same innovation priorities. We distinguished between the two main types of innovation—incremental and radical. Our study focused on whether and how a company’s metric intensity (i.e., the quantity, frequency, and extent to which performance metrics are tracked and used) varies with the type of innovation dependency.


To answer our research question, we used data from one of the largest peer-mentoring organizations in the United States for top executives of SMEs. The main data came from a survey on innovation and performance management administered by the organization in 2018. We also collected anonymous responses from 266 U.S.-based SMEs. The responding companies are mostly private and from a broad range of industries with a median annual revenue of $10 million to $20 million. Using these survey responses, we constructed two main measures of innovation dependency (i.e., the degree of dependency on incremental innovation and that on radical innovation) as well as our measure of metric intensity.


Before we conducted the study, we expected that the type of innovation that’s crucial to a company’s survival and success has a significant impact on its ability to quantify work, and that it also shapes how managers perceive the benefits and costs of employing formal metrics. Consequently, we believed that innovation needs play an important role in determining how intensively a company uses performance metrics. Our results are consistent with our predictions: Companies relying more on incremental innovation tend to have higher metric intensity, whereas those depending more on radical innovation exhibit a lower level of metric intensity.


With incremental innovation, advancements in products, services, or processes often build upon existing ones and follow predictable improvement processes. Organizations and managers have already accumulated a wealth of related technical and market information from various internal and external sources, making reliable performance metrics and benchmarks readily available. In addition, incremental improvements typically require swift and targeted problem solving. Use of quantified metrics can provide timely insights and actionable guidance to facilitate the incremental innovation process. Hence, managers of companies that depend more on incremental innovation are likely to perceive greater benefits from the intensive use of metrics and find it easier to integrate the quantification of work into their business management practices.


If a company’s survival and success depend more on radical innovation, however, unforeseen challenges and undefined questions or concepts are more common. There are fewer quantitative metrics available for the evaluation of radical innovation activities. Since radical innovation usually involves risky long-term processes with uncertain outcomes, short-term metrics may not be reliable leading indicators for successful innovation outcomes and may even narrow the creative open-thinking process essential for radical innovation. Metrics that are linked to monetary rewards may also stifle employees’ intrinsic motivation. As a result, managers of companies that depend more on radical innovation are more worried about the adverse effects of metrics on innovation and are less likely to adopt intensive metric usage.


Culture or shared values can play a critical role in an organization when processes are difficult to measure and outputs are uncertain. We further explored whether organizational culture reinforces or diminishes the relationship between innovation dependency and metric intensity. Our findings indicate that the positive relationship between metric intensity and the dependency on incremental innovation is strengthened when the organizational culture emphasizes greater “control” values, such as accountability, precision, or consistency.


On the other hand, the negative relationship between metric intensity and the dependency on radical innovation is mitigated when the organizational culture emphasizes greater “flexibility” values, such as loose monitoring or high error tolerance. This suggests that cultures that allow employees to have more flexibility may improve the perceived benefits of using performance metrics, enabling greater use of metrics in companies relying more on radical innovation. The results also emphasize the role of organizational culture as an important contextual factor that can affect how managers use performance metrics and what effects are realized from those uses.


Finally, as we delved into the purpose of performance metrics, we found that greater use of metrics for decision-facilitating purposes—such as operational planning, strategy communication, progress monitoring, and learning from performance feedback—can weaken the negative relationship between metric intensity and dependency on radical innovation. This effect is also likely due to an increase of perceived benefits of using performance metrics when they’re used more for decision-facilitating purposes rather than for decision-influencing (incentive) purposes.




Performance measurement, or technology-enabled quantification of work, provides useful tools for assessing performance and providing guidance. However, we observed that companies of similar sizes in the same industry and at similar stages in the life cycle use metrics to different extents, suggesting that they have very different preferences over the degree of quantification and the use of those performance metrics.


Our study aimed to uncover a key factor that influences companies’ tendency to “manage by numbers”—that is, the type of innovation they depend on for survival and success (incremental and/or radical innovation). We provide evidence showing that metric intensity in an organization is determined by the type of innovation dependency. Additionally, culture, or the shared values and behavioral norms in an organization, can impact the relationship between innovation dependency and metric intensity. A culture that promotes “flexibility” (e.g., high error tolerance) could help facilitate the use of performance metrics in organizations depending on radical innovation. 


Our findings highlight the complexity and intricacy of designing performance measurement systems. Managers can gain a clearer understanding that there’s no one-size-fits-all approach that suits all organizations. Design choices related to metric intensity are influenced by various company-level contextual factors. In particular, our study suggests that metrics and their use need to be aligned with a company’s innovation dependency, which reflects the company’s competitive environment and strategy.


When managers are designing or redesigning a performance measurement system, they need to carefully consider the type of innovation their company depends on, as distinct innovation processes require different approaches to utilizing metrics. Moreover, during major shifts in the competitive environment or business models, which may potentially demand changes in the type of a business’s innovation dependency, adjustments to the use of performance metrics become especially crucial to effectively align with and support evolving strategic priorities.

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