Carole-Ann’s 2011 Predictions for Decision Management

Carole-Ann’s 2011 Predictions for Decision Management

For Ajay Ohri on DecisionStats.com

What were the top 5 events in 2010 in your field?
  1. Maturity: the Decision Management space was made up of technology vendors, big and small, that typically focused on one or two aspects of this discipline.  Over the past few years, we have seen a lot of consolidation in the industry – first with Business Intelligence (BI) then Business Process Management (BPM) and lately in Business Rules Management (BRM) and Advanced Analytics.  As a result the giant Platform vendors have helped create visibility for this discipline.  Lots of tiny clues finally bubbled up in 2010 to attest of the increasing activity around Decision Management.  For example, more products than ever were named Decision Manager; companies advertised for Decision Managers as a job title in their job section; most people understand what I do when I am introduced in a social setting!
  2. Boredom: unfortunately, as the industry matures, inevitably innovation slows down…  At the main BRMS shows we heard here and there complaints that the technology was stalling.  We heard it from vendors like Red Hat (Drools) and we heard it from bored end-users hoping for some excitement at Business Rules Forum’s vendor panel.  They sadly did not get it
  3. Scrum: I am not thinking about the methodology there!  If you have ever seen a rugby game, you can probably understand why this is the term that comes to mind when I look at the messy & confusing technology landscape.  Feet blindly try to kick the ball out while superhuman forces are moving randomly the whole pack – or so it felt when I played!  Business Users in search of Business Solutions are facing more and more technology choices that feel like comparing apples to oranges.  There is value in all of them and each one addresses a specific aspect of Decision Management but I regret that the industry did not simplify the picture in 2010.  On the contrary!  Many buzzwords were created or at least made popular last year, creating even more confusion on a muddy field.  A few examples: Social CRM, Collaborative Decision Making, Adaptive Case Management, etc.  Don’t take me wrong, I *do* like the technologies.  I sympathize with the decision maker that is trying to pick the right solution though.
  4. Information: Analytics have been used for years of course but the volume of data surrounding us has been growing to unparalleled levels.  We can blame or thank (depending on our perspective) Social Media for that.  Sites like Facebook and LinkedIn have made it possible and easy to publish relevant (as well as fluffy) information in real-time.  As we all started to get the hang of it and potentially over-publish, technology evolved to enable the storage, correlation and analysis of humongous volumes of data that we could not dream of before.  25 billion tweets were posted in 2010.  Every month, over 30 billion pieces of data are shared on Facebook alone.  This is not just about vanity and marketing though.  This data can be leveraged for the greater good.  Carlos pointed to some fascinating facts about catastrophic event response team getting organized thanks to crowd-sourced information.  We are also seeing, in the Decision management world, more and more applicability for those very technology that have been developed for the needs of Big Data – I’ll name for example Hadoop that Carlos (yet again) discussed in his talks at Rules Fest end of 2009 and 2010.
  5. Self-Organization: it may be a side effect of the Social Media movement but I must admit that I was impressed by the success of self-organizing initiatives.  Granted, this last trend has nothing to do with Decision Management per se but I think it is a great evolution worth noting.  Let me point to a couple of examples.  I usually attend traditional conferences and tradeshows in which the content can be good but is sometimes terrible.  I was pleasantly surprised by the professionalism and attendance at *un-conferences* such as P-Camp (P stands for Product – an event for Product Managers).  When you think about it, it is already difficult to get a show together when people are dedicated to the tasks.  How crazy is it to have volunteers set one up with no budget and no agenda?  Well, people simply show up to do their part and everyone has fun voting on-site for what seems the most appealing content at the time.  Crowdsourcing applied to shows: it works!  Similar experience with meetups or tweetups.  I also enjoyed attending some impromptu Twitter jam sessions on a given topic.  Social Media is certainly helping people reach out and get together in person or virtually and that is wonderful!

A segment of a social network
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What are the top three trends you see in 2011?

  1. Performance:  I might be cheating here.   I was very bullish about predicting much progress for 2010 in the area of Performance Management in your Decision Management initiatives.  I believe that progress was made but Carlos did not give me full credit for the right prediction…  Okay, I am a little optimistic on timeline…  I admit it…  If it did not fully happen in 2010, can I predict it again in 2011?  I think that companies want to better track their business performance in order to correct the trajectory of course but also to improve their projections.  I see that it is turning into reality already here and there.  I expect it to become a trend in 2011!
  2. Insight: Big Data being available all around us with new technologies and algorithms will continue to propagate in 2011 leading to more widely spread Analytics capabilities.  The buzz at Analytics shows on Social Network Analysis (SNA) is a sign that there is interest in those kinds of things.  There is tremendous information that can be leveraged for smart decision-making.  I think there will be more of that in 2011 as initiatives launches in 2010 will mature into material results.
    5 Ways to Cultivate an Active Social Network
    Image by Intersection Consulting via Flickr
  3. Collaboration:  Social Media for the Enterprise is a discipline in the making.  Social Media was initially seen for the most part as a Marketing channel.  Over the years, companies have started experimenting with external communities and ideation capabilities with moderate success.  The few strategic initiatives started in 2010 by “old fashion” companies seem to be an indication that we are past the early adopters.  This discipline may very well materialize in 2011 as a core capability, well, or at least a new trend.  I believe that capabilities such Chatter, offered by Salesforce, will transform (slowly) how people interact in the workplace and leverage the volumes of social data captured in LinkedIn and other Social Media sites.  Collaboration is of course a topic of interest for me personally.  I even signed up for Kare Anderson’s collaboration collaboration site – yes, twice the word “collaboration”: it is really about collaborating on collaboration techniques.  Even though collaboration does not require Social Media, this medium offers perspectives not available until now.

