Businesses in all industries are leveraging predictive analytics (PA) to make better decisions. The healthcare industry, in particular, has made great strides thanks to PA. The technology is helping healthcare professionals predict diseases ahead of time while providing doctors with data on the most effective treatment options.
The world of retail is changing, with heavyweights such as Macy’s, Sears and Kmart shutting down many stores. So, how can retail businesses adapt in order to stay relevant? One strategy is to leverage predictive analytics (PA).
Over the last two decades, the U.S. has been plagued with high rates of prescription drug overdose. About 142 American citizens die every day from drug overdoses, many of which are caused by prescription medications obtained legally. Additionally, the number of opioids prescribed as of 2015 is three times as high as the number of prescriptions given out in 1999. Due to these staggering statistics, doctors and data scientists are working towards using predictive analytics to reduce the number of prescription drug overdoses.
With supply chains becoming larger and more complex, it is becoming more difficult to improve service through a reduced order-cycle time while enhancing inventory availability and reducing operating costs at the same time. Big data is revolutionizing the optimization of supply chain and inventory management by improving visibility. It is telling a compelling story that is making leaders listen. Companies that have adopted predictive analysis see up to a 50% reduction in non-performing inventory and a 25% reduction in inventory holding costs, thus freeing up working capital.
Traditionally, the apparel retail industry has consisted of customers going into stores, trying on clothing, and then deciding whether or not to buy. However, now that people frequently buy apparel online, businesses are leveraging the power of predictive analytics (PA) to improve their customer conversion rates and reduce returns. Machine learning, predictive modeling and data analysis are the backbone of PA technology, which uses historical shopping data to help businesses make well-informed decisions.
The travel industry is one of the most technologically advanced markets in the world, adopting big data and predictive analytics (PA) when the tech was still in its early days. The highly competitive nature of the industry has prompted airlines and hotels to develop apps that leverage this cutting-edge technology in order to satisfy and retain customers.
We live in an increasingly digitized world where developers are using data to help companies gain valuable insights regarding their business. This information can be leveraged to determine flaws in an organization’s structure and operations, churning out smart solutions that reduce costs and increase revenue. This is especially true in the healthcare industry, where predictive analytics (PA) plays a key role in bolstering a patient’s treatment plan and reducing out-of-pocket costs.
Predictive analytics and big data are two forms of cutting-edge technology that are commonly integrated into apps and software, but many individuals are confused when it comes to how these two technologies compare. In fact, many are unsure which data-handling technology is best for their development project, which can make hiring the right developer a challenge.
Predictive analytics (PA) is transforming virtually every industry, from sports and banking to healthcare. This technology is essential in advancing the healthcare industry, as it offers a full-fledged idea of what a patient’s medical history looks like and compares it to data from patients with similar histories.
Flurry’s annual mobile technology round-up report revealed a surprising fact: the amount of time spent using apps grew by just 6% in 2017. This figure reflects a significantly smaller margin of growth than the 11% increase observed in 2016.