Examples of what you can accomplish with Big Data
Are you convinced of the power and potential of Big Data and predictive analytics, but still a bit hazy on what it can really do for you and your company, then I’m please to say that you’re in the right article. Here are 10 very real and practical examples of what you could accomplish with Big Data, inspired by an article of the Big Data Insight Group.
Dialogue with consumers
Today’s consumers are a tough nut to crack. They look around a lot before they buy, talk to their entire social network about their purchases, demand to be treated as unique and want to be sincerely thanked for buying your products. Big Data allows you to profile these increasingly vocal and fickle little ‘tyrants’ in a far-reaching manner so that you can engage in an almost one-on-one, real-time conversation with them. This is not actually a luxury. If you don’t treat them like they want to, they will leave you in the blink of an eye.
Just a small example: when any customer enters a bank, Big Data tools allow the clerk to check his/her profile in real-time and learn which relevant products or services (s)he might advise. Big Data will also have a key role to play in uniting the digital and physical shopping spheres: a retailer could suggest an offer on a mobile carrier, on the basis of a consumer indicating a certain need in the social media.
Re-develop your products
Big Data can also help you understand how others perceive your products so that you can adapt them, or your marketing, if need be. Analysis of unstructured social media text allows you to uncover the sentiments of your customers and even segment those in different geographical locations or among different demographic groups.
On top of that, Big Data lets you test thousands of different variations of computer-aided designs in the blink of an eye so that you can check how minor changes in, for instance, material affect costs, lead times and performance. You can then raise the efficiency of the production process accordingly.
Perform risk analysis
Success not only depends on how you run your company. Social and economic factors are crucial for your accomplishments as well. Predictive analytics, fueled by Big Data allows you to scan and analyze newspaper reports or social media feeds so that you permanently keep up to speed on the latest developments in your industry and its environment. Detailed health-tests on your suppliers and customers are another goodie that comes with Big Data. This will allow you to take action when one of them is in risk of defaulting.
Keeping your data safe
You can map the entire data landscape across your company with Big Data tools, thus allowing you to analyze the threats that you face internally. You will be able to detect potentially sensitive information that is not protected in an appropriate manner and make sure it is stored according to regulatory requirements. With real-time Big Data analytics you can, for example, flag up any situation where 16 digit numbers – potentially credit card data - are stored or emailed out and investigate accordingly.
Create new revenue streams
The insights that you gain from analyzing your market and its consumers with Big Data are not just valuable to you. You could sell them as non-personalized trend data to large industry players operating in the same segment as you and create a whole new revenue stream.
One of the more impressive examples comes from Shazam, the song identification application. It helps record labels find out where music sub-cultures are arising by monitoring the use of its service, including the location data that mobile devices so conveniently provide. The record labels can then find and sign up promising new artists or remarket their existing ones accordingly.
Customize your website in real time
Big Data analytics allows you to personalize the content or look and feel of your website in real time to suit each consumer entering your website, depending on, for instance, their sex, nationality or from where they ended up on your site. The best-known example is probably offering tailored recommendations: Amazon’s use of real-time, item-based, collaborative filtering (IBCF) to fuel its ‛Frequently bought together’ and ‛Customers who bought this item also bought’ features or LinkedIn suggesting ‛People you may know’ or ‛Companies you may want to follow’. And the approach works: Amazon generates about 20% more revenue via this method.
Reducing maintenance costs
Traditionally, factories estimate that a certain type of equipment is likely to wear out after so many years. Consequently, they replace every piece of that technology within that many years, even devices that have much more useful life left in them. Big Data tools do away with such unpractical and costly averages. The massive amounts of data that they access and use and their unequalled speed can spot failing grid devices and predict when they will give out. The result: a much more cost-effective replacement strategy for the utility and less downtime, as faulty devices are tracked a lot faster.
Offering tailored healthcare
We are living in a hyper-personalized world, but healthcare seems to be one of the last sectors still using generalized approaches. When someone is diagnosed with cancer they usually undergo one therapy, and if that doesn’t work, the doctors try another, etc. But what if a cancer patient could receive medication that is tailored to his individual genes? This would result in a better outcome, less cost, less frustration and less fear.
With human genome mapping and Big Data tools, it will soon be commonplace for everyone to have their genes mapped as part of their medical record. This brings medicine closer than ever to finding the genetic determinants that cause a disease and developing drugs expressly tailored to treat those causes — in other words, personalized medicine.
Offering enterprise-wide insights
Previously, if business users needed to analyze large amounts of varied data, they had to ask their IT colleagues for help as they themselves lacked the technical skills for doing so. Often, by the time they received the requested information, it was no longer useful or even correct. With Big Data tools, the technical teams can do the groundwork and then build repeatability into algorithms for faster searches. In other words, they can develop systems and install interactive and dynamic visualization tools that allow business users to analyze, view and benefit from the data.
Making our cities smarter
To help them deal with the consequences of their fast expansion, an increasing number of smart cities are indeed leveraging Big Data tools for the benefit of their citizens and the environment. The city of Oslo in Norway, for instance, reduced street lighting energy consumption by 62% with a smart solution. Since the Memphis Police Department started using predictive software in 2006, it has been able to reduce serious crime by 30 %. The city of Portland, Oregon, used technology to optimize the timing of its traffic signals and was able to eliminate more than 157,000 metric tonnes of CO2 emissions in just six years – the equivalent of taking 30,000 passenger vehicles off the roads for an entire year. The smart city project of Rivas Vaciamadrid in Spain – Ecopolis – has realized energy savings of 35% and a 50% reduction in ICT spending through a winning combination of smart grid and energy management, access control, air quality monitoring, traffic management, IPTV, etc. And those are just a few of the most spectacular examples.