Brief Bio-

Carole-Ann is a renowned guru in the Decision Management space. She created the vision for Decision Management that is widely adopted now in the industry. Her claim to fame is the strategy and direction of Blaze Advisor, the then-leading BRMS product, while she also managed all the Decision Management tools at FICO (business rules, predictive analytics and optimization). She has a vision for Decision Management both as a technology and a discipline that can revolutionize the way corporations do business, and will never get tired of painting that vision for her audience. She speaks often at Industry conferences and has conducted university classes in France and Washington DC.

Leveraging her Masters degree in Applied Mathematics / Computer Science from a “Grande Ecole” in France, she started her career building advanced systems using all kinds of technologies — expert systems, rules, optimization, dashboarding and cubes, web search, and beta version of database replication – as well as conducting strategic consulting gigs around change management.

She now tweets as @CMatignon, blogs at blog.sparklinglogic.com and interacts at community.sparklinglogic.com.

She started her career building advanced systems using all kinds of technologies — expert systems, rules, optimization, dashboarding and cubes, web search, and beta version of database replication.  At Cleversys (acquired by Kurt Salmon & Associates), she also conducted strategic consulting gigs mostly around change management.

While playing with advanced software components, she found a passion for technology and joined ILOG (acquired by IBM).  She developed a growing interest in Optimization as well as Business Rules.  At ILOG, she coined the term BRMS while brainstorming with her Sales counterpart.  She led the Presales organization for Telecom in the Americas up until 2000 when she joined Blaze Software (acquired by Brokat Technologies, HNC Software and finally FICO).

Her 360-degree experience allowed her to gain appreciation for all aspects of a software company, giving her a unique perspective on the business.  Her technical background kept her very much in touch with technology as she advanced.

She also became addicted to Twitter in the process.  She is active on all kinds of social media, always looking for new digital experience!

Outside of work, Carole-Ann loves spending time with her two boys.  They grow fruits in their Northern California home and cook all together in the French tradition.

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Social Networks Hype Cycle
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Interview Ajay Ohri Decisionstats.com with DMR

From-

http://www.dataminingblog.com/data-mining-research-interview-ajay-ohri/

Here is the winner of the Data Mining Research People Award 2010: Ajay Ohri! Thanks to Ajay for giving some time to answer Data Mining Research questions. And all the best to his blog, Decision Stat!

Data Mining Research (DMR): Could you please introduce yourself to the readers of Data Mining Research?

Ajay Ohri (AO): I am a business consultant and writer based out of Delhi- India. I have been working in and around the field of business analytics since 2004, and have worked with some very good and big companies primarily in financial analytics and outsourced analytics. Since 2007, I have been writing my blog at http://decisionstats.com which now has almost 10,000 views monthly.

All in all, I wrote about data, and my hobby is also writing (poetry). Both my hobby and my profession stem from my education ( a masters in business, and a bachelors in mechanical engineering).

My research interests in data mining are interfaces (simpler interfaces to enable better data mining), education (making data mining less complex and accessible to more people and students), and time series and regression (specifically ARIMAX)
In business my research interests software marketing strategies (open source, Software as a service, advertising supported versus traditional licensing) and creation of technology and entrepreneurial hubs (like Palo Alto and Research Triangle, or Bangalore India).

DMR: I know you have worked with both SAS and R. Could you give your opinion about these two data mining tools?

AO: As per my understanding, SAS stands for SAS language, SAS Institute and SAS software platform. The terms are interchangeably used by people in industry and academia- but there have been some branding issues on this.
I have not worked much with SAS Enterprise Miner , probably because I could not afford it as business consultant, and organizations I worked with did not have a budget for Enterprise Miner.
I have worked alone and in teams with Base SAS, SAS Stat, SAS Access, and SAS ETS- and JMP. Also I worked with SAS BI but as a user to extract information.
You could say my use of SAS platform was mostly in predictive analytics and reporting, but I have a couple of projects under my belt for knowledge discovery and data mining, and pattern analysis. Again some of my SAS experience is a bit dated for almost 1 year ago.

I really like specific parts of SAS platform – as in the interface design of JMP (which is better than Enterprise Guide or Base SAS ) -and Proc Sort in Base SAS- I guess sequential processing of data makes SAS way faster- though with computing evolving from Desktops/Servers to even cheaper time shared cloud computers- I am not sure how long Base SAS and SAS Stat can hold this unique selling proposition.

I dislike the clutter in SAS Stat output, it confuses me with too much information, and I dislike shoddy graphics in the rendering output of graphical engine of SAS. Its shoddy coding work in SAS/Graph and if JMP can give better graphics why is legacy source code preventing SAS platform from doing a better job of it.

I sometimes think the best part of SAS is actually code written by Goodnight and Sall in 1970’s , the latest procs don’t impress me much.

SAS as a company is something I admire especially for its way of treating employees globally- but it is strange to see the rest of tech industry not following it. Also I don’t like over aggression and the SAS versus Rest of the Analytics /Data Mining World mentality that I sometimes pick up when I deal with industry thought leaders.

I think making SAS Enterprise Miner, JMP, and Base SAS in a completely new web interface priced at per hour rates is my wishlist but I guess I am a bit sentimental here- most data miners I know from early 2000’s did start with SAS as their first bread earning software. Also I think SAS needs to be better priced in Business Intelligence- it seems quite cheap in BI compared to Cognos/IBM but expensive in analytical licensing.

