More than ever before, engineers are creating products for developing countries. One of the purposes of these products is to improve the consumer's quality of life. Currently, there is no established method of measuring the social impact of these types of products. As a result, engineers have used their own metrics to assess their product's impact, if at all. Some of the common metrics used include products sold and revenue, which measure the financial success of a product without recognizing the social successes or failures it might have. In this thesis I introduce a potential metric, the Product Impact Metric (PIM), which quantifies the impact a product has on impoverished individuals -- especially those living in developing countries. It measures social impact broadly in five dimensions: health, education, standard of living, employment quality, and security. By measuring impact multidimensionally it captures both direct (having to do with the products main functions) and indirect impacts (not related to the products main functions), thereby revealing more about the products total impact than with other metrics. These indirect impacts can have a larger influence on the consumer than the direct impacts and are often left unmeasured. It is calculated based on 18 simple field measurements of the consumer. The Product Impact Metric can be used to predict social impact (using personas that represent real individuals) or measure social impact (using specific data from products introduced into the market). Despite its challenges, the measurement of a program or policies social impact is a common practice in the field of social sciences. This measurement is made through social impact indicators which are used to measure, predict, and improve potential social impacts. While there are clear benefits to predicting the social impact of a product, it is unclear how engineers are to select social impact indicators and build predictive models. This thesis introduces a method of selecting social impact indicators and creating predictive social impact models that can help engineers predict and improve the social impact of their product. First, an engineer identifies the product's users, objectives, and requirements. Then, the social impact categories that are related to the product are determined. From each of these categories, the engineer selects several social impact indicators. Finally, models are created for each indicator to predict how a product will change these indicators. The impact categories and indicators can be translated into product requirements and performance measures that can be used in product development processes. This method of predicting social impact is used on the proposed, expanded U.S. Mexico border wall.
College and Department
Ira A. Fulton College of Engineering and Technology; Mechanical Engineering
BYU ScholarsArchive Citation
Stevenson, Phillip Douglas, "Methods and Metrics to Measure and Predict the Social Impact of Engineered Products" (2018). Theses and Dissertations. 6972.
Phillip Stevenson, Social Impact, Predictive Models, Product Design