Too often, corporate executives look at big data as a Magic 8 Ball capable of answering any question. The true results are more modest, although still impressive. Big data analytics can reveal much about your customers’ operations and their clients customers, but only if you can provide a well-defined use case and set define the scope of the analysis to yield reasonable returns. Seeing is believing, so when you’re selling a big data project, going in armed with examples will help you demonstrate the real value of big data while setting appropriate expectations.
Big data examples are even more important in the selling process when you appreciate that today’s CIOs buy based on data-driven results, and ROI from big data can be elusive: Wikibon estimates that, in 2013, the ROI on big data was actually $0.55 for every dollar spent. It makes you wonder why big data sales continue to grow at such an incredible rate. According to IDC, there will be a 50 percent increase in sales of big data analytics from 2015 to 2019, growing from $122 billion to $187 billion in revenue. Companies continue to invest in big data because the ROI metrics are always vague at the start of any project, but the promise of the returns makes the investment worthwhile. In fact, Gartner, Inc. found that 41 percent of companies are willing to underwrite big data projects without knowing the return.
Having solid examples of big data use cases and success stories can combat concerns over ROI by highlighting various results and benefits.
Big Data Can Benefit Any Industry
Every industry has unique operational needs and can derive its own benefits from big data analytics:
- In financial services, big data is being applied to make more informed financial decisions. For example, Morgan Stanley has started using Hadoop to analyze investments on a larger scale and with better results. Big data analysis is proving valuable for sentiment analysis, predictive analytics and financial trades.
- The automotive industry is using big data to analyze car functions and improve design, manufacturing and safety features. For example, the Ford Fusion generates about 25 GB of data per hour, which can be used to analyze driving patterns, assess wear on car parts, understand car performance and reduce maintenance costs.
- In supply chain management and logistics, big data analysis is uncovering new ways to improve shipping and reduce costs. Using telematics, for example trucking companies are able to use GPS information, fuel consumption and other data to streamline fleet tracking and lower the cost of delivery of goods.
- Retail is one of the biggest consumers of big data analytics. Margins on consumer goods are tight, so retailers are continually looking for new ways to optimize pricing, increase sales and improve customer loyalty. Walmart, for example, applied big data analytics to prepare for stocking for Hurricane Sandy; analytics demonstrated that strawberry Pop Tarts were in high demand along with flashlights and emergency gear.
- In healthcare, big data analytics are being applied to improve patient care, reduce readmission rates and manage costs. At the University of California, Davis, for example, researchers are using EHR data to reduce sepsis infection, which can have a 40 percent mortality rate. The algorithm provides a predictive model to show which patients are at higher risk of infection.
These examples and others show that big data analytics can provide tangible returns, even if some of those returns can’t be readily measured as return against dollars invested.
Big Data Use Cases for Any Business
In addition to industry-specific applications for big data, there are other use cases that offer benefits, no matter what kind of business your solution-provider customers operate:
- Pricing optimization – Research by McKinsey shows that most companies make 75 percent of their revenue from their standard products, with a one-percent price increase translating to an 8.7 percent increase in revenue. However, 30 percent of pricing decisions fail to deliver the best price. Big data can help optimize pricing, including creating differentiated pricing based on customers’ willingness to pay.
- Customer responsiveness – Big data can tell companies more about their customers and help them be more responsive to customer needs. A Forrester study shows that 44 percent of B2C marketers are using big data analytics to improve customer responsiveness, and 36 percent are actively using data mining for customer relations strategies.
- Contextual marketing – Big data can be used to power real-time analytics, making it ideal for contextual marketing. The simplest example is the custom advertising that websites serve up based on your browsing history. Big data can be used to create automated systems of engagement to customize offers and personalize sales.
These are just three use cases where big data can be applied. There are countless others. If you take the time to understand your prospects’ business objectives, it should be simple to develop your own big data examples to demonstrate the real value of big data. When selling your next big data project, keep in mind that the value of big data insight isn’t always measured in dollars.