If you are a new stats or business student, chances are – you may know much more R than SAS today. The shift in education at least has been very rapid, and I guess R is also more of a platform than a analytics or data mining software.

I like a lot of things in R- from graphics, to better data mining packages, modular design of software, but above all I like the can do kick ass spirit of R community. Lots of young people collaborating with lots of young to old professors, and the energy is infectious. Everybody is a CEO in R ’s world. Latest data mining algols will probably start in R, published in journals.

Which is better for data mining SAS or R? It depends on your data and your deadline. The golden rule of management and business is -it depends.

Also I have worked with a lot of KXEN, SQL, SPSS.

DMR: Can you tell us more about Decision Stats? You have a traffic of 120′000 for 2010. How did you reach such a success?

AO: I don’t think 120,000 is a success. Its not a failure. It just happened- the more I wrote, the more people read.In 2007-2008 I used to obsess over traffic. I tried SEO, comments, back linking, and I did some black hat experimental stuff. Some of it worked- some didn’t.

In the end, I started asking questions and interviewing people. To my surprise, senior management is almost always more candid , frank and honest about their views while middle managers, public relations, marketing folks can be defensive.

Social Media helped a bit- Twitter, Linkedin, Facebook really helped my network of friends who I suppose acted as informal ambassadors to spread the word.
Again I was constrained by necessity than choices- my middle class finances ( I also had a baby son in 2007-my current laptop still has some broken keys :) – by my inability to afford traveling to conferences, and my location Delhi isn’t really a tech hub.

The more questions I asked around the internet, the more people responded, and I wrote it all down.

I guess I just was lucky to meet a lot of nice people on the internet who took time to mentor and educate me.

I tried building other websites but didn’t succeed so i guess I really don’t know. I am not a smart coder, not very clever at writing but I do try to be honest.

Basic economics says pricing is proportional to demand and inversely proportional to supply. Honest and candid opinions have infinite demand and an uncertain supply.

DMR: There is a rumor about a R book you plan to publish in 2011 :-) Can you confirm the rumor and tell us more?

AO: I just signed a contract with Springer for ” R for Business Analytics”. R is a great software, and lots of books for statistically trained people, but I felt like writing a book for the MBAs and existing analytics users- on how to easily transition to R for Analytics.

Like any language there are tricks and tweaks in R, and with a focus on code editors, IDE, GUI, web interfaces, R’s famous learning curve can be bent a bit.

Making analytics beautiful, and simpler to use is always a passion for me. With 3000 packages, R can be used for a lot more things and a lot more simply than is commonly understood.
The target audience however is business analysts- or people working in corporate environments.

Brief Bio-
Ajay Ohri has been working in the field of analytics since 2004 , when it was a still nascent emerging Industries in India. He has worked with the top two Indian outsourcers listed on NYSE,and with Citigroup on cross sell analytics where he helped sell an extra 50000 credit cards by cross sell analytics .He was one of the very first independent data mining consultants in India working on analytics products and domestic Indian market analytics .He regularly writes on analytics topics on his web site www.decisionstats.com and is currently working on open source analytical tools like R besides analytical software like SPSS and SAS.

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Keynote: Five Ways Predictive Analytics Cuts Enterprise Risk  

Eric Siegel, Ph.D., Program Chair, Predictive Analytics World

All business is an exercise in risk management. All organizations would benefit from measuring, tracking and computing risk as a core process, much like insurance companies do.

Predictive analytics does the trick, one customer at a time. This technology is a data-driven means to compute the risk each customer will defect, not respond to an expensive mailer, consume a retention discount even if she were not going to leave in the first place, not be targeted for a telephone solicitation that would have landed a sale, commit fraud, or become a “loss customer” such as a bad debtor or an insurance policy-holder with high claims.

In this keynote session, Dr. Eric Siegel reveals:

– Five ways predictive analytics evolves your enterprise to reduce risk

– Hidden sources of risk across operational functions

– What every business should learn from insurance companies

– How advancements have reversed the very meaning of fraud

– Why “man + machine” teams are greater than the sum of their parts for enterprise decision support

Length – 00:45:57 | Email to a Colleague

Price: $195

 

 

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Play video of session: Platinum Sponsor Presentation, Analytics: The Beauty of Diversity
Platinum Sponsor Presentation: Analytics – The Beauty of Diversity 

Anne H. Milley, Senior Director of Analytic Strategy, Worldwide Product Marketing, SAS

Analytics contributes to, and draws from, multiple disciplines. The unifying theme of “making the world a better place” is bred from diversity. For instance, the same methods used in econometrics might be used in market research, psychometrics and other disciplines. In a similar way, diverse paradigms are needed to best solve problems, reveal opportunities and make better decisions. This is why we evolve capabilities to formulate and solve a wide range of problems through multiple integrated languages and interfaces. Extending that, we have provided integration with other languages so that users can draw on the disciplines and paradigms needed to best practice their craft.

