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

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

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

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

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

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

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

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

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

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.

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

This link is for the top conferences in data mining.