Identifying quality metrics enables businesses to measure and control processes designed to make high-quality products. Measuring whether the product meets customer expectations provides a high level of understanding of the impact of quality. Framing the totality of quality in dimensions enables more accurate measurement. Accurate measurement of quality dimensions enables targeted improvements with monitored outcomes. David Garvin, writing in "The Harvard Review," describes eight quality metrics, or "dimensions," used to frame and understand the contributions of quality to customer satisfaction.
Performance metrics measure a product’s main operational characteristics. Performance traits typically include observable attributes, including time, speed, event handling, volume, order throughput, and consumable life. Overtly measurable and observable aspects are compared to previous products, competitor products or baselines as a basis of demonstrating performance gains and meeting customer specifications.
Features define the specific functional behaviors and services provided by the product. Measuring features requires customer specifications and an evaluation of whether product functionality supports the specifications. Metrics are typically binary “yes/no” counts that allow comparisons of expected product functionality.
Product and product use reliability measurements focus on the frequency of failure or probability of failure within a time period. Reliability metrics also include frequency of failure in batches or work flows. Failure measurements include event logging, mean averages of failures over time, failure rates per unit, defect encounters per batch, replacement frequency, and maintenance event frequency.
Conformance metrics establish measures to compare expected outcomes with actual outcomes. Measurements include manufacturing defect rates, service call incidents, warranty claims and returns. Conformance metrics used as an indicator of potential customer dissatisfaction include deviations from standards, spelling errors, localization failure, and poor construction that does not lead to repair or service calls.
Durability metrics deal with measurable product life and the number of uses before a product must be repaired or replaced. Measuring the proportion of failure event frequencies that result in product repair or replacement enables managers to gauge the durability of a product.
Serviceability primarily measures the ease of repair, but also includes the speed, courtesy and competence of service personnel. Customers measure product quality not only by the frequency of product failure, but also the amount of time before the product is restored to service, wait time for service, speed in which the repairs are completed, and the number of service calls required to complete a transaction. Subjective measures, such as the perceived competence of the service representative, call center support effectiveness and ease of communication, all affect the derived serviceability of a product.
Aesthetics is a purely subjective metric when measuring quality. Personal evaluation of product appeal to the physical senses reflects individual taste and preference. Benchmark aesthetic metrics against a focus group from the targeted demographic seek to determine whether the product is likely to meet customer expectations. High variation in personal taste makes it difficult to accurately predict customer satisfaction with this metric.
Perceived quality measures the impact of brand, perceived product durability, images and advertising on a consumer’s positivity -- or negativity -- regarding the product. Subjective in nature, consumer surveys are commonly used to provide numerical scores of perceived quality.
Capture metrics in both quantitative and qualitative analysis. Quantitative metrics and analysis use numerical data from which conclusions are drawn. Quantitative metrics include count data, event frequency, measurements and time. Qualitative analysis uses subjective data, often in numerical format, to evaluate a hypothesis. Qualitative measures include opinions, feelings, satisfaction ratings and predictive behavioral reporting.
- "University of Cambridge Institute for Manufacturing"; Quality Framework
- "Harvard Business Review"; Competing on the Eight Dimensions of Quality; David A. Garvin; November-December 1987
- Goodshoot/Goodshoot/Getty Images