Business Analytics

Big Data and Analytics: Game Theory in Practice

2012-01-10T12:36:00.001-06:00

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?

2012-01-05T07:16:00.000-06:00

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

2011-12-28T09:46:00.000-06:00

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

2011-02-27T07:42:00.002-06:00

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

2011-02-04T14:12:00.000-06:00

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

2011-02-01T19:19:00.002-06:00

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

2011-02-01T10:03:00.000-06:00

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?

2011-01-30T07:58:00.000-06:00

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

Predictive Analytics Summit 2011: Innovations in Marketing Analytics, Social Media, Healthcare, Energy, and Optimization

2011-01-23T08:26:00.001-06:00

I will be a feature speaker in the Predictive Analytics Innovation Summit 2011- San Diego – February, 24 & 25. My topic will be innovation in marketing analytics, social media, healthcare, energy, and optimization. the abstract is:

Local and global markets are changing more rapidly than ever before, and companies’ ability to predict those changes before they occur is vital. Social media adds a faster component to CRM, loyalty programs, and web analytics data allowing detection algorithms with 3D visualizations in mobile devices. The healthcare industry uses a boosting algorithm to improve care and disease management and to detect fraud. The energy industry uses smart meters analytics to conduct virtual audits and real-time demand side management. Predictive analytics intelligent agents are revolutionizing optimization issues in business analytics.

Overview: http://www.theiegroup.com/PA_Brochure.pdf

I would be very interested to gauge your interest in attending.

You'd be in excellent company. Confirmed Speakers Include:

- Alberto Roldan, Founder Business Analytics Group

- Senior Vice President, Analytics, Citi Bank

- Director, Marketing Analytics, National Geographic

- Director, Web & Mobile Analytics, USAA

- Director Data Insights, Dominos

- Director, Analytics, Manpower

If interested in attending contact me at: alberto.roldan@cognizant.com

Be Part of the Future and Not the Past

2011-01-20T09:24:00.000-06:00

This article about a 14 year old that designed the most popular free app for iTunes, Bubble Ball, a "physics puzzle game" for Apple devices is an example of how companies should tune to the younger generation to thrive in this rapidly changing market conditions. In my predictions for 2011 I emphasized the need for companies to listen to the 9-30 year old poluplation:

"Finally, my last prediction: in order to flourish and quickly adapt to changes in these rapidly changing economic times, we need to carefully listen to those that are our future. The examples from Siemens Competition (speech recognition technology), Gap (social media), and visualizations (web-based games) are common technologies used by the 9-to-30-year-old population. One of my main roles as an innovator is to listen to those voices and use my experience to provide guidance in implementing those new technologies and methodologies for businesses. A warning and advice to companies: listen carefully to those that represent our future. The future belongs to them, and our job is to provide guidance based on our experience." http://atomai.blogspot.com/2010/12/trends-in-business-analytics-for-2011.html

Survey: midsize businesses investing heavily in analytics, cloud

2011-01-17T07:55:00.000-06:00

This article summarizes the IBM surveys for midsized business and their investments in analytics. Interestingly, companies will be buying the software but they will be needing help in the integration and implementation of analytics models.

IEEE ICDM 2011 : IEEE International Conference on Data Mining

2011-01-16T10:58:00.000-06:00

IEEE ICDM 2011 : IEEE International Conference on Data Mining

A data mining approach for classifying DNA repair genes into ageing-related or non-ageing-related

2011-01-15T08:41:00.000-06:00

This classification technique used for DNA genes is applicable to marketing analytics, including social media analytics. The basic concept is that you separate your population into two different populations (i.e. control and experiment populations). Then you profile both population and compared them by attributes.

Google’s Schmidt on Open Source and Health IT

2011-01-12T11:02:00.000-06:00

We have developed a healthcare analytics predictive solution that includes care management, disease management, claims processing, utilization review, and fraud and abuse. We have found that we can precisely identify and segment large populations using data mining and predictive modeling techniques. Our solution is technology neutral can can be implemented using open source technologies.

If interested, please contact me at: alberto.roldan@cognizant.com

Smart grid analytics – a marketing opportunity

2011-01-12T10:44:00.000-06:00

At Cognizant Technologies we developed a successful analytics models using a universe of 1.2 million smart meters. We determine that we could accurately predict meter failures within a 30-45 days interval. Also, we could predict meter outage, and spike in consumption within a -1 to -3 hours interval. Our smart grid analytics solution is technology neutral and is applicable to any smart grid meters. It is cost effective for electric utilities spending a couple of dollars per meter, and hence the ROI is high.