Length – 20:11 | Email to a Colleague

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Play video of session: Gold Sponsor Presentation Predictive Analytics Accelerate Insight for Financial Services
Gold Sponsor Presentation: Predictive Analytics Accelerate Insight for Financial Services 

Finbarr Deely, Director of Business Development,ParAccel

Financial services organizations face immense hurdles in maintaining profitability and building competitive advantage. Financial services organizations must perform “what-if” scenario analysis, identify risks, and detect fraud patterns. The advanced analytic complexity required often makes such analysis slow and painful, if not impossible. This presentation outlines the analytic challenges facing these organizations and provides a clear path to providing the accelerated insight needed to perform in today’s complex business environment to reduce risk, stop fraud and increase profits. * The value of predictive analytics in Accelerating Insight * Financial Services Analytic Case Studies * Brief Overview of ParAccel Analytic Database

Length – 09:06 | Email to a Colleague

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TOPIC: BUSINESS VALUE
Case Study: Monster.com
Creating Global Competitive Power with Predictive Analytics 

Jean Paul Isson, Vice President, Globab BI & Predictive Analytics, Monster Worldwide

Using Predictive analytics to gain a deeper understanding of customer behaviours, increase marketing ROI and drive growth

– Creating global competitive power with business intelligence: Making the right decisions – at the right time

– Avoiding common change management challenges in sales, marketing, customer service, and products

– Developing a BI vision – and implementing it: successful business intelligence implementation models

– Using predictive analytics as a business driver to stay on top of the competition

– Following the Monster Worldwide global BI evolution: How Monster used BI to go from good to great

Length – 51:17 | Email to a Colleague

Price: $195

 

 

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TOPIC: SURVEY ANALYSIS
Case Study: YMCA
Turning Member Satisfaction Surveys into an Actionable Narrative 

Dean Abbott, President, Abbott Analytics

Employees are a key constituency at the Y and previous analysis has shown that their attitudes have a direct bearing on Member Satisfaction. This session will describe a successful approach for the analysis of YMCA employee surveys. Decision trees are built and examined in depth to identify key questions in describing key employee satisfaction metrics, including several interesting groupings of employee attitudes. Our approach will be contrasted with other factor analysis and regression-based approaches to survey analysis that we used initially. The predictive models described are currently in use and resulted in both greater understanding of employee attitudes, and a revised “short-form” survey with fewer key questions identified by the decision trees as the most important predictors.

Length – 50:19 | Email to a Colleague

Price: $195

 

 

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TOPIC: INDUSTRY TRENDS
2010 Data Minter Survey Results: Highlights
 

Karl Rexer, Ph.D., Rexer Analytics

Do you want to know the views, actions, and opinions of the data mining community? Each year, Rexer Analytics conducts a global survey of data miners to find out. This year at PAW we unveil the results of our 4th Annual Data Miner Survey. This session will present the research highlights, such as:

– Analytic goals & key challenges

– Impact of the economy

– Regional differences

– Text mining trends

Length – 15:20 | Email to a Colleague

Price: $195

 

 

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Multiple Case Studies: U.S. DoD, U.S. DHS, SSA
Text Mining: Lessons Learned 

John F. Elder, Chief Scientist, Elder Research, Inc.

Text Mining is the “Wild West” of data mining and predictive analytics – the potential for gain is huge, the capability claims are often tall tales, and the “land rush” for leadership is very much a race.

In solving unstructured (text) analysis challenges, we found that principles from inductive modeling – learning relationships from labeled cases – has great power to enhance text mining. Dr. Elder highlights key technical breakthroughs discovered while working on projects for leading government agencies, including: Text Mining is the “Wild West” of data mining and predictive analytics – the potential for gain is huge, the capability claims are often tall tales, and the “land rush” for leadership is very much a race.

– Prioritizing searches for the Dept. of Homeland Security

– Quick decisions for Social Security Admin. disability

– Document discovery for the Dept. of Defense

– Disease discovery for the Dept. of Homeland Security

– Risk profiling for the Dept. of Defense

Length – 48:58 | Email to a Colleague

Price: $195

 

 

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Play video of session: Keynote: How Target Gets the Most out of Its Guest Data to Improve Marketing ROI
Keynote: How Target Gets the Most out of Its Guest Data to Improve Marketing ROI 

Andrew Pole, Senior Manager, Media and Database Marketing, Target

In this session, you’ll learn how Target leverages its own internal guest data to optimize its direct marketing – with the ultimate goal of enhancing our guests’ shopping experience and driving in-store and online performance. You will hear about what guest data is available at Target, how and where we collect it, and how it is used to improve the performance and relevance of direct marketing vehicles. Furthermore, we will discuss Target’s development and usage of guest segmentation, response modeling, and optimization as means to suppress poor performers from mailings, determine relevant product categories and services for online targeted content, and optimally assign receipt marketing offers to our guests when offer quantities are limited.

Length – 47:49 | Email to a Colleague

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Play video of session: Platinum Sponsor Presentation: Driving Analytics Into Decision Making
Platinum Sponsor Presentation: Driving Analytics Into Decision Making  

Jason Verlen, Director, SPSS Product Strategy & Management, IBM Software Group

Organizations looking to dramatically improve their business outcomes are turning to decision management, a convergence of technology and business processes that is used to streamline and predict the outcome of daily decision-making. IBM SPSS Decision Management technology provides the critical link between analytical insight and recommended actions. In this session you’ll learn how Decision Management software integrates analytics with business rules and business applications for front-line systems such as call center applications, insurance claim processing, and websites. See how you can improve every customer interaction, minimize operational risk, reduce fraud and optimize results.

Length – 17:29 | Email to a Colleague

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TOPIC: DATA INFRASTRUCTURE AND INTEGRATION
Case Study: Macy’s
The world is not flat (even though modeling software has to think it is) 

Paul Coleman, Director of Marketing Statistics, Macy’s Inc.

