Big Data and Analytics: Game Theory in Practice

This new year I have decided to concentrate in big data and advanced analytics.  Specifically, I am emphasizing the area of game theory and big data to give business insights in the area of "what if" scenarios.  This article inThe Economist on Modelling Behaviour is a good starting point. 

The objective is how to provide business insights in a rapidly changing world with big data challenges.  One of my proposed solutions is to adapt or use game theory in business analytics.  I had the fortune and privilege to be trained in game theory by Dr. Allen Whiting in the mid-1970s.  Game theory has been around since the 1940s (although there are references for as long as 1713!) and is used in 2007 Hurwiczs, Maskin and Myerson were awarded awarded the Nobel Prize in Economics "for having laid the foundations of mechanism design theory."

I will always be in debt to Dr. Whiting (former Undersecretary of State in the Kennedy and Johnson administrations) for teaching me how to do analysis in a way that has become my livelihood since the 1976. Friendship like imagination has no limits!

Link: http://www.economist.com/node/21527025

Enjoy!

What's your Algortihm?

This is a good article that describe what do I do for a living and different business analytics applications.

Alberto’s Business Analytics Predictions for 2012

Alberto’s Business Analytics Predictions for 2012

2011 was a great year for business analytics across all industries. As business analytics projects proved their measurable value within companies, I believe that in 2012 we will continue to see a mathematical increase in the number of companies that use business analytics. My predictions for 2012 are not in order of importance.

1. Increased utilization of advanced analytics in retail, CPG, healthcare, energy, banking, and healthcare – These industries will continue to lead in incorporating advanced analytics in their day-to-day operations using real-time or near real-time systems. Education and understanding of how advanced analytics can help companies will increase within companies in strategic and tactical areas.

2. 3D visualization techniques used in gaming will become more prevalent in business analytics – Visual analytics will enhance dashboarding and reporting techniques currently used by companies due to its measurable lift in providing better business insights.

3. Decrease in the amount of time that it takes to successfully design, test and implement an advanced analytics project to no more than three months – As companies become more educated in the benefits of advanced analytics, tools, and resources, they will start demanding the streamlining of analytics projects so that they can “turn around in a quarter.”™

4. Enhanced integration of IT and business stakeholders – Business analytics will bring the long- sought goal of better integration between IT and business stakeholders within companies. Business analytics will become the bridge between IT and business stakeholders since it answers specific business questions that are implemented through the enterprise by the IT organization.

5. Resources with analytic skills will continue to be a hot commodity – Companies will seek these resources to incorporate them into their infrastructure. As the demand for these finite resources increases, the marketplace price will increase.

6. Outsourcing and Offshoring of analytic projects and resources – Companies will seek analytic business models that can turn projects around quickly and seamlessly within their infrastructure. They will discover that it takes a combination of analytics, IT, and project management skills to successfully implement an analytics project with measurable business lift. Outsourcing and offshoring models will become a more attractive alternative in terms of pricing and delivery.

7. IT organizations will continue to struggle with analytics projects – The learning curve of the differences and similarities between analytics and IT projects will continue to plague IT organizations, and outsourcing and offshoring delivery models will become more attractive methods to deal with these issues.

8. Analytics tools will continue to thrive in the marketplace – Companies will continue to purchase these tools to give them the ability to predict and segment their big data. Analytics appliances that are industry- and problem-specific will proliferate in the next 2-3 years.

9. Social media integration with transaction data will become a priority for business stakeholders and the IT organizations – Companies have a gut feeling that this data is important and that it will help them to better target their customers and decrease costs. Although companies will struggle with this integration issue, they will ultimately turn to using advanced analytic techniques for successful and measurable business lift integration.

10. Voice recognition and natural language software will become a major data integration issue – As companies increase the use of voice recognition software, integration of these massive amounts of data will become a challenging issue and they will turn to advanced analytic techniques to solve this issue.

11. Big data analytics will become a priority for companies – As companies acquire more and more data, the issue of how to get value of this data will become a priority for many companies. The difference between having big data and getting the most value of this data will become part of the strategic goals for many companies. Big data with actionable and measurable business insights will go hand-in-hand.

12. Continuous improvement and refreshing of predictive models and business segments – As companies implement predictive models and statistical valid segments within their organizations, the ability to improve and the need to know when and how to automatically refresh these models will become an issue for many IT organizations. Initially, companies will move to offshoring and outsourcing these tasks. In the longer term, IT organizations will look to automate these tasks, and they will incorporate techniques such as embedded analytics.

Innovation is alive and thriving in the area of analytics.  Applications in different industries, cross-utilization of techniques in different domains, and new optimization techniques are always improving.  The future belongs to the young generation and the role of my generation is to provide guidance so their dreams are realized.  Let us roll up our sleeves and work for a better and brighter future.  We are unleashing the power of the mind!

HR Analytics Conference in San Francisco, March 7-8

I will be the feature speaker on HR Predictive Analytics at the HR Planning and Analysis conference in San Francisco in March 7-8. I will cover predictive analytics in HR, a new management asset metric (the Workforce Turnover Efficiency ratio), an Employee Lifetime Cycle Measurement, and an organizational structure model to adapt HR metrics at the enterprise level.

Yahoo Labs Forms Group to Target Advertising

This is great news.  The downsize is that Yahoo Labs should have been using its capabilities to get into the business analytics world at least for the last 3 years, so they are behind the curve.  The good size is that once you know the science, IT, and mathematical techniques it is a matter of adding the business size to come with potential solutions.  Let me quote from an article that I wrote in 2008:

"The next step is akin to a chef putting together a gourmet meal by using the finest ingredients and tools of the trade. A conductor brings out the most expressive details of a classical piece while blending all the sounds of an orchestra as one exquisite experience.


"If anticipation is part of journey, I can hardly wait for the sounds and tastes that will come in the next 12 months when business, technology, and science merge to produce masterpieces to help solve complex business problems."
 
Unleashing the Power of the MInd!

Predictive Modeling Techniques Positively Impacting P&C Insurers' Bottom Line

Property and Casualty insurance companies have found that implementation of predictive analytics models impact rate accuracy by about 10%.  Other industries are not as advanced as the P&C industry mostly because they are at the "how would predictive modeling impact our ROI stage", or because they are looking at predictive software, but have not moved to implementation. Other companies are facing implementation issues when dealing with big data and multiple predictive models.  At the Predictive Analytics Innovation Summit I will be addressing the issue of optimization.

Managing the data deluge

This is one of the topics that I will be addressing at the Predictive Analytics Innovation Summit in San Diego, Feb 24-25.  My proposed solution for the predictive analytics issue of big data is to use intelligent agents that will decide when some of the thousands of models should be refreshed.

What will be the state of Analytics in 2020?

This is a great survey by Bruno Aziza, Director of Worldwide Strategy BI at Microsoft.  Interesting is how people in the field recognize that embedded analytics is the future (30%).  In order for this to happen the optimization of predictive models in large data sets is a must in oder to automate the prioritization of the refreshing of the predictive models.  I have found that this optimization issue can be solved by using predictive analytics intelligent agents that can be embedded.  If you want ot hear more about this optimization solution (predictive analytics intelligent agents) whether embedded or not, please contact me at atomanalytics@gmail.com

Alberto Roldan