[Article] Six Business Benefits of Smart Analytics

  • By WSO2 Team
  • 19 Feb, 2017

Data has always been the heart of decision making, and in modern enterprises, every single action is a data point. Be it changes in temperature, a difference in action, or a change in markets, today’s businesses are at the center of a veritable flood of data.

Consider a brokerage firm. Stockbrokers, in order to be good at their jobs, must take the pulse thousands (if not millions) of transactions each day to understand what the market might do next. While the data is often available, the sheer volume and frequency of it is too much for any human to form a complete picture. The challenge, then, lies in translating data to actionable insight.

This is where analytics comes in. By harnessing the power of big data, analytics reduces this torrent to clearer, actionable insights, such as trends in stock trading and movements. This vastly improves the speed and efficiency at which decisions are made. Done right, however, analytics can enable better decision making - enterprises can create groundbreaking new products, understand pain points and optimization, and gain advantages in today’s markets.

Monitoring and analysis - for when humans aren’t enough

A study estimates that by 20241, the world's enterprise servers will process - annually - the digital equivalent of a stack of books extending all the way to Alpha Centauri, the closest star system to the Solar System. That's an incredible amount of data to collect and understand.

Enterprise analytics brings the ability to gather and analyze such large amounts of data at millisecond speeds. Consider, for example, how usage data for a system can be analyzed to dynamically distribute resources such as processing power to that system. Or how millions of web page views can be analyzed to see which ones generate sales on the website and how.

Bridging data and insight, it drives the split-second business intelligence required to understand anything from sensor data to financial transactions, distilling vast data sets to insights that can be understood and acted on by humans.

Detect even the smallest change and trigger immediate action

Every enterprise generates data in a constant state of motion: thousands of changes take place both within and without an organization, ranging from fields as diverse as marketplaces to healthcare to data from mobile and web applications.

Streaming analytics - the science of analyzing such data - brings with it the ability to correlate events in these data streams, detect patterns, and trigger responses. It allows you to capture perishable insights - situational changes that can only be detected in the moment of occurrence, and cannot be captured with traditional analytics, which often occur far too late.

Consider Experian, the global credit-checking giant. Experian analyzes customer data in real-time. This in turn, is fed to their marketing engine, which can offer tailored content to a customer at speeds faster than any human being.

By connecting the relevant data streams to the right software and services, this allows organizations to ceaselessly monitor flows of data and instantly react to changes - in anything from application interactions to product performance to stock market fraud.

Make more informed business decisions in complex scenarios

One of the biggest - and some would say the only - requirements of decision-making is accurate information.

Traditionally, decision making is driven by experience and intuition. However, analytics, with the ability to interrogate and visualize large volumes of information, brings about fact-based decision making. It allows one to separate the signal from the noise and detect answers and non-obvious solutions in record time. Businesses are able to better navigate complex situations, especially those where lots of variables are at play.

For example, the Coca-Cola company’s ‘Black Book’2 algorithms understand the 600-plus flavors of an orange, and analyze acidity, sweetness, weather patterns, expected yields, and calculate how to consistently deliver an identical flavor profile, regardless of the vast differences between batches of fruits.

Create radically new data-based products for your business

Data - and the analysis thereof - brings about the creation of services that would have been otherwise impossible. Take the case of Transport for London (TfL), for example, where analytics is not just a luxury - analytics systems process traffic data from the myriads of sensors and compute solutions for keeping traffic and people flowing smoothly throughout the city of London.

As insight becomes available, businesses unlock the ability to create entirely new products, solutions, and experiences. In TfL’s case, analytics not only makes traffic management more efficient: it also allows them to identify the travel times of passengers3, calculate peak times and adjust prices accordingly. It’s an inherent part of servicing the billion or so people who use TfL services while generating revenue for London.

Use location and contextual data to create better customer experiences

The new frontier for customer service - especially for large organizations - is personalization.

The most prominent examples are retailers like Amazon and Target, which use contextual data to adapt their front-ends to inbound customers. However, analytics doesn’t end there.

Consider West, which builds omnichannel customer interaction solutions. West’s challenge was to ensure that their systems - which collectively cater to 300 million users across the world - can respond intelligently to customers, regardless of whether they’re calling in or sending in text. To do this, they built a complex cloud platform that can seamlessly cater to any customer, handling everything from contextual awareness to voice biometrics - and this platform is monitored, its streams of customer data sorted for insight, with analytics. The possibilities are endless. For a detailed discussion on retail analytics see.

Extend your solutions to analyze the past, present and the future

Of course, with modern advances in analytics, it doesn’t stop at analyzing the past and the present. By conducting historical analysis on events in the past, and by using machine learning tools to build prediction models, it’s possible to achieve the holy grail of business insight - predicting what will happen next.

An excellent example is CVS Health4, which developed a system to predict what employees a customer might react best to. They analyzed customer characteristics and employee’s record of responses to those patterns of people to assign work, reportedly leading to a 30% increase in customer retention rate.

Bringing analytics to the enterprise

Analytics is primarily a tool of decision making, and in this process, enterprise analytics adds speed, accuracy and efficiency. It’s also capable of highlighting undervalued opportunities and reducing the element of human prejudice when making decisions.

The WSO2 Analytics platform, with its use of big data, streaming, historical and predictive analysis, allows businesses to tap into all of the possibilities discussed above. It allows businesses to analyze large data streams, react to changes in real-time, predict trends, and even open up new, domain-specific avenues for entirely new services and products.