Software for statistical modeling generally use flat files, where each record represents a unique case with all its variables. In contrast most large databases are relational, where data are distributed among various normalized tables for efficient storage. Variable creation and model scoring engines are necessary to bridge data mining and storage needs. Development datasets taken from a sampled history require snapshot management. Scoring datasets are taken from the present timeframe and the entire available universe. Organizations, with significant data, must decide when to store or calculate necessary data and understand the consequences for their modeling program.

Length – 34:54 | Email to a Colleague

Price: $195

 

 

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TOPIC: CUSTOMER VALUE
Case Study: SunTrust
When One Model Will Not Solve the Problem – Using Multiple Models to Create One Solution 

Dudley Gwaltney, Group Vice President, Analytical Modeling, SunTrust Bank

In 2007, SunTrust Bank developed a series of models to identify clients likely to have large changes in deposit balances. The models include three basic binary and two linear regression models.

Based on the models, 15% of SunTrust clients were targeted as those most likely to have large balance changes. These clients accounted for 65% of the absolute balance change and 60% of the large balance change clients. The targeted clients are grouped into a portfolio and assigned to individual SunTrust Retail Branch. Since 2008, the portfolio generated a 2.6% increase in balances over control.

Using the SunTrust example, this presentation will focus on:

– Identifying situations requiring multiple models

– Determining what types of models are needed

– Combining the individual component models into one output

Length – 48:22 | Email to a Colleague

Price: $195

 

 

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TOPIC: RESPONSE & CROSS-SELL
Case Study: Paychex
Staying One Step Ahead of the Competition – Development of a Predictive 401(k) Marketing and Sales Campaign 

Jason Fox, Information Systems and Portfolio Manager,Paychex

In-depth case study of Paychex, Inc. utilizing predictive modeling to turn the tides on competitive pressures within their own client base. Paychex, a leading provider of payroll and human resource solutions, will guide you through the development of a Predictive 401(k) Marketing and Sales model. Through the use of sophisticated data mining techniques and regression analysis the model derives the probability a client will add retirement services products with Paychex or with a competitor. Session will include roadblocks that could have ended development and ROI analysis. Speaker: Frank Fiorille, Director of Enterprise Risk Management, Paychex Speaker: Jason Fox, Risk Management Analyst, Paychex

Length – 26:29 | Email to a Colleague

Price: $195

 

 

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TOPIC: SEGMENTATION
Practitioner: Canadian Imperial Bank of Commerce
Segmentation Do’s and Don’ts 

Daymond Ling, Senior Director, Modelling & Analytics,Canadian Imperial Bank of Commerce

The concept of Segmentation is well accepted in business and has withstood the test of time. Even with the advent of new artificial intelligence and machine learning methods, this old war horse still has its place and is alive and well. Like all analytical methods, when used correctly it can lead to enhanced market positioning and competitive advantage, while improper application can have severe negative consequences.

This session will explore what are the elements of success, and what are the worse practices that lead to failure. The relationship between segmentation and predictive modeling will also be discussed to clarify when it is appropriate to use one versus the other, and how to use them together synergistically.

Length – 45:57 | Email to a Colleague

Price: $195

 

 

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TOPIC: SOCIAL DATA
Thought Leadership
Social Network Analysis: Killer Application for Cloud Analytics
 

James Kobielus, Senior Analyst, Forrester Research

Social networks such as Twitter and Facebook are a potential goldmine of insights on what is truly going through customers´minds. Every company wants to know whether, how, how often, and by whom they´re being mentioned across the billowing new cloud of social media. Just as important, every company wants to influence those discussions in their favor, target new business, and harvest maximum revenue potential. In this session, Forrester analyst James Kobielus identifies fruitful applications of social network analysis in customer service, sales, marketing, and brand management. He presents a roadmap for enterprises to leverage their inline analytics initiatives and leverage high-performance data warehousing (DW) clouds and appliances in order to analyze shifting patterns of customer sentiment, influence, and propensity. Leveraging Forrester’s ongoing research in advanced analytics and customer relationship management, Kobielus will discuss industry trends, commercial modeling tools, and emerging best practices in social network analysis, which represents a game-changing new discipline in predictive analytics.

Length – 48:16 | Email to a Colleague

Price: $195

 

 

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TOPIC: HEALTHCARE – INTERNATIONAL TARGETING
Case Study: Life Line Screening
Taking CRM Global Through Predictive Analytics 

Ozgur Dogan,
VP, Quantitative Solutions Group, Merkle Inc

Trish Mathe,
Director of Database Marketing, Life Line Screening

While Life Line is successfully executing a US CRM roadmap, they are also beginning this same evolution abroad. They are beginning in the UK where Merkle procured data and built a response model that is pulling responses over 30% higher than competitors. This presentation will give an overview of the US CRM roadmap, and then focus on the beginning of their strategy abroad, focusing on the data procurement they could not get anywhere else but through Merkle and the successful modeling and analytics for the UK. Speaker: Ozgur Dogan, VP, Quantitative Solutions Group, Merkle Inc Speaker: Trish Mathe, Director of Database Marketing, Life Line Screening

Length – 40:12 | Email to a Colleague

Price: $195

 

 

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TOPIC: SURVEY ANALYSIS
Case Study: Forrester
Making Survey Insights Addressable and Scalable – The Case Study of Forrester’s Technographics Benchmark Survey 

Nethra Sambamoorthi, Team Leader, Consumer Dynamics & Analytics, Global Consulting, Acxiom Corporation

Marketers use surveys to create enterprise wide applicable strategic insights to: (1) develop segmentation schemes, (2) summarize consumer behaviors and attitudes for the whole US population, and (3) use multiple surveys to draw unified views about their target audience. However, these insights are not directly addressable and scalable to the whole consumer universe which is very important when applying the power of survey intelligence to the one to one consumer marketing problems marketers routinely face. Acxiom partnered with Forrester Research, creating addressable and scalable applications of Forrester’s Technographics Survey and applied it successfully to a number of industries and applications.

