Are businesses doing enough to maximize the competitive edge big data offers? According to a 2015 survey conducted by Gartner, Inc. — a firm that supplies information technology research and consultation services to a global clientele — nearly 75 percent of businesses have already committed or are in the process of committing to big data. At the same time, however, other studies suggest that businesses have analyzed less than one half of one percent of all the big data they are generating and collecting.
Of course, to analyze such massive amounts of information, businesses need the services of skilled business intelligence (BI) professionals. Amassing data is one thing. Knowing what to do with that data is something else entirely. And knowing what to do requires a combination of strategic insight, techno-logical savvy, and adaptability. Because it is such a dynamic field, business analytics can feel very entrepreneurial.
What are some established business analytics applications? And how can these applications help your company derive the greatest competitive value from its big data?
Increase Organizational Efficiency
Careful analysis of internal processes and procedures can be the key to making a business more competitive. Your company may have installed a state-of-the-art e-commerce solution, but if that system has trouble communicating with the tools your company uses for order fulfillment, any operational gains may disappear.
Business analytics can be instrumental in identifying and eliminating hidden waste. Business analytics can also help build understanding, increase focus and improve working relationships between your company’s front and back offices. All departments, managers and workers stand to increase their productivity thanks to the holistic functional analyses business analytics can provide.
Revolutionize Resource Allocation
If analyzed properly, big data can drive decisions that will enhance your business’s competitiveness. What are your business’s investments, and are you getting the best possible return on those investments?
In the early 2000s, Oakland A’s general manager Billy Beane asked these questions. How could his baseball team, hamstrung by its small market share, possibly hope to compete against Goliaths, like the New York Yankees, with much greater resources at their disposal? Beane’s solution was to turn to advanced metrics. He worked against the grain and used relatively neglected statistical indicators (on-base percentage, walk-to-strikeout ratio and more) to find bargain talent. The A’s remained competitive on the field despite their roster’s low payroll, in part because Beane chose to invest in data collec-tion and analysis. Now, nearly every team in major league baseball uses big data to help determine a player’s actual value, and to manage contracts in a way that not all of their financial resources are tied up in one or two stars.
Get Out Ahead of Trends
In business, the future is unknown but not entirely unknowable. Predictive analysis is the science of mining data to make reasonable estimates about the future, to seize opportunities before a competitor does, and to mitigate risks.
By uncovering and considering every variable, predictive analysis aims to substitute foresight for hindsight. However, predictive analyses aren’t simply forecasts. They provide insight into how specific decisions will break down in terms of cost and benefit. What looks like a trend today may, six months from now, prove instead to have been a fad, or an anomaly — a bad investment wisely avoided.
Discover New Markets
Marketers love big data in business because it creates new and exciting opportunities for market segmentation. Big data means moving beyond traditional demographics like age, gender and geographic location. Big data also allows marketers to drill down to more granular levels (e.g., married couples between the ages of 25 and 32, without children, living in dense urban centers, and who do the majority of their online shopping on a desktop computer).
Big data also allows marketers to sort their companies’ clientele into many different but overlapping subsets of individuals. By clustering leads and conversions in new ways that only big data allows, marketing analysts can uncover new information about what causes customers to act the way they do. Without market segmentation, actionable consumer interests, demands and values may remain invisible. That is, until a rival profits from being the first to make an appeal to those interests, demands and values.
Enhance Your Brand and Develop Meaningful Relationships With Your Customers
A recent report in Forbes illustrates how a business can employ big data’s hard evidence to distinguish itself from its competitors in more intangible ways. Tesco, the largest supermarket chain in the United Kingdom, has recently partnered with the nonprofit organization Food Cloud. Together, Tesco and Food Cloud are using advanced analytics to locate retail locations with surplus groceries and to pair them with food banks and other charitable organizations that can make the most of surplus food donations. By entering into this partnership, Tesco is transforming big data into community goodwill; a reputation for social responsibility; and, consequently, potential growth in customer loyalty. As The Wall Street Journal has reported, “for many investors, socially responsible investing is now a guiding principle.” Applying business analytics to issues of corporate governance can help position your company as a leader in its industry.
No competitive advantage in business is permanent. Businesses must exercise constant diligence and invest heavily in innovation in order to maintain their position, much less avoid falling behind. Even though the tools and tricks of the trade may be new, competing on analytics and taking full advantage of big data in business is an age-old problem. When everything seems to be noise, what are the patterns, and who is able to recognize them first? Qualified business analysts have a unique point-of-view, and, increasingly, companies understand how limited their perspectives are without it.
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