During the year ahead, industries related to construction, engineering, and design will be placing increasing faith in the power of predictive analytics, and this unique form of data gathering and assessment will hold a powerful influence over company direction and managerial decision-making. In the field of retail, and in some companies that focus on product development, predictive analytics already factor heavily into company growth and investment allocation. But now that this trend is proving its value, it’s catching on and spilling over into a wider range of enterprises.
What are Predictive Analytics?
Traditional data streams and analytical models gather information and draw conclusions from events in the past, identifying patterns of repeated behavior, for example, and the outcomes of this behavior under different sets of controlled and uncontrolled circumstances. But predictive analytics take that data and use it to anticipate future events. While older models reveal trends and correlations in things that have already occurred, predictive analytics can be used to forecast the future and steer a company in way that takes maximum advantage of coming events.
In the retail field, Target was recognized early on as a company on the forefront of this trend. As the popular story goes, the company once received a complaint from the father of teenager after sending coupons for newborn baby supplies to his daughter. Later he realized that she was indeed pregnant, which the company already knew as a result of her purchase of prenatal vitamins. Predictive analytics takes the purchasing decisions of the moment and extrapolates them into the purchasing decisions of the future, and in its most sophisticated form, it can do this on a minute, customer-by-customer level.
So how can this powerful data assessment model apply to engineering and construction management? The auto industry is already laying the groundwork for an engineering and design revolution in this form of data application. Since car parts tend to have predictable lifespans, and maintenance needs tend to happen in predictive waves, smart car companies are creating service departments in their retail shops. When cars are brought for maintenance, data collected by the shop is sent back to the company’s engineering department. This unbroken loop of data allows manufactures to build necessary technology and maintenance schedules right into the cars.
If car manufacturers can now monitor maintenance needs for each individual customer–within each individual car– what can predictive data and analytics do for your own business? How can this model help you generate and maintain contact with new clients and entire new markets? For more information on how to predictive data streams to use for your engineering and design enterprise, reach out to the MA staffing and business management experts at Tech Needs. If you are looking for engineering recruiters in New Hampshire, contact us today.