Very large, unstructured, volatile data sets lead to complicated and sometimes messy information. This is why according to worldwide research 85 percent of Fortune 500 businesses will not be able to use Big Data effectively (until 2015) to create a competitive advantage. Collecting data and analyzing it is not enough, as data streams are expected to generate the right conclusions at the right time. The problem is that almost 80 percent of the data is unstructured and polluted with useless data. However, some businesses have pioneered the use of Big Data and have thereby profited from it.
WalMart has made their suppliers completely responsible for the replenishment of products, informed by WalMart’s management system. The vendors are able to replenish the products at the right moment. Once the products are sold at the counter of WalMart, the replenishment process checks for stock levels falling below a certain value. Walmart is thereby the leader in Commercial Big-Data applications.
Buzzcapture: The algorithms of this business sort online conversations about clients such as ING and Vodafone based on relevance, and can even estimate whether conversations are angry or happy. It thereby often knows disturbances before its clients do.
Erasmus MC:The Erasmus University Medical Center Rotterdam works with DNA sequencing techniques, which can provide almost one and a half terabytes of information about only one tumor. It has developed a data model which has significantly speed up the response time in gathering this information. This makes cancer research at the Eramus MC much more efficient than before.
Cablecom: By analyzing the timing of the subscription cancellation of Cablecom (a telecommunications company), it has been able to reduce the number of cancellations in one year from 20 to 5 percent by offering clients a better deal when they might be contemplating canceling their subscription.
IBM: A selected group of drivers are testing IBM’s ‘Traffic Prediction Tool’, an app which uses GPS-data on the drivers’ driving habits, which can be personalized to give advice for the optimal route to their desired destination.
Rolls-Royce: this company has attached sensors to its engines, which relay real-time performance data to its central database using ETL software. The company is now able to predict accurately when an engine needs repairs or maintenance.
Li&Fung: this Chinese supply-chain operator is one of the largest in the world, and their real-time processed transaction information means they are a very accurate estimator for economic development. Investment analysts gladly pay for this kind of information.
Equens: together with the Fraud Detection Expertise Center, Equens, a payment processor, has developed a system which analyzes transactions with lightning speed so as to detect the location of the skimming of bankcards, and also blocking these skimmed bankcards with immediate effect.
Capital One: This credit card company has developed algorithms which use a ‘predictive optimization engine’, based on previous website visits, which can estimate the social rank and income of a Capital One website visitor, thereby advertising only certain deals to them.
Visa: its use of novel and highly effective software has meant that it has been more efficient in managing its data streams, by decreasing the time taken to analyze all its transactions from one month to 13 minutes using the new Hadoop system from Apache.
Kaggle: a start-up which organizes competitions whereby participants must make extraordinary predictions by analyzing large data sets using Business Intelligence software solutions. This increases the incentive for companies to analyze their data efficiently.
Nestlé: much of its data about clients, suppliers and resources was outdated, incomplete and even incorrect or had duplicates. By using new information systems to clean up this mess, Nestlé has saved an estimated total of one billion dollars the year.
Please let us know which company in your view is the smartest and why.
