Your job is about to get easier.
Thanks to an influx of emerging technology in analytics, you’ll be able to generate insights and solve problems more quickly than ever before.
Let’s take a look at how these emerging technologies are changing three vertical industries.
Healthcare: Machine Learning Improves Patient Treatments
One of the technologies transforming healthcare is machine learning.
Machine learning allows software applications to predict outcomes without explicit programming.
One healthcare organization, Memorial Sloan Kettering (MSK), is working with IBM Watson to develop machine learning applications for diagnosing patients.
TechEmergence says that diagnosis is “a very complicated process” that involves “a myriad of factors… of which machines cannot presently collate and make sense.”
Over the years, MSK's oncology department has acquired considerable data on cancer patients and treatments. Thanks to their partnership with Watson, MSK’s team can suggest treatment ideas for doctors dealing with cancer cases “by pulling what worked best in the past.”
This is a standout example of how doctors can using machine learning for better treatment.
Retail: Predictive Analytics Improves Inventory Management
The next two verticals highlight the potential for predictive analytics in different ways.
BizTech notes that brands with ineffective inventory management practices will not only lose out on the occasional sale. Ultimately, it may lead to competitors picking up disgruntled customers.
“That leads the retailer to believe that demand for the product has shrunk,” the site says, “when actually customers are simply fulfilling that demand elsewhere.”
Inventory costs can be lowered as much as 40 percent with predictive analytics. Additionally, such technology can increase sales up to 20 percent and boost turnover rate by up to 3.5 times.
By using predictive analytics, retailers can boost performance in several areas.
Manufacturing: Proactive Repair Keeps Supply Chain In Motion
Predictive analytics also has applications in manufacturing.
Predicting part, product, or service failure can ensure proper tool selection for field technicians, among other things.
This is according to Deloitte’s robust 2017 “Exponential Manufacturing” report.
The authors state that “learning the causes behind a failure can enable manufacturers to more effectively address the root of the problem, rather than its symptoms.”
They present a case study for Schneider Electric, who collected data for one year for a steam model turbine. “Analysis enabled Schneider to address the root cause—thermal expansion problems—before they led to ‘symptoms’—bearing vibration—that caused equipment shutdowns,” the authors say.
As a result, the company estimates the potential savings of millions of dollars with fewer days of equipment downtime.
Whether you work in healthcare, retail, manufacturing, or another industry, machine learning and predictive analytics are just two examples of emerging technology that can make your job easier.