How Data Science Benefits All Companies (Not Just E-commerce & IT Giants)
Big Data Might Change The World As We Know It
You can use Big Data to do almost anything. So here is our guide of How Data Science Benefits All Companies (Not Just E-commerce & IT Giants).
Love Shopping on Amazon?
Did you know that Amazon uses Big Data to gather all sorts of data points. While users browse and shop, from their individual history, etc. to fine-tune its own recommendation engine?
Are you aware that Amazon also uses these data points to recommend new products to you? This means that you don’t have to browse through an entire catalogue. Machine learning personalises its marketing channels. That’s why you receive recommendations for products that you are most likely to purchase.
Big Data-driven marketing and sales processes are working in real-time. Your data is processed with several million data sets together with one aim, to make you buy more or use more of the service.
Love Searching on Google?
Google powers its primary bread-winner, the search engine, with Big data, Artificial Intelligence, and Machine learning. But it’s not just that. Google Maps gathers several bytes of data on a real-time basis. This gives you accurate predictions of traffic.
If knowledge is power in business, it’s data that fuels this knowledge.
According to estimates, we’ll collectively reach a volume of 44 trillion gigabytes by the end of this year (2020).
The e-commerce bigwigs and the IT giants have seemingly led the rally as far as the adoption of data science and data analytics. However, several companies across industries (such as insurance, telecommunications, logistics, and financial services) are increasingly investing in the field.
Here are a few Big Data use cases to prove that other industries started investing in Big Data too:
The New York Stock Exchange
The Financial Services industry is deeply invested in the qualitative returns of Big Data analysis and management, and the use of Big Data to build better experiences for end-users, to make better decisions, and to build business processes that just work better.
The New York Stock Exchange, for instance, captures 4 to 5 Terabytes or more of data each day. In the year 2016, there were 18.9 billion connections.
Obviously, the New York Stock Exchange couldn’t keep up with this data deluge. For that reason, it used IBM’s Netezza platform to help bring in Big Data management analytics to handle complex analytics, market surveillance, capacity planning, and more.
UPS has a $20 billion dollar problem: the shipping, packaging, and logistics giant is stuck with unions and a huge task of trying to bring its delivery network or operations from the past era. They had to find a way out of its own problems and it then embraced Big data.
UPS gathers tons of data – from customers, delivery vehicles, origin and source locations, warehouses, and even their drivers’ handheld devices, along with GPS information – to craft delivery routes, optimal use of resources, fleet and fuel allocation, and more.
The kind, the quantum, and the variety of data is beyond complex, to say the least. Some of this data also includes shipment weights, pick and delivery times, and a history of the usual customer requests.
Right away, using all this information to carve out delivery routes or to improve processes helps reduce time and delivery costs for UPS. A reduction of 1 mile per day/ driver can save $50 million a year in fuel, vehicle maintenance, and time.
New Age Lending with Wonga, Lenddo, & Kreditech
Credit is essential for us all. The availability of financial credit allows many of us to own assets, to get a better education, to manage emergencies, and more. For many of us, a strong credit score is also essential to avail of some necessities such as mortgages, emergency cash handouts, and even insurance.
At present, individuals have very little control over how they are scored. They have even less ability to contest inaccurate, biased, or unfair assessments of their credit. Traditional, automated credit scoring tools raise longstanding concerns of accuracy and unfairness.
Thanks to Big Data, all this is about to change.
Take Wonga – an ambitious, data-driven, short-term lending website for instance. Wonga uses a proprietary algorithm and publicly available customer information to decide (in real-time) whether to accept loan applications.
Wonga’s model incorporates 7,000 pieces of data on each customer, from credit bureaus and other databases, to determine if he or she is creditworthy. Wonga goes as far as to also consider the time of the day and the way an applicant clicks around on their website as factors to take into consideration.
Hong-kong based Lenddo scrutinizes applications also based on the individual’s connections on Twitter and Facebook.
Kreditech, a Germany company that seeks to provide “scoring as a service” — takes at least 8,000 different indicators into account before “lending” — things such as “location data (GPS, micro-geographical), social graph (likes, friends, locations, posts), behavioural analytics (movement and duration on the webpage), e-commerce shopping behaviour, and device data (apps installed, operating systems).
Progressive Insurance Company
Someone’s watching how you drive- so take that hand off the gear knob. That “someone” isn’t just the traffic cops or the CCTV cameras on the busy junctions.
Your Insurance company is watching you as well. Don’t believe us? Just ask Progressive — one of the largest car insurance companies in the U.S.
From quote to claim, every single application is scrutinised. Your driving behaviour is closely watched.
Progressive’s “Snapshot” device uses technology that observes an individual’s driving behaviour. This data can then be used for everything like quote processing time, pricing, claims turnaround time, and more.
All these are beyond the traditional insurance rating variables (such as demographic profile or the insured vehicle’s year, make, and model) alone. Progressive — the company — believes that the actual driving behaviour carries more than twice the predictive power of any other factor. Thanks to technology and real-time data, they know all of this even before you ask for an insurance quote for your car.
What Is Next?
Healthcare, insurance, manufacturing, travel, agriculture, space, retail, and several other businesses are joining the bandwagon when it comes to big data and related technology such as machine learning, artificial intelligence, and the Internet of things (IoT).
Want to find out how you can compete, reduce costs, boost profits, or streamline your business with the help of Big Data? Get in touch with us.
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