By Melissa Brown
Big data and analytics are buzzwords that have been around for a while. And during the past few years, there’s been a massive increase in the amount of data organizations have collected. Companies that know how to effectively use the information, however, are still in the minority. When surveyed, most business executives agreed that analytical decisions based on data are better than those based on intuition. Many companies are trying to change the way they make decisions, but NewVantage Partners found in their 2019 Big Data and AI Executive Survey that most are struggling in their attempts to become data driven.
There are examples from almost every industry that demonstrate what data analytics can do for organizations:
With surprising accuracy, Target identifies pregnant shoppers and offers them coupons for baby products. They found that most pregnant women buy 24 distinct items at certain times during their pregnancy. They purchased unscented lotion at around four weeks, calcium, magnesium and zinc supplements at 14 weeks, then cotton balls, hand sanitizer and wash cloths in the last trimester.
UPS uses geo-location data to optimize its drivers’ routes. The company also mounts sensors on critical vehicle parts to anticipate needed repairs and prevent breakdowns, saving millions of dollars every year.
Publications like Forbes and Huffington Post use data to determine which top stories to run.
Hospitals in Paris work collaboratively to predict how many patients will be admitted to each hospital on a daily and hourly basis to ensure they have enough staff on hand.
At BP’s refineries, they collect data on the temperature and stress levels of pipes so they can fix problems before there’s an issue. BP reports that their data collection saves them billions.
Amazon uses an algorithm it calls “item-to-item collaborative filtering.” It monitors the products users look at, what they’ve bought, what they have in their shopping cart, items they’ve rated highly in their feedback, what other customers have purchased and makes recommendations based on associations among those products. If you place charcoal briquettes in your cart, Amazon will likely recommend a grill cleaning brush.
Several travel sites can predict when an airline ticket to a particular destination will reach its lowest price and alerts users when it does. Today, few customers would bother with a travel site that is unable to offer this service.
The Atlantic published a three-part series on the role of big data in the college-search process. Although many colleges across the nation have been struggling to stay afloat, relying on a scattershot approach to marketing, others are using student targeting formulas to increase enrollment. They’re seeking out students in other states who have profiles similar to the most successful students who currently attend their college.
Realizing that graduation rates play a large role in where students decide to attend, many colleges are also using predictive analytics to determine which students are likely to drop out so they can get them get back on track. Georgia State University has a team of advisers who track more than 800 risk factors on a daily basis. When the data shows a student is in trouble, they reach out to them with solutions. GSU raised its six-year graduation rate from 32 percent in 2003 to 54 percent in 2017. Comparative data on graduation rates can be found at collegecompletion.chronicle.com.
According to Harvard Business Review, while most organizations surveyed stated they understood the potential of big data and plan to implement its use, most haven’t. When NewVantage Partners surveyed 64 c-level technology and business executives from top companies, 77% reported that “adoption of big data and AI initiatives continues to represent a challenge for their organizations.”
Over 70 percent said, “they have yet to forge a data culture.” This is despite the fact that over 90% of them have spent millions in increased investment toward this goal. Respondents stated, “technology isn’t the problem — people and (to a lesser extent) processes are. 40.3 percent identify lack of organization alignment and 24 percent cite cultural resistance as the leading factors contributing to this lack of business adoption.” Another issue is that employees don’t always know what to do with the data they’re given. Forrester, a market research company, found that only 29% of companies stated they are “good at connecting analytics to action.”
Data, just like great ideas, are only valuable when acted upon. Thomas Edison stated, “The value of an idea lies in the using of it.” We have only scratched the surface with what big data can do. Organizations that learn how to harness its potential will find innovative ways to solve problems, serve customers better and remain competitive.
Melissa Brown is a web developer at SimpleDzn.com and former business professor at the University of Alaska. She can be reached at email@example.com. This column is brought to you as a public service by the UAF Department of Applied Business.