If you want more information please contact me at: alberto.roldan@cognizant.com

By 2014, Shifts in Analytics Spending, BI Delivery

2011-01-09T08:44:00.000-06:00

Gartner's prediction about the shift of spending in analytics from software vendors to integrators is a recognition that companies need experts for predictive modeling and data mining. This is an important shift since in the past some companies thought that they only needed the software and not the expertise.

Why Is Facebook Worth $50 Billion? Check Out These Charts.

2011-01-07T13:23:00.000-06:00

Check this article in Forbes. A couple of weeks ago I wrote an article about trends in 2011 in business analytics. One of the trends that I mentioned was the acceleration in change management that social media has introduced must be carefully managed using advanced business analytics techniques (See, http://atomai.blogspot.com/2010/12/trends-in-business-analytics-for-2011.html). As you look at the charts in the Forbes article we must remember that Yahoo was incorporated in 1995, Google in 1998, and Facebook in 2004!

Top Conferences in Data Mining

2011-01-03T11:17:00.000-06:00

This link is for the top conferences in data mining.

Social Media

2010-12-31T09:29:00.000-06:00

Good blog on social media, analytics tools and marketing research. It gives the Social Media fundamentals in these areas.

Analytics and In-Memory Databases are Changing Data Centers

2010-12-31T09:06:00.000-06:00

For real-time analytics with large data volume this is a solution. My first exposure to this technology was about 18 months and I was impressed with its capabilities.

Another solution for realt-time analytics is the use of intelligent agents (think about the crawlers that are currently used but with some embedded analytics capabilities added-on to the recognition and identification algortihmns). I wrote an article about this in 2007: http://atomai.blogspot.com/2007/03/application-of-data-mining-and.html

In-memory databases analytics and intelligent agents are not mutually exclusive. If anything, these technologies are complementary in nature.

Data Mining Awards 2010

2010-12-30T08:41:00.002-06:00

Bringing Down the High Cost of Business Forecasting

2010-12-30T08:39:00.000-06:00

Excellent and on point article by MIT Review about the decreasing costs of business analytics using cloud computing analytics tools.

Robotic Surgery and Business Analytics

2010-12-26T11:41:00.000-06:00

Robotic Surgey and Business Analytics
by Alberto Roldan
Copyright 2010 Alberto Roldan

Imagine a future where we can use the techniques, technologies, and methodologies of robotic surgery in business analytics. For example:

What if we can "see", diagnosed, and repair the health of a business using 3D visualizations, predictive algorithms, and statistical control processes?
What if we could in detail the good parts of our business and compared it with the diseased or needed repair part of our business real-time?
What if we can monitor the different components of the health of a company (i.e., financial, operational, marketing, CRM, and social media) in real time while we are making strategic and tactical decisions.

The surgical outcomes of robotic surgery is less pain and faster recovery. We trust a complex organism as the human body to robotic surgery. What is preventing us to use the same science, technology, and matehmatical methods in business analytics? I believe that we are living in the future, because the future is now.

Click to the link above and tell me if you are interested.

Contact me at atomanalytics@gmail.com

Trends in Business Analytics for 2011: Alberto's Predictions

2010-12-16T08:19:00.004-06:00

There are three main trends that we can see occurring in 2011 across all industries and regardless of company size: (a) a large increase in volume of work, (b) utilization of social media as a key data source, and (c) challenges in implementation and innovation. First, the year 2011 will bring a tremendous increase in the volume of work in business analytics. Specifically, the area of predictive analytics had an increased momentum in the last half of 2010 that will carry to 2011 without any abatement in sight. My prediction is that companies will increase their 2011 appetite for predictive analytics by over 200% from 2010.

The need for more efficient ways to do work and adapt to swift changes in the economic environment will be feeding the craving for companies to use business analytics. Some of the accompanying challenges that this increased appetite for predictive analytics will include the following:

Prioritization of analytics projects to align with corporate strategic and tactical objectives
Analytic resources identification - the profiling of individuals that know predictive modeling technique
Institutionalization of budgeting for analytics projects , or no more unplanned budget for analytics projects

Whether business analytics resides in the IT or business organization, companies will need to modify their business models to reflect the contributions and needs of an analytics organization. Companies need to decide whether they will bring analytics talent by acquisitions, hiring, or by outsourcing. Offshoring will be substantially different for IT than for analytics (rate cards, project management, and resources). Adjustments on delivery expectations for analytics projects may be needed since the analytics portion of a project can be a short-term exercise, but the enterprise implementation for the same project could be a long-term project.

