Interview Jamie Nunnelly NISS

An interview with Jamie Nunnelly, Communications Director of National Institute of Statistical Sciences

Ajay– What does NISS do? And What does SAMSI do?

Jamie– The National Institute of Statistical Sciences (NISS) was established in 1990 by the national statistics societies and the Research Triangle universities and organizations, with the mission to identify, catalyze and foster high-impact, cross-disciplinary and cross-sector research involving the statistical sciences.

NISS is dedicated to strengthening and serving the national statistics community, most notably by catalyzing community members’ participation in applied research driven by challenges facing government and industry. NISS also provides career development opportunities for statisticians and scientists, especially those in the formative stages of their careers.

The Institute identifies emerging issues to which members of the statistics community can make key contributions, and then catalyzes the right combinations of researchers from multiple disciplines and sectors to tackle each problem. More than 300 researchers from over 100 institutions have worked on our projects.

The Statistical and Applied Mathematical Sciences Institute (SAMSI) is a partnership of Duke University,  North Carolina State University, The University of North Carolina at Chapel Hill, and NISS in collaboration with the William Kenan Jr. Institute for Engineering, Technology and Science and is part of the Mathematical Sciences Institutes of the NSF.

SAMSI focuses on 1-2 programs of research interest in the statistical and/or applied mathematical area and visitors from around the world are involved with the programs and come from a variety of disciplines in addition to mathematics and statistics.

Many come to SAMSI to attend workshops, and also participate in working groups throughout the academic year. Many of the working groups communicate via WebEx so people can be involved with the research remotely. SAMSI also has a robust education and outreach program to help undergraduate and graduate students learn about cutting edge research in applied mathematics and statistics.

Ajay– What successes have you had in 2010- and what do you need to succeed in 2011. Whats planned for 2011 anyway

Jamie– NISS has had a very successful collaboration with the National Agricultural Statistical Service (NASS) over the past two years that was just renewed for the next two years. NISS & NASS had three teams consisting of a faculty researcher in statistics, a NASS researcher, a NISS mentor, a postdoctoral fellow and a graduate student working on statistical modeling and other areas of research for NASS.

NISS is also working on a syndromic surveillance project with Clemson University, Duke University, The University of Georgia, The University of South Carolina. The group is currently working with some hospitals to test out a model they have been developing to help predict disease outbreak.

SAMSI had a very successful year with two programs ending this past summer, which were the Stochastic Dynamics program and the Space-time Analysis for Environmental Mapping, Epidemiology and Climate Change. Several papers were written and published and many presentations have been made at various conferences around the world regarding the work that was conducted as SAMSI last year.

Next year’s program is so big that the institute has decided to devote all it’s time and energy around it, which is uncertainty quantification. The opening workshop, in addition to the main methodological theme, will be broken down into three areas of interest under this broad umbrella of research: climate change, engineering and renewable energy, and geosciences.

Ajay– Describe your career in science and communication.

Jamie– I have been in communications since 1985, working for large Fortune 500 companies such as General Motors and Tropicana Products. I moved to the Research Triangle region of North Carolina after graduate school and got into economic development and science communications first working for the Research Triangle Regional Partnership in 1994.

From 1996-2005 I was the communications director for the Research Triangle Park, working for the Research Triangle Foundation of NC. I published a quarterly magazine called The Park Guide for awhile, then came to work for NISS and SAMSI in 2008.

I really enjoy working with the mathematicians and statisticians. I always joke that I am the least educated person working here and that is not far from the truth! I am honored to help get the message out about all of the important research that is conducted here each day that is helping to improve the lives of so many people out there.

Ajay– Research Triangle or Silicon Valley– Which is better for tech people and why? Your opinion

Jamie– Both the Silicon Valley and Research Triangle are great regions for tech people to locate, but of course, I have to be biased and choose Research Triangle!

Really any place in the world that you find many universities working together with businesses and government, you have an area that will grow and thrive, because the collaborations help all of us generate new ideas, many of which blossom into new businesses, or new endeavors of research.

The quality of life in places such as the Research Triangle is great because you have people from around the world moving to a place, each bringing his/her culture, food, and uniqueness to this place, and enriching everyone else as a result.

Two advantages the Research Triangle has over Silicon Valley are that the Research Triangle has a bigger diversity of industries, so when the telecommunications industry busted back in 2001-02, the region took a hit, but the biotechnology industry was still growing, so unemployment rose, but not to the extent that other areas might have experienced.

