![Predicting Airline Loyalty Churn - Cathay Pacific Marco Polo [Case Study]](https://www.smartdatacollective.com/wp-content/uploads/2017/07/airline-loyalty-300x150.jpg)
-300x200.jpg)
-300x71.jpg)
Transforming Data Into Action [PART 1]
Everywhere you look in tech today you’ll read or hear about big data and all the many uses businesses could get from it. Businesses do certainly need to become more data driven and in fact the business model for the Information Age is something we’ve referred to as “sense and respond.” Moving from the old “make – sell” business model to the new sense and respond model requires data across all your business functions.
Everywhere you look in tech today you’ll read or hear about big data and all the many uses businesses could get from it. Businesses do certainly need to become more data driven and in fact the business model for the Information Age is something we’ve referred to as “sense and respond.” Moving from the old “make – sell” business model to the new sense and respond model requires data across all your business functions. On the other end of that requirement we’re creating massive amounts of data every second so you’d think that it would be a simple matter to implement the sense and respond model. The problem though. is that having lot’s of data and needing lot’s of data leaves out an important part of this equation…the process of turning mountains of data into actionable information is just not simple.
- Banking payment fraud detection and investigation
- Public sector assigning law enforcement based on predicting where / when crimes are likely to happen
- Retail optimizing merchandise placement in stores
- Asset intensive industries monitor and analyze real time machine sensor data to predict and correct failures before they happen
- Insurance claims fraud detection
- Retail making purchase suggestions based on previous transactions and macro buying trends (although that has issues, see the next paragraph)
- Healthcare evidence based medicine
This idea of mass profiling is interesting, but it has to move beyond the personalization paradigm and stop classifying you into a segment. Segmentation is very popular but is an old concept that misses the mark in a world where my expectation is individualized. It actually is missing the missing the level of relevance that I expect now. With the growth of social web there’s a lot more individual data available and in many cases you have permission to use it. Socialytics is rapidly growing and providing some interesting tools to pull out that individual data. On the other side though, it’s not necessarily getting mapped into the transaction data and other “big data” that would provide a complete picture of my actions and beyond actions, into my behavior and wants / desires. The capability to move beyond personalization and into individualization is critical for building out experiences that meet expectations.
In the next post, I will look at a newish concept called small data. I think that perhaps the big data movement distracts us in some ways from what might be a much bigger revolution around mass democratization of data access and processing. Building out an ecosystem of data and people, or expanding the definition of the enterprise social network (ESN), may be the biggest win for companies.
Trending Now
Hot Posts
Big Data, Data Mining and Machine Learning: Deriving Value for Business
Subhankar Bhattacharjee - August 17, 2017
How Can Big Data Solve the Challenges of E-Commerce Personalization?
Jasmine Morgan - August 16, 2017Latest
Medical AI Isn’t Just Beneficial – It’s Becoming Necessary
August 19, 2017
Converting Analog Signals is Vital to the IoT
August 18, 2017
Popular
User Adoption – Resistance Is Futile, We Hope
January 10, 2012
![Transforming Data Into Action [PART 1]](https://www.smartdatacollective.com/wp-content/uploads/2017/05/SmartData-Collective.png)
You must log in to post a comment.