Social media will become an even more important key data source. It will be used to reduce the time that it takes to predict trends affecting companies and their competitors. Companies that successfully leverage analytics in social media to detect future trends, and make changes to their strategy, will differentiate in the marketplace by using “swift insights” to quickly adapt to changing market conditions. The best example to understand the importance of swift insights is the experience of Coca-Cola vis-à-vis Gap. In 1985 Coca-Cola introduced a new coke formula, and it took them nearly three months to return to their original formula after a public outcry. On the other hand, Gap introduced its new logo, and the public backlash was so pronounced in the social media that one week later they returned to their original logo. In mathematical terms this mean that social media accelerated the identification of the need for change by eleven times (11x). In other words, if an average car ran at 50 miles in 1985, it will run at 550 miles in 2010.

The involvement of business personnel from companies will become essential in defining the social media analytics strategy, and for testing the results of any analytics project. This involves additional time commitments that must be managed both strategically and operationally. A combination of savvy, innovative, and experienced staff in consulting, technology, finance, and analytics skills will become critical in 2011 for companies to successfully integrate social media analytics into their business models. Any licensed driver can drive a car at 50 miles per hour, but only skilled experts can maneuver a car at 550 miles per hour.

The areas of innovation and implementation are connected by a combination of best practices and repeatable processes in best of breed companies. Enterprise analytics implementation requires a combination of a knowledge of statistics, analytical tools, and optimization techniques. Companies must guard against unwise investments in analytics by following best practices: references, due diligence, proof of value, pilot or POC, evaluation, budgeting, project planning, and implementation. Once the analytic problems have been defined and aligned with strategic goals, companies should look at their internal project planning process to ensure the availability of right resources, skills, and budget.

Planning a phased approach is recommended in all analytic analytics projects. This allows for the evaluation of the business lift, in addition it gives time for improvements and modifications that are department and geographically specific. The key for planning analytics capabilities within a company is to build a small but strong foundation of business, technical, and analytics skills and then move from small projects to larger projects.

The integration of technology innovations with analytics will be a crucial test for many companies in 2011 and beyond. There are three main technologies that will make an impact in the way we do business in 2011: mobile devices, visualization, and speech technologies. The delivery of predictive analytics results using mobile devices, like the iPad, tablets, and smart phones, allows executives and field personnel to have access to swift insights. Those insights will allow decision makers at all levels of a company to know the impact of their decisions in revenues, costs, and profitability.

The ability to use analytics and mobile devices to deliver filtered and ready to act information (converting data into information) will depend on innovative visualization techniques. The screen space in mobile devices is smaller than laptops and PCs, hence the need for smarter visualizations. The use of spreadsheets is not efficient in smart phones. For companies that have hundreds of products, the representation of multiple dimensions or variables (i.e., predicted revenues, profits, and commissions), the use of line or bar charts also have a limited use. The use of interactive 3D visualizations in mobile devices to represent analytics outcomes will become a new breakthrough in the business world. 3D visualizations and predictions are common practice in web-based games, and those algorithms will be integrated into the business world in 2011.

Speech technology is another innovation that will be making its mark in 2011 and beyond. In December 2010 two high school students won a price at the Siemens Competition by developing a speech recognition algorithm that can detect a speaker’s emotion better than any current technology. Imagine how many errors individuals make when they are in a hurry, or otherwise distracted. The business impact of preventable errors could be billions of dollars annually using a combination of this speech recognition technology and predictive analytics outcomes, all delivered through mobile devices.

Finally, my last prediction: in order to flourish and quickly adapt to changes in these rapidly changing economic times, we need to carefully listen to those that are our future. The examples from Siemens Competition (speech recognition technology), Gap (social media), and visualizations (web-based games) are common technologies used by the 9-to-30-year-old population. One of my main roles as an innovator is to listen to those voices and use my experience to provide guidance in implementing those new technologies and methodologies for businesses. A warning and advice to companies: listen carefully to those that represent our future. The future belongs to them, and our job is to provide guidance based on our experience.

My wish to companies for the year 2011: be the future not the past. Companies need to be open to new ideas and new ways to do business using analytics. Learn from the Blockbuster-Netflix proposed partnership in 2000. Blockbuster laughed Netflix out of their office thinking that the online subscribe service model would not be successful in the movie rental business. Now Netflix is a thriving business with 16 million members, while Blockbuster is in bankruptcy with $900 million in debt.

Smart-grid analytics to be $4 billion industry

2010-12-03T07:44:00.002-06:00

I just recently completed a sucessful predictive analytics project in smart grid analytics for a utility with about 1 million smart meters. The methodology developed allow us to predict meter events; as well as power outages and spike in consumption at the meter level. See, http://atomai.blogspot.com/2010/11/smart-grid-business-analytics-adding.html

For additional details contact me.