How Business Analytics will shape our digital future
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How Business Analytics will shape our digital future

How Business Analytics will shape our digital future

For today’s business executive, one word will define their careers: Data.

The digital economy is disrupting businesses, whether it’s large multinationals spanning countries or a two-person startup in a garage. With large datasets now available, the business world and financial markets are scrambling to adapt to this fast-moving flow of information.

Forbes reported 53 percent of companies are using big data analytics today, an increase of 17 percent in 2015, with telecommunication and financial services industries fueling the fastest adoption. This rapid uptake is one that spans the globe – 55 percent of companies in North America currently adopt big data analytics, followed by Europe, the Middle East, and Africa (EMEA) with 53 percent and Asia-Pacific with 44 percent current adoption.

Dresner Advisory Services’ 2017 Big Data Analytics Market Study also found that companies value big data analytics to be of greater strategic importance than the Internet of Things (IoT), natural language analytics, cognitive Business Intelligence (BI), and location intelligence.

“We’re rapidly entering a world where everything can be monitored and measured,” the Massachusetts Institute of Technology’s Center for Digital Business director and economist Erik Brynjolfsson said. “But the big problem is going to be the ability of humans to use, analyze and make sense of the data.”

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Source: UCLA

Companies who are able to tackle this phenomenal amount of digital information – be it for marketing and sales to customer base and market opportunities – are thus, unsurprisingly, today’s most innovative. These are the sort of companies announcing profit margins three times more rapidly than the average rate. They are the fastest innovators and disruptors in their sectors and in some cases, beyond them.

Traditional MBA models of education – focusing squarely on finance, marketing, accounting and economics – may not be the best fit for those looking to capitalise in this new intersection of data and business that is hungry for talent.

“Today’s executives must possess a level of agility, market awareness and strategic decision-making skill that would seem almost superhuman a generation ago,” University of California Los Angeles’ (UCLA) Anderson School of Management MSBA executive director Paul Brandano said.

The digital economy now has enough data to let everyone, from governments to investors, to build a constantly evolving picture of today’s customers, markets, competition, and operations that make profit possible, Brandano explained.

This intersection between data and human behaviour was the stuff businesses dreamed of just a generation ago. Today, this seemingly “superhuman” act is possible for any business student taught the right skills and program. Using what is dubbed “the new oil,” we are now able to use data to track the behaviour of 368 million Facebook members on the social network, identify which customers will get pregnant when, and find out which goods to manufacture on demand for AliBaba’s 507 million mobile monthly customers. The list goes on.

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Source: UCLA

UCLA could not sit back during this recent explosion of digital data in the business world, school administrators said. From surveillance tapes to social media, public records and more, the future is in data – and the university intends to specialise in it.

Its Master of Science in Business Analytics (MSBA) is aimed at furthering knowledge and educating the next generation of leaders in business analytics. They have recruited figures from the industry to join its faculty, such as Uber’s former Head of Economic Research Keith Chen who redesigned the dynamic Surge pricing model, as well as academic luminaries like the Journal of the European Economic Association co-editor Paola Giuliano.

It is one of the few top-tier business schools to offer the MSBA degree, merging theory and principle with up-to-the-minute business practice. Technical courses focus on R, Python, SQL, Machine Learning, and data management, supplemented by classes in business fundamentals and metrics. Then, the coursework shifts to MBA-style courses with an emphasis on applied math, statistics, and data management approaches.

It’s a curriculum that stands out from what other business schools are offering. Here, each student is taught how to use state-of-the-art data analytics tools to make better business decisions. In its Operations Analytics class, students learn how to use quantitative models to optimize internal processes and resources.

Meanwhile, at its Competitive Analytics class, professors guide students in answering questions such as: How competitive is a given industry? What role does product differentiation play in determining pricing and margins? Which specific products are close substitutes (whether from the same firm or from different firms)? In the Customer Analytics course, students leverage innovative analytic approaches to better understand, predict and influence the behavior of the customer.

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Source: UCLA

This year, MSBA student Subbaiah Bopaiah and his team developed a random forest model in Python to predict weekly and monthly sales for US e-commerce giant Amazon, with the aim of studying the effects of different advertising parameters on total sales for products advertised on Amazon.

Other students like Xuan Zhong cleaned a large amount of Budweiser’s sales and market data and analysed the causal effect between the beverage company’s Super Bowl ad on the brand’s post-Super Bowl sales by running regression analysis on revenue data versus the percentage of viewership across designated market areas.

In addition to these classroom examples, students get to apply what they learn in the real world through their summer internships and a corporate-sponsored Capstone: Applied Analytics Project (AAP). In teams of four, students must use real client data to produce a market-ready analytics report and solve an important strategic problem a real company is facing.

To build each year’s class, the UCLA Anderson team starts by looking for unicorns. It’s a short program – 13 months – yet one that resembles a PhD course in its rigor and technical prerequisites.

“The next generation of manager will have the technical skills to earn a seat in the IT suite, but will also possess the management skills to convince senior executives that the story emerging from the data is valid, trust worthy and well-articulated,” Brandano said.

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Source: UCLA

Such talent is scarce, but the school makes sure its MSBA cohort is made up of candidates with the rare combination of technical and programming skills as well as the ability to communicate with clarity and charisma.

Looking at its Class of 2018 website can be intimidating, with this year’s candidates coming from a range of impressive backgrounds, an average graduate CGPA of 3.59, and 710/92 percent average total GMAT results.

Previous employers include big names such as AliBaba, Baidu, McKinsey & Company, Motorola, etc. There’s a former JP Morgan Chase application developer Ankita Nagori, former Forbes Media senior analyst Ada Lin, and former Talking Data – China’s largest mobile data firm – data scientist Liang Li, to name a few. It’s a highly international class as well – 70 percent are from abroad, from 11 nations of origin.

Although the program is only in its first year, every student has secured a research project or internship at some of the world’s leading high tech, entertainment, healthcare, retail and internet companies for the summer.

It may be early days for big data and UCLA, but at the rate it is going, it looks to be exciting times ahead.

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