Harvard's New Data Science Program Signals a Big Shift for Businesses
Harvard hosts some of the most prestigious programs in the world, especially in business and law. So it was big news in the data science industry when the university announced a new master's program in data science in March 2017 -- and it was bigger news when the university recently credited the program for a 2 percent increase in international applications to the Graduate School of Arts and Sciences.
The fact that elite universities are now investing in -- and seeing results from -- data science programs should send a signal to entrepreneurs: It’s time to start seriously considering the implications of data science in every industry. Like blockchain, data science has quickly emerged from virtually nowhere to find applications in every sector. Until now, bigger universities have been slow to keep up, which has allowed independent, alternative educators such as Kaggle, Udemy and Coursera to drive the industry.
The establishment of a data science curriculum at one of the oldest and most reputable universities in America hints at the potential impact data science will have on entrepreneurship -- after all, cryptocurrency and blockchain are still relegated to extracurricular clubs at Harvard, even though they've attracted fervent interest from startups and venture capitalists.
Despite some skepticism from those already in the data science industry, the increase in applications shows that the program at Harvard has staying power. But the true value of data science will be realized by entrepreneurs who are willing to embrace the vast possibilities for disruption that the industry offers.
Data is leveling the playing field.
The economy basically demanded a graduate course in data science from an elite university. IBM analysts predict that job openings for data and analytic talent will increase by 364,000 in the U.S. by 2020, and jobs for advanced data scientists will reach nearly 62,000 by the same year.
Data science is an appealing career path because of its flexibility. Data science tactics can be used in everything from corporate business and law to startups in new technologies such as the Internet of Things, virtual reality and SEO. As startups race to use new tech to gather as much data as possible, data scientists are the ones who will leverage all that data to create value. Now, every disruptive company needs to have a data science component.
But incorporating data science can signal a foundational change in company structure. As more data becomes freely available from both people and devices, it will become a natural resource anyone can harvest; a solo entrepreneur gathering and analyzing data effectively can compete with a giant company that uses its data ineffectively. In this sense, data is a market equalizer; scaling will become less of a priority for companies with sound data practices.
And those ignoring data streams are already being quickly outmatched. In retail, for example, McKinsey & Company found that a business leveraging big data efficiently can increase its operating margin by 60 percent. Data science can unlock new potential for businesses in any industry. Focusing on four fundamental objectives can help entrepreneurs leverage data and keep up with the competition:
1. Decode market shifts using advanced metrics.
Data science is most useful as a way to view and organize large data sets to optimize insights. Don't rely on conventional wisdom; use data to uncover actual market conditions such as need, demand, competition performance and other industry-specific metrics.
Be sure to engage critically with the data and its implications; it's not enough to glance at a spreadsheet. Eighty-five percent of respondents to an executive survey by New Vantage said they use big data, but only 37 percent have found success with it. Execution is more important than intent when it comes to data integration.
2. Build out robust customer profiles.
Most startups understand that customer retention is a priority over customer acquisition -- and fortunately, existing customers offer a lot more data than potential customers. This data can help uncover customer behavior patterns, which help entrepreneurs develop effective retainment strategies.
When applied to consumer behavior, data science techniques can help organizations of any size. The town of Derry, New Hampshire, hired customer analytics startup Buxton to study its citizens' consumer behaviors and make recommendations to help recruit new businesses. By leveraging that data set, the town (and, in turn, the businesses located there) was able to better understand their customer base.
3. Uncover what works best about a product or service.
Sometimes consumers act differently than they speak. Data science is useful in uncovering realities about a product rather than perceptions. By uncovering who is using a product and for what reason, startups will be able to make tweaks -- or pivot entirely -- with lower risk and more efficiency.
Zurich Insurance, for example, recently implemented data analytics AI to reduce operational inefficiencies in its injury claims system. According to a case study presented to Gartner, the company saved $5 million per year by using the program to reduce medical report assessment times from one hour to a few seconds.
4. Fail more effectively.
Data science allows entrepreneurs to be know-it-alls, a major perk of which is finding information that was previously hidden. Trial and error is a key process of entrepreneurship -- the "right" idea often comes on the fourth or fifth unique attempt. Data helps business owners learn more from their failures and maximize future successes.
UPS, for example, uses data to tweak its massive distribution network and save hundreds of millions of dollars using its On-Road Integrated Optimization and Navigation system. Data science provides a broad overview of the huge number of possibilities that can improve efficiency in a business.
Entrepreneurs should have a reason behind every move they make, and data science gives them the best reasons to make the best moves. Harvard isn’t the first organization to jump on board the data science bandwagon. Its prestige, however, will carry over into industries both old and new.