Length – 39:23 | Email to a Colleague

Price: $195

 

 

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TOPIC: HEALTHCARE
Case Study: UPMC Health Plan
A Predictive Model for Hospital Readmissions 

Scott Zasadil, Senior Scientist, UPMC Health Plan

Hospital readmissions are a significant component of our nation’s healthcare costs. Predicting who is likely to be readmitted is a challenging problem. Using a set of 123,951 hospital discharges spanning nearly three years, we developed a model that predicts an individual’s 30-day readmission should they incur a hospital admission. The model uses an ensemble of boosted decision trees and prior medical claims and captures 64% of all 30-day readmits with a true positive rate of over 27%. Moreover, many of the ‘false’ positives are simply delayed true positives. 53% of the predicted 30-day readmissions are readmitted within 180 days.

Length – 54:18 | Email to a Colleague

Price: $195

Brief Interview Timo Elliott

Here is a brief interview with Timo Elliott.Timo Elliott is a 19-year veteran of SAP Business Objects.

Ajay- What are the top 5 events in Business Integration and Data Visualization services you saw in 2010 and what are the top three trends you see in these in 2011.


Timo-

Top five events in 2010:

(1) Back to strong market growth. IT spending plummeted last year (BI continued to grow, but more slowly than previous years). This year, organizations reopened their wallets and funded new analytics initiatives — all the signs indicate that BI market growth will be double that of 2009.

(2) The launch of the iPad. Mobile BI has been around for years, but the iPad opened the floodgates of organizations taking a serious look at mobile analytics — and the easy-to-use, executive-friendly iPad dashboards have considerably raised the profile of analytics projects inside organizations.

(3) Data warehousing got exciting again. Decades of incremental improvements (column databases, massively parallel processing, appliances, in-memory processing…) all came together with robust commercial offers that challenged existing data storage and calculation methods. And new “NoSQL” approaches, designed for the new problems of massive amounts of less-structured web data, started moving into the mainstream.

(4) The end of Google Wave, the start of social BI.Google Wave was launched as a rethink of how we could bring together email, instant messaging, and social networks. While Google decided to close down the technology this year, it has left its mark, notably by influencing the future of “social BI”, with several major vendors bringing out commercial products this year.

(5) The start of the big BI merge. While several small independent BI vendors reported strong growth, the major trend of the year was consolidation and integration: the BI megavendors (SAP, Oracle, IBM, Microsoft) increased their market share (sometimes by acquiring smaller vendors, e.g. IBM/SPSS and SAP/Sybase) and integrated analytics with their existing products, blurring the line between BI and other technology areas.

Top three trends next year:

(1) Analytics, reinvented. New DW techniques make it possible to do sub-second, interactive analytics directly against row-level operational data. Now BI processes and interfaces need to be rethought and redesigned to make best use of this — notably by blurring the distinctions between the “design” and “consumption” phases of BI.

(2) Corporate and personal BI come together. The ability to mix corporate and personal data for quick, pragmatic analysis is a common business need. The typical solution to the problem — extracting and combining the data into a local data store (either Excel or a departmental data mart) — pleases users, but introduces duplication and extra costs and makes a mockery of information governance. 2011 will see the rise of systems that let individuals and departments load their data into personal spaces in the corporate environment, allowing pragmatic analytic flexibility without compromising security and governance.

(3) The next generation of business applications. Where are the business applications designed to support what people really do all day, such as implementing this year’s strategy, launching new products, or acquiring another company? 2011 will see the first prototypes of people-focused, flexible, information-centric, and collaborative applications, bringing together the best of business intelligence, “enterprise 2.0”, and existing operational applications.

And one that should happen, but probably won’t:

(4) Intelligence = Information + PEOPLE. Successful analytics isn’t about technology — it’s about people, process, and culture. The biggest trend in 2011 should be organizations spending the majority of their efforts on user adoption rather than technical implementation.                 About- http://timoelliott.com/blog/about

Timo Elliott is a 19-year veteran of SAP BusinessObjects, and has spent the last twenty years working with customers around the world on information strategy.

He works closely with SAP research and innovation centers around the world to evangelize new technology prototypes.

His popular Business Analytics and SAPWeb20 blogs track innovation in analytics and social media, including topics such as augmented corporate reality, collaborative decision-making, and social network analysis.

His PowerPoint Twitter Tools lets presenters see and react to tweets in real time, embedded directly within their slides.

A popular and engaging speaker, Elliott presents regularly to IT and business audiences at international conferences, on subjects such as why BI projects fail and what to do about it, and the intersection of BI and enterprise 2.0.

Prior to Business Objects, Elliott was a computer consultant in Hong Kong and led analytics projects for Shell in New Zealand. He holds a first-class honors degree in Economics with Statistics from Bristol University, England. He blogs on http://timoelliott.com/blog/ (one of the best designed blogs in BI) . You can see more about him personal web site here and photo/sketch blog here. You should follow Timo at http://twitter.com/timoelliott

Art Credit- Timo Elliott

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Data Visualization using Tableau

Image representing Tableau Software as depicte...
Image via CrunchBase

Here is a great piece of software for data visualization– the public version is free.

