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6 analytics trends that will shape business in 2016

Thor Olavsrud | Jan. 26, 2016
Deloitte identifies six major trends and market disruptions that will drive C-suite technology investments in 2016.

Colleges and universities are working hard to produce data science talent, but the number of data scientists will remain limited and the competition for top talent will be fierce.

"Companies need to recognize that they need to really develop close relationships with these degree programs," Lucker says. "Creating a true courtship between companies and universities is becoming more and more important."

Additionally, Lucker notes that attracting talent is only part of the equation. Companies that can get top data science talent in the door need to think long and hard about retention.

"It's important to have a proper data science career path and diversity of working experience to foster the retention rate of these employees," he says. "Doing the same thing day in and day out is not going to foster a strong relationship."

3. Man/machine partnerships are getting stronger

IDC is projecting that businesses will spend more than $60 billion on cognitive solutions by 2025. While there have been numerous projections that artificial intelligence and cognitive solutions will eliminate large numbers of jobs, Lucker says leading businesses will use humans to add value to smart machines. After all, human talent will be required to build and implement cognitive technologies, and others will serve as a check to ensure the technologies are performing well. Still others will complement computers in roles machines can't perform well, for instance roles involving high levels of creativity or empathy.

In other words, the man-machine dichotomy is not "either-or" but "both-and."

"Cognitive computing and cognitive techniques are really just another tool in the toolbox," Lucker says, noting that cognitive won't be the right solution for all problems. "It's a complementary tool to add to the array of analytic approaches that really talented and diverse data science folks have available to them."

"It requires a human being with our advanced judgment skills to look at the results that emerge from these cognitive and machine learning analyses and do a litmus test on them," Lucker adds.

4. The Internet of Things -- and people

People are going to reemerge as an important element in the Internet of Things (IoT) in 2016 as well, Lucker says. IoT is rapidly evolving from the realm of interesting gadgets to include tracking people as "things" to form new business models and influence behaviors. Lucker notes this innovation is taking place in both consumer-focused and business-to-business industries and will have significant implications for business models and industry.

The capability to track people and their movements means data on travel patterns and spending patterns and similar things will allow for wholly new business models. Think Uber, for instance.

And Lucker notes that many businesses already have much of the necessary infrastructure in place. For instance, auto insurance companies are already using customer smartphone data to power "pay as you drive" applications, and some health insurance firms are giving discounts to customers that undertake fitness activities documented by wearable tracking devices. Sensor data is also powering fleet management in long-distance trucking.

 

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