5 Ways to Use Big Data That Have Nothing to Do With Marketing
For all of the buzz about big data and analytics, most of the real world use cases you read about involve marketing. It's true: big data is powerful for marketing, allowing them to finely tune their targeting and messaging efforts. But that's just a tiny fraction of the potential for big data. From operational improvements to safeguarding your business against the next recession, big data has a lot to offer aside from marketing. Here are just a few of those ways.
For all of the buzz about big data and analytics, most of the real world use cases you read about involve marketing. It’s true: big data is powerful for marketing, allowing them to finely tune their targeting and messaging efforts. But that’s just a tiny fraction of the potential for big data. From operational improvements to safeguarding your business against the next recession, big data has a lot to offer aside from marketing. Here are just a few of those ways.
1. Cyber Crime and Fraud Detection
Big data’s most powerful use is in identifying patterns. From that, it’s easy to set a baseline for what is normal behavior and what is not. You can determine normal human behavior as well as normal machine behavior. Using those baselines, it’s easy to spot abnormalities that indicate potential wrongdoing. For example, you can spot credit activities that are outside the customer’s normal buying habits and detect fraudulent activity like credit card or identity theft. Or, you can detect abnormal traffic patterns on a system or network and determine when cybercrime is underway.
2. Improve the Supply Chain
There are literally entire books written on this subject, so this article can only skim the surface—big data analytics is a potent instrument for finding ways to improve the supply chain. From determining which suppliers have the best history for on-time deliveries to finding the best route to get raw materials from the Far East to the U.S. Midwest, big data can help. It can also help on a more granular level, allowing you to pick which suppliers are most likely to offer low prices during a price surge or which ones can keep your production lines running when there is a shortage of raw materials or parts.
3. Developing Better Products
Armed with historical data on product quality and market response to products, you can develop better products that cost less to produce, deliver a higher level of quality, and sell better in the open market. Data analytics is far more accurate than focus groups and surveys, because you’re evaluating products based on how similar products actually performed in the marketplace, versus what somebody says in a closed forum when their money isn’t on the line.
4. Optimize Hiring and Work Scheduling
Big data and analytics are poised to turn the world of HR on its head. Until now, hiring practices were based on assumptions: HR managers assume that candidates from top schools are the best hires, and assume that a high GPA translates into a good work ethic. Armed with the actual data, they’re learning that there are other ways to determine a good hire, such as whether or not they complete the degree programs they started, or whether they held down a job outside of school. Data can also streamline the scheduling process, identifying when the workplace needs to be fully staffed versus times when running a skeleton crew can save some money.
5. Minimize Equipment Failures
Humans can easily identify simple patterns that lead to early equipment malfunction, but sometimes it’s a complex series of factors that cause equipment to expire early, or conversely, perform longer and better than expected. Data analytics can identify those complicated patterns, empowering businesses to change operational conditions to improve lifespan, or build better equipment that can withstand the conditions.
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