And you can use it for Desktop Analytics as well as BI /server versions at very low cost.

About Tableau Software

http://www.tableausoftware.com/press_release/tableau-massive-growth-hiring-q3-2010

Tableau was named by Software Magazine as the fastest growing software company in the $10 million to $30 million range in the world, and the second fastest growing software company worldwide overall. The ranking stems from the publication’s 28th annual Software 500 ranking of the world’s largest software service providers.

“We’re growing fast because the market is starving for easy-to-use products that deliver rapid-fire business intelligence to everyone. Our customers want ways to unlock their databases and produce engaging reports and dashboards,” said Christian Chabot CEO and co-founder of Tableau.

http://www.tableausoftware.com/about/who-we-are

History in the Making

Put together an Academy-Award winning professor from the nation’s most prestigious university, a savvy business leader with a passion for data, and a brilliant computer scientist. Add in one of the most challenging problems in software – making databases and spreadsheets understandable to ordinary people. You have just recreated the fundamental ingredients for Tableau.

The catalyst? A Department of Defense (DOD) project aimed at increasing people’s ability to analyze information and brought to famed Stanford professor, Pat Hanrahan. A founding member of Pixar and later its chief architect for RenderMan, Pat invented the technology that changed the world of animated film. If you know Buzz and Woody of “Toy Story”, you have Pat to thank.

Under Pat’s leadership, a team of Stanford Ph.D.s got together just down the hall from the Google folks. Pat and Chris Stolte, the brilliant computer scientist, realized that data visualization could produce large gains in people’s ability to understand information. Rather than analyzing data in text form and then creating visualizations of those findings, Pat and Chris invented a technology called VizQL™ by which visualization is part of the journey and not just the destination. Fast analytics and visualization for everyone was born.

While satisfying the DOD project, Pat and Chris met Christian Chabot, a former data analyst who turned into Jello when he saw what had been invented. The three formed a company and spun out of Stanford like so many before them (Yahoo, Google, VMWare, SUN). With Christian on board as CEO, Tableau rapidly hit one success after another: its first customer (now Tableau’s VP, Operations, Tom Walker), an OEM deal with Hyperion (now Oracle), funding from New Enterprise Associates, a PC Magazine award for “Product of the Year” just one year after launch, and now over 50,000 people in 50+ countries benefiting from the breakthrough.

also see http://www.tableausoftware.com/about/leadership

http://www.tableausoftware.com/about/board

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and now  a demo I ran on the Kaggle contest data (it is a csv dataset with 95000 rows)

I found Tableau works extremely good at pivoting data and visualizing it -almost like Excel on  Steroids. Download the free version here ( I dont know about an academic program (see links below) but software is not expensive at all)

http://buy.tableausoftware.com/

Desktop Personal Edition

The Personal Edition is a visual analysis and reporting solution for data stored in Excel, MS Access or Text Files. Available via download.

Product Information

$999*

Desktop Professional Edition

The Professional Edition is a visual analysis and reporting solution for data stored in MS SQL Server, MS Analysis Services, Oracle, IBM DB2, Netezza, Hyperion Essbase, Teradata, Vertica, MySQL, PostgreSQL, Firebird, Excel, MS Access or Text Files. Available via download.

Product Information

$1800*

Tableau Server

Tableau Server enables users of Tableau Desktop Professional to publish workbooks and visualizations to a server where users with web browsers can access and interact with the results. Available via download.

Product Information

Contact Us

* Price is per Named User and includes one year of maintenance (upgrades and support). Products are made available as a download immediately after purchase. You may revisit the download site at any time during your current maintenance period to access the latest releases.

 

 

Cisco SocialMiner

A highly simplified version of the RSS feed ic...
Image via Wikipedia

A new product from Cisco to mine social media for analytics on sentiment-

http://www.cisco.com/en/US/products/ps11349/index.html

Cisco SocialMiner is a social media customer care solution that can help you proactively respond to customers and prospects communicating through public social media networks like Twitter, Facebook, or other public forums or blogging sites. By providing social media monitoring, queuing, and workflow to organize customer posts on social media networks and deliver them to your social media customer care team, your company can respond to customers in real time using the same social network they are using.

Cisco SocialMiner provides:

  • The ability to configure multiple campaigns to search for customer postings on the public social web about your company’s products, services, or area of expertise
  • Filtering of social contacts based on preconfigured campaign filters to focus campaign searches
  • Routing of social contacts to skilled customer care representatives in the contact center or to experts in the enterprise–multiple people can work together to handle responses to customer postings through shared work queues
  • Detailed metrics for social media customer care activities, campaign reports, and team reports

With Cisco SocialMiner, your company can listen and respond to customer conversations originating in the social web. Being proactive can help your company enhance its service, improve customer loyalty, garner new customers, and protect your brand.

Table 1. Features and Benefits of Cisco SocialMiner 8.5

Feature Benefits
Product Baseline Features
Social media feeds

• Feeds are configurable sources to capture public social contacts that contain specific words, terms, or phrases.

• Feeds enable you to search for information on the public social web about your company’s products, services, or area of expertise.

