Benchmarking for companies and policy-makers

Benchmarking is the practice of comparing business processes and performance metrics to industry bests and best practices from other companies. Dimensions typically measured are quality, time and cost.

Four types

Mercy Harper from APQC, next to performance and practice benchmarking also divide internal and external benchmarking:

-Performance benchmarking involves gathering and comparing quantitative data (i.e., measures or key performance indicators). Performance benchmarking is usually the first step organizations take to identify performance gaps.

-Practice benchmarking involves gathering and comparing qualitative information about how an activity is conducted through people, processes, and technology.

-Internal benchmarking compares metrics (performance benchmarking) and/or practices (practice benchmarking) from different units, product lines, departments, programs, geographies, etc., within the organization.

-External benchmarking compares metrics and/or practices of one organization to one or many others.

For brands and policy-makers

A benchmarking process compares a brand with best-in-class standards, so the company can improve across the board. There are companies, like Talkwalker, which offer digital benchmarking tools, and argue that performance benchmarking is a powerful tool only if you’re looking for external benchmarking. Benchmarking against yourself is wasting of time, states Talkwalker.
A benchmarking process can also compare not only brands, but, for example, building energy. To establish benchmarking models, the most important are samples, so to say, data from different sources across the board. Good benchmarking methods should be consistent, robust and able to explain. Benchmarking programs can be a good tool not only for private organisations, but for policy-makers as well.

Open data for benchmarking models

For example, the research published in Energy Policy magazine examines how efficient is building energy benchmarking with open-data from 10 cities. While the buildings are by far the largest source of urban energy consumption, cities show an effort to reduce their energy use. Buildings undergo energy benchmarking—the process of measuring building energy performance in order to identify buildings that are inefficient. Researchers examined the feasibility of using city-specific, public open data sources in two benchmarking models and compared the results to the same models when using the Commercial Building Energy Consumption Survey (CBECS) dataset, the basis for Energy Star.
The two latter benchmarking models use datasets containing building characteristics and annual energy use from ten major cities. Results demonstrate that benchmarking models using open data outperform models based solely on the CBECS dataset.
Additionally, results indicate that building area, property type, conditioned area, and water usage are the most important variables for cities to collect. Having demonstrated the benefits of using open data, scientists recommend changing current benchmarking practices to ones which support a data-driven framework.