The Knowledge Exchange / Business Analytics / Business at the speed of life: The era of real-time analytics

Business at the speed of life: The era of real-time analytics

Organisations are moving their focus from being product-centric to customer-centric. I recently spoke with the CIO of a leading Asian insurance company who discussed their CEO’s new mantra … the desire to focus on doing business at the speed of life. He went on to elaborate,

“Consumers today demand instant satisfaction; regardless of the occasion, whether it’s online purchases, money transfers, package tracking, social communication, and even over-the-counter purchases. Organisations have it tough trying to convey a relevant message in a timely fashion, especially considering the move towards acquiring knowledge using the web and social media, as well as the proliferation of marketing messages everywhere you look, flip and click. Consumers now expect a personalised, relevant and contextual customer experience. Organisations face a decreasing window of time to detect threats and take advantage of opportunity. The challenge facing us is how to combine ten years of ERP data, 20 years of customer history and combining that with the current customer interaction data. Add to this that some of that data is unstructured and it quickly becomes apparent that our information technology environment and our enterprise data warehouse simply was not designed for this real-time contextual focus.”

This reality is where many organisations find themselves today. Industry leaders see big data as an opportunity and high-performance analytics (HPA) as the enabler to gaining competitive advantage. The focus is how to bring analytical insight to the point of decision, whether that be through the sales team, customer service representatives, ATMs, websites or other operational applications.

The recipe to great customer experience

Organisations that are successfully delivering great customer experience through real-time insights are consistently:

  • Accurate. Poor insight, sped up, means angry customers faster. Increasing accuracy of insight requires analysing existing structured data (source of truth) and unstructured data together. It means looking at all of the data not just sampling the data.
  • Event-driven. Doing business at the speed of life means we need to understand, predict and listen for the life stage triggers. Knowledge of when and why a customer is interacting with you is critical to improving your cut-through. The opportunity is not to make an offer, but to make the right offer in real-time. We have all received a credit card offer in the mail. Somewhere there was an event that was captured and the offer was relevant at that point in time. Three weeks later it’s spam.
  • Empowering the channel. Operationalisation and delivery of insight to the interaction points with your customers is vital to success. Some have labeled this the consumerisation or democratisation of analytics. It could be as simple as a popup on your website, a dynamic script for your call centre representatives or a salesman looking at location based reports on a tablet. Placing insight in the hands of those who make decisions about your business every day is the real-time analytics pay off.

HPA delivers insight at the speed of life

HPA enables organisations to drive real-time competitive advantage in three key ways:

  1. Ability to look at all the data– Improved accuracy requires the ability to aggregate structured data from your enterprise data warehouse and unstructured data from inside the firewall (email and voice) and outside sources (social). HPA embraces technologies like Hadoop to bring unified insight.
  2. Operationalisation of insight– Delivering insight faster is crucial for organisations to take advantage of that ever-shrinking window of opportunity. Shortening the decision cycle requires the ability to expose the insight as decision services that can be embedded in applications like your CRM system, online store and website. HPA manages the end-to-end data-to-value process allowing the velocity to increase exponentially. This is achieved by capturing, transforming, and storing data, and performing advanced analytics over in-memory storage to provide pure speed while managing larger datasets.
  3. Mobility – It is paramount that the insights can be placed into the hands of those interacting with customers. As such the ability to support mobile delivery by web and native applications means the right insight gets to the right person at the right time … and in the right location.

Real-time analytics is the enabler to a customer-centric strategy.

So where do you start? Look for areas where you can bring structure to a key decision making process, that positively impacts the customer. The challenge is how to do this profitably, and that’s where analytics comes in. Here are some examples to kick-start your thinking. You could offer:

  • Real-time personlised marketing offers to a segment of one at the point of sale. Include detail on location and type of transaction to bring more context and relevance to the offer.
  • Predictive maintenance of assets affecting customer experience. Analyse machine data that looks for the beginning of historical fault patterns, e.g., electricity grids, telecommunication towers, ATMs, production lines.
  • Individual risk-based pricing in insurance. Highly personalised policies can help differentiate you in the market while looking at greater profitability in the long-term.
  • Disruption management in transport and logistics. Understand the ripple effect of an error and re-coordinate the different assets and resources to achieve the best possible outcome for the customer and your bottom line. Oh and do it in real–time.

Read more about real-time analytics in the white paper, In-Memory Analytics for Big Data.

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