• Cisco SocialMiner supports the following types of feeds:

• Facebook

• Twitter
Campaign management

• Groups feeds into campaigns to organize all posting activity related to a product category or business objective

• Produces metrics on campaign activity

• Provides the ability to configure multiple campaigns to search for customer postings on specific products or services

• Groups social contacts for handling by the social media customer care team

• Enables filtering of social contacts based on preconfigured campaign filters to focus campaign searches
Route and queue social contacts

• Enables routing of social contacts to skilled customer care representatives in the contact center

• Draws on expertise in the enterprise by allowing multiple people in the enterprise to work together to handle responses to customer postings through shared work queues

• Enables automated distribution of work to improve efficiency and effectiveness of social media engagement
Tagging

• Allows work to be routed to the appropriate team by grouping each post or social contact into different categories; for example, a post can be marked with the “customer_support” tag; this post will then appear on a customer support agent’s queue for processing
Social media customer care metrics

• Provides detailed metrics on social media customer care activities, campaign reports, and team reports

• Measures work and results

• Manages to service-level goals

• Supports brand management

• Optimizes staffing

• Includes dashboarding of social media posting activity when Cisco Unified Intelligence Center is used
Reporting for social contacts

• Provides a reporting database that can be accessed using any reporting tool, including Cisco Unified Intelligence Center

• Enables customer care management to accurately report on and track social media interactions by the contact center
OpenSocial-compliant gadgets

Representational State Transfer (REST) application programming interfaces (APIs)

• Provides flexible user interface options

• Enables extensive opportunities for customization
Optional integration with full suite of Cisco Collaboration tools

• Allows you to take advantage of the full suite of Cisco Collaboration tools, including Cisco Quad, Cisco Show and Share, and Cisco Pulse technology, to help your social media customer care team quickly find answers to help customers efficiently and effectively

• Easy to maintain with existing IT personnel
Operating Environment
Cisco Unified Computing System(UCS) C-Series or B-Series Servers

• Requires a Cisco UCS C-Series or B-Series Server.

• Server consolidation means lower cost per server with Cisco UCS Servers.
Architecture
Scalability

• One server supports up to 30 simultaneous social media customer care users and 10,000 social contacts per hour.
Management
Cisco Unified Real-Time Monitoring Tool (RTMT)

• Operational management is enhanced through integration with the Cisco Unified RTMT, providing consistent application monitoring across Cisco Unified Communications Solutions.
Simple Network Management Protocol (SNMP)

• SNMP with an associated MIB is supported through the Cisco Voice Operating System (VOS).
Reporting
Cisco Unified Intelligence Center

• Create customizable reports of social media customer care events using Cisco Unified Intelligence Center (purchased separately).

 

 

Libre Office

Some ambiguity about Libre Office and why it needed to change from Open Office- just when Open Office seemed so threatening on the desktop

FROM- http://www.documentfoundation.org/faq/

Q: So is this a breakaway project?

A: Not at all. The Document Foundation will continue to be focused on developing, supporting, and promoting the same software, and it’s very much business as usual. We are simply moving to a new and more appropriate organisational model for the next decade – a logical development from Sun’s inspirational launch a decade ago.

Q: Why are you calling yourselves “The Document Foundation”?

A: For ten years we have used the same name – “OpenOffice.org” – for both the Community and the software. We’ve decided it removes ambiguity to have a different name for the two, so the Community is now “The Document Foundation”, and the software “LibreOffice”. Note: there are other examples of this usage in the free software community – e.g. the Mozilla Foundation with the Firefox browser.

Q: Does this mean you intend to develop other pieces of software?

A: We would like to have that possibility open to us in the future…

Q: And why are you calling the software “LibreOffice” instead of “OpenOffice.org”?

A: The OpenOffice.org trademark is owned by Oracle Corporation. Our hope is that Oracle will donate this to the Foundation, along with the other assets it holds in trust for the Community, in due course, once legal etc issues are resolved. However, we need to continue work in the meantime – hence “LibreOffice” (“free office”).

Q: Why are you building a new web infrastructure?

A: Since Oracle’s takeover of Sun Microsystems, the Community has been under “notice to quit” from our previous Collabnet infrastructure. With today’s announcement of a Foundation, we now have an entity which can own our emerging new infrastructure.

Q: What does this announcement mean to other derivatives of OpenOffice.org?

A: We want The Document Foundation to be open to code contributions from as many people as possible. We are delighted to announce that the enhancements produced by the Go-OOo team will be merged into LibreOffice, effective immediately. We hope that others will follow suit.

Q: What difference will this make to the commercial products produced by Oracle Corporation, IBM, Novell, Red Flag, etc?

A: The Document Foundation cannot answer for other bodies. However, there is nothing in the licence arrangements to stop companies continuing to release commercial derivatives of LibreOffice. The new Foundation will also mean companies can contribute funds or resources without worries that they may be helping a commercial competitor.

Q: What difference will The Document Foundation make to developers?

A: The Document Foundation sets out deliberately to be as developer friendly as possible. We do not demand that contributors share their copyright with us. People will gain status in our community based on peer evaluation of their contributions – not by who their employer is.

Q: What difference will The Document Foundation make to users of LibreOffice?

A: LibreOffice is The Document Foundation’s reason for existence. We do not have and will not have a commercial product which receives preferential treatment. We only have one focus – delivering the best free office suite for our users – LibreOffice.

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Non Microsoft and Non Oracle vendors are indeed going to find it useful the possiblities of bundling a free Libre Office that reduces the total cost of ownership for analytics software. Right now, some of the best free advertising for Microsoft OS and Office is done by enterprise software vendors who create Windows Only Products and enable MS Office integration better than  Open Office integration. This is done citing user demand- but it is a chicken egg dilemma- as functionality leads to enhanced demand. Microsoft on the other hand is aware of this dependence and has made SQL Server and SQL Analytics (besides investing in analytics startups like Revolution Analytics) along with it’s own infrastructure -Azure Cloud Platform/EC2 instances.