Regulation – a class of Big Data apps

There are bad guys out there!

 

Going back to the gist of my last post, one of the pillars that underpinned de-regulation was the idea that companies would work in a ‘correct’ manner and regulate themselves. The truth is that this worked and still does work very well for 95% of companies but there are always bad pennies committing fraud or simply not being careful in accounting practices. Thanks to a few well known financial disasters, even before the global meltdown, the concept of re-regulation loomed large across many industries. There are many sets of rules that are now in place to bring governance to company business – some of the more well known include Sarbanes-Oxley and Basel II and III which have been around for a little while now. We might ask ourselves what do they have in common and the answer is that both and many more such initiatives, demand that very accurate and accountable numbers are produced quickly from very complex underlying data – the need for Business Intelligence rears its head once again and the term ‘Big Data’ can certainly be applied to some of these initiatives.

 

Re-regulation demands that some very complex numbers are delivered:

 

  • Quickly
  • Accurately
  • Transparently

 

 

Throw into the pot that the data needed often as not comes from tens or even hundreds of operational systems distributed across the world and that some of these initiatives need very complex predictive modelling and detailed segmentation and we see a new class of Big Data applications.

Big Data Use-cases – Insurance, Energy and Utilities, Travel and Hi-Tech

Big Data is still in its infancy stage of it’s life cycle and alike traditional EDW/BI, it will take couple years to be part of nervous system of an organization. From what I have seen recently, most of the real big data initiatives that are currently in Production are by start-ups and upcoming companies that are working on new product line around real-time analytics and integration. Some of them are actually offering their products through cloud as SAAS and specifically extending it to AAAS (Analysis as a Service). The Cloud and Big Data computing has opened a new market for innovators.

Let’s look at some of the use cases for few traditional industries here:

Big Data use-cases in Insurance Industry

At the recent insurance industry trade shows, “big data” was the talk of the floor. The broad, vague term means different things to different people, though, and like many buzzwords suffers a bit from overexposure. But most people see the potential of advanced data and analytics to make insurance operations more efficient and effective. Here are few of the use cases that are very relevant to Insurance industry and has high ROI potential

  • Fraud Detection & Analysis
  • Personalized Pricing:
  • Customer Sentiment Analysis
  • Catastrophic Planning
  • Call Detail Record
  • Loyalty Management
  • Social Media Analytics
  • Advertising and Campaign Management
  • Agents Analysis
  • Customer Value Management
  • Underwriting and Loss modeling

Big Data use-cases in Utility Industry:

With the proliferation of smart meters, utilities are finding themselves inundated with data as they build out the Internet-enabled, interactive power system called the smart grid. But according to Oracle survey, many utility companies have yet to exploit that data as they modernize the grid. “The average utility with at least one smart meter program in place has increased the frequency of its data collection by 180x– collecting data once every four hours as opposed to just once a month,” states the survey of 151 utility executives in the U.S. and Canada conducted in April. “Despite improvements, 45%of utilities still struggle to report information to business managers as fast as they need it and 50% miss opportunities to deliver useful information to customers”. Here are few of the use cases that’s candidate for big data implementation and analytics

  • Smart Meters – Notifications and Alerts,
  • Smart Meters – Real-time Usage Pattern Analysis
  • Smart Meters – Predictive Analysis for Distribution of power
  • Smart Grid – Weather Pattern and Real Time Usage and Distribution
  • Manage Disasters and Outages
  • Compliance Checks and Audits
  • Customer Sentiment Analysis
  • Customer Feedback and Call Detail Record Analysis

Big Data use-cases in ECommerce & Hi-Tech Digital Industry

  • Association and Complementary Products – Big Data can be used as input to recommendation engines within websites like Amazon or Buy.com that can increase average order size by recommending complementary products on real time basis based on predictive analysis for cross-selling.
  • Cross-channel analytics — sales attribution, average order value, lifetime value (e.g., how many in-store purchases resulted from a particular recommendation, advertisement or promotion).
  • Event analytics — what series of steps (golden path) led to a desired outcome (e.g., purchase, registration).
  • Right Offer at the Right Time
  • Next Best Offer – deploying predictive models in combination with recommendation engines that drive automated next best offers and tailored interactions across multiple interaction channels.
  • Large-scale click-stream analytics
  • Ad targeting, analysis, forecasting and optimization
  • Abuse and click-fraud prevention
  • Social graph analysis and profile segmentation
  • Campaign management and loyalty programs

Big Data use-cases in Travel Industry

Just think about every data point produced in one single business or pleasure trip, from the chosen time, airline choice, hotel destination, meals, entertainment decisions, and how that data can then be used to provide a deeper and richer consumer experience in a quicker and easier sale of services. As one industry publication points out it is the ability to personalize that will spur Big Data analytics and foster development of new applications and new services in the travel realm.

  • Personalized Pricing for Travel – Aviation, Hotels, Vacation Packages and Cars….
  • Customer Sentiment and Behavior Analysis
  • Customer Loyalty Management
  • Call Detail Record Analysis for Customer Experience
  • Traffic Pattern and Congestion Management
  • GPS Coordinated data processing for Geo-Fencing
  • Social Media – Advertising and Campaign Management
  • Social Media – Consumer Feedback and Interaction analysis

These are just few of the possibilities of big data use cases in these industries. Though the possibilities are endless, key to success is to have a strong framework for big data implementation and having the first step right in the direction.