The latest recession has hit us all very hard, so even this strategy has not made us immune to having high unemployment, but the Research Triangle region has been pegged by experts to be one of the first regions to emerge out of the Great Recession.

The other advantage I think we have is that our cost of living is still much more reasonable than Silicon Valley. It’s still possible to get a nice sized home, some land and not break the bank!

Ajay– How do you manage an active online social media presence, your job and your family. How important is balance in professional life and when young professional should realize this?

Jamie– Balance is everything, isn’t it? When I leave the office, I turn off my iPhone and disconnect from Twitter/Facebook etc.

I know that is not recommended by some folks, but I am a one person communications department and I love my family and friends and feel its important to devote time to them as well as to my career.

I think it is very important for young people to establish this early in their careers because if they don’t they will fall victim to working way too many hours and really, who loves you at the end of the day?

Your company may appreciate all you do for them, but if you leave, or you get sick and cannot work for them, you will be replaced

. Lee Iacocca, former CEO of Chrystler, said, “No matter what you’ve done for yourself or for humanity, if you can’t look back on having given love and attention to your own family, what have you really accomplished?” I think that is what is really most important in life.

About-

Jamie Nunnelly has been in communications for 25 years. She is currently on the board of directors for Chatham County Economic Development Corporation and Leadership Triangle & is a member of the International Association of Business Communicators and the Public Relations Society of America. She earned a bachelor’s degree in interpersonal and public communications at Bowling Green State University and a master’s degree in mass communications at the University of South Florida.

You can contact Jamie at http://niss.org/content/jamie-nunnelly or on twitter at

Quantifying Analytics ROI

Japanese House Crest “Go-Shichi no Kiri”
Image via Wikipedia

I had a brief twitter exchange with Jim Davis, Chief Marketing Officer, SAS Institute on Return of Investment on Business Analytics Projects for customers. I have interviewed Jim Davis before last year https://decisionstats.com/2009/06/05/interview-jim-davis-sas-institute/

Now Jim Davis is a big guy, and he is rushing from the launch of SAS Institute’s Social Media Analytics in Japan- to some arguably difficult flying conditions in time to be home in America for Thanksgiving. That and and I have not been much of a good Blog Boy recently, more swayed by love of open source, than love of software per se. I love equally, given I am bad at both equally.

Anyways, Jim’s contention  ( http://twitter.com/Davis_Jim ) was customers should go in business analytics only if there is Positive Return on Investment.  I am quoting him here-

What is important is that there be a positive ROI on each and every BA project. Otherwise don’t do it.

That’s not the marketing I was taught in my business school- basically it was sell, sell, sell.

However I see most BI sales vendors also go through -let me meet my sales quota for this quarter- and quantifying customer ROI is simple maths than predictive analytics but there seems to be some information assymetry in it.

Here is a paper from North Western University on ROI in IT projects-.

but overall it would be in the interest of customers and Business Analytics Vendors to publish aggregated ROI.

The opponents to this transparency in ROI would be market leaders in market share, who have trapped their customers by high migration costs (due to complexity) or contractually.

A recent study listed Oracle having a large percentage of unhappy customers who would still renew!, SAP had problems when it raised prices for licensing arbitrarily (that CEO is now CEO of HP and dodging legal notices from Oracle).

Indeed Jim Davis’s famous unsettling call for focusing on Business Analytics,as Business Intelligence is dead- that call has been implemented more aggressively by IBM in analytical acquisitions than even SAS itself which has been conservative about inorganic growth. Quantifying ROI, should theoretically aid open source software the most (since they are cheapest in up front licensing) or newer technologies like MapReduce /Hadoop (since they are quite so fast)- but I think that market has a way of factoring in these things- and customers are not as foolish neither as unaware of costs versus benefits of migration.

The contrary to this is Business Analytics and Business Intelligence are imperfect markets with duo-poly  or big players thriving in absence of customer regulation.

You get more protection as a customer of $20 bag of potato chips, than as a customer of a $200,000 software. Regulators are wary to step in to ensure ROI fairness (since most bright techies are qither working for private sector, have their own startup or invested in startups)- who in Govt understands Analytics and Intelligence strong enough to ensure vendor lock-ins are not done, and market flexibility is done. It is also a lower choice for embattled regulators to ensure ROI on enterprise software unlike the aggressiveness they have showed in retail or online software.

Who will Analyze the Analysts and who can quantify the value of quants (or penalize them for shoddy quantitative analytics)- is an interesting phenomenon we expect to see more of.

 

 

Why do bloggers blog ?

Xbox (revision 1.0) internal layout. Including...
Image via Wikipedia

Step 1 is to create internal motivation to create a blog in the first place

Step 2 is to find what to write

Reasons Bloggers Blog-

Basic -Ranting


Examples- I hate Facebook Platform team treats me badly with waits, and breaks my code.

SAS Marketing wont give me  a big discount to make me look good in front of my boss.

Companies  wont give me their software for free- even though I will use it to make money (and not play X Box)

I want my vendors to be FOSS but my customers to switch to SaaS.

Google wont do this- Apple wont do that- Microsoft wont do those.

Revolution would give me 4 great packages but not the open source for RevoScaler (which only 300 people would understand in the first place)

Safety-

I better kiss the Professor and give a Turkey for dinner, as he sits on my thesis committee.

I will recommend Prof X’s lousy book in the hope he recommends my lousy book as a textbook too.

It is safe to laugh when the boss is making a joke-I should comment on her corporate blog, and retweet her.

Belonging-

I belong to this great online community of smart people. Let me agree to what they say.

I really believe in EVERYTHING that ALL the 2 MILLION members of the community have to say ALL the TIME.

I belong to this online community because all my friends are on my computer.

4 Egositic

My blog page rank is now X plus delta tau because of sugary key words (2004)

My technorati numbers rise (2005)

I was once on Digg (2007)

I have Z * exp N followers on Twitter and even more on Facebook (2008)

My Klout is increasing on twitter, My stack overflow reputation ‘s cup floweth over. (2009)

My Karma on Reddit is more important than my Karma in real life (2010)

Self Actualization-

I got time to kill- and I think I may learn more, meet intersting people and discover something wandering on the internet.

All those who wonder are not lost- Wikiquote

I got a story to tell, poems to write, code to give away. A free  Blog is something a Chinese , an Iranian  and a North korean really really know what the value is.

But after all that, WHY Do Bloggers Blog?

  • Because we are still waiting for Facebook to create the Blog Killer.
  • Its better than saying I am unemployed and a social loner
  • Reddit Karma feels good. Any Karma of any kind.

Reputation on Social Networks

Law of Diminishing Marginal Utility
Image via Wikipedia

Classical Economics talks of the value of utlity, diminishing marginal utility if the same things is repeated again and again (like spam in an online community)

StackOverflow has a great way of measuring reputation – and thus allows intangible benefits /awards -similar to wikipedia badges , reddit karma. Utility is also auto generated like @klout  on twitter or lists memberships and other sucessful open source communities online including Ubuntu forums have ways to create ah hierarchies even in class less utopian classes.

Basically it then acts as the motivating game as the mostly boy population try to race on numbers.

 

in Stack Overflow- you can get buddies to upvote you and basically act as a role playing game too.

—–From http://stackoverflow.com/faq#reputation

To gain reputation, post good questions and useful answers. Your peers will vote on your posts, and those votes will cause you to gain (or, in rare cases, lose) reputation:

answer is voted up +10
question is voted up +5
answer is accepted +15 (+2 to acceptor)
post is voted down -2 (-1 to voter)

A maximum of 30 votes can be cast per user per day, and you can earn a maximum of 200 reputation per day (although accepted answers and bounty awards are immune to this limit). Also, please note that votes for any posts marked “community wiki” do not generate reputation.

Amass enough reputation points and Stack Overflow will allow you to go beyond simply asking and answering questions:

15 Vote up
15 Flag offensive
50 Leave comments
100 Edit community wiki posts
125 Vote down (costs 1 rep)
200 Reduced advertising

DirkE and JD swoon about Shane's MOM in Room 106 while writing R code

In a shadowy room in cyberworld , two geeks plot revenge on a common

blgger and up vote each other on stack overflow while discussing Shane’s MOM

http://chat.stackoverflow.com/transcript/106/2010/11/15

 

How can you announce this on SO?

Oh…

Sure…go for it.

I’ll downvote it.

🙂

We should also add it into the [r] wiki.

I added it to the wiki.

We should probably try to clean that up a little; some of the other tags have put a lot of effort into it. (e.g. stackoverflow.com/tags/java/info)

Whoa! I didn’t downvote your post.

I was wondering…
Feel free to upvote it to set it back to even.

3:18 PM

I did.

Someone voted to close too.

Some people take themselves way too seriously…

Yup. And not unlike the people constantly call for community-wiki.

BTW I didn’t see the button for CW anymore once it was posted. What am I missing?

I think that I may have seen something about a bug related to that…

Four close votes, and -2 score. Whoa Nelly.

Ha! I’m not overly surprised. Meant to suggest that you use CW…

Ironically, you’re still ahead in the rep. on this question, right? Although I think that it might get downvoted into oblivion before we’re done…

I up-voted. Dirk, I’ve got your back. 😉

 

 

Begin……

3 hours later…

8:09 PM

@DirkEddelbuettel you catch Ajay’s latest? ow.ly/3a8gK

Jeebus

I had actually unsub’ed from his feed. Now I know why. How you’re doing with the Yahoo Pipes app?

Methinks he has some sort of clinical compulsive condition given how every single post has to include a reference that his facvourite software company from NC, and/or members of their management team.

@DirkEddelbuettel I stumbled on that one in Twitter. pipes project has been tabled while I fight some other battles.

I think he’s fishing for SEO sugar with his posts. His use of words seems contrived to include key words over and over

Twitter is so useless, between him and Ed Borasky’s (znmeb) spambots nothing else of value appers.

I guess like so many streams it requires filtering. The basic twitter blocking takes them out prett

y quickly

So blocking is common? They ought to show that: “subscribed to N, listened to by M and showing good taste by blocking O asshats”
8:19 PM

ha! yeah that would be good signaling. Not sure how common it is, but I use it mostly for spam bots. I actually have only blocked 2 warm blooded humans (counting Ajay’s multiple accts as one person)

Dirk Eddelbuettel

Oh boy 🙂 Romain has fired a salvo on r-devel: “Depends on what your goal is: getting the job done, or learning about the R/C API”. Hehe.

@JDLong Tell who: One is Shane’s mother, and the other is … ?

JD Long
JD Long

speaking of shane’s mom, he and Josh deciding to be productive members of real society today?

PAWCON -This week in London

Watch out for the twitter hash news on PAWCON and the exciting agenda lined up. If your in the City- you may want to just drop in

http://www.predictiveanalyticsworld.com/london/2010/agenda.php#day1-7

Disclaimer- PAWCON has been a blog partner with Decisionstats (since the first PAWCON ). It is vendor neutral and features open source as well proprietary software, as well case studies from academia and Industry for a balanced view.

 

Little birdie told me some exciting product enhancements may be in the works including a not yet announced R plugin 😉 and the latest SAS product using embedded analytics and Dr Elder’s full day data mining workshop.

Citation-

http://www.predictiveanalyticsworld.com/london/2010/agenda.php#day1-7

Monday November 15, 2010
All conference sessions take place in Edward 5-7

8:00am-9:00am

Registration, Coffee and Danish
Room: Albert Suites


9:00am-9:50am

Keynote
Five Ways Predictive Analytics Cuts Enterprise Risk

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 will reveal:

  • 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

 

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

Top of this page ] [ Agenda overview ]


IBM9:50am-10:10am

Platinum Sponsor Presentation
The Analytical Revolution

The algorithms at the heart of predictive analytics have been around for years – in some cases for decades. But now, as we see predictive analytics move to the mainstream and become a competitive necessity for organisations in all industries, the most crucial challenges are to ensure that results can be delivered to where they can make a direct impact on outcomes and business performance, and that the application of analytics can be scaled to the most demanding enterprise requirements.

This session will look at the obstacles to successfully applying analysis at the enterprise level, and how today’s approaches and technologies can enable the true “industrialisation” of predictive analytics.

Speaker: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd

Top of this page ] [ Agenda overview ]


Deloitte10:10am-10:20am

Gold Sponsor Presentation
How Predictive Analytics is Driving Business Value

Organisations are increasingly relying on analytics to make key business decisions. Today, technology advances and the increasing need to realise competitive advantage in the market place are driving predictive analytics from the domain of marketers and tactical one-off exercises to the point where analytics are being embedded within core business processes.

During this session, Richard will share some of the focus areas where Deloitte is driving business transformation through predictive analytics, including Workforce, Brand Equity and Reputational Risk, Customer Insight and Network Analytics.

Speaker: Richard Fayers, Senior Manager, Deloitte Analytical Insight

Top of this page ] [ Agenda overview ]


10:20am-10:45am

Break / Exhibits
Room: Albert Suites


10:45am-11:35am
Healthcare
Case Study: Life Line Screening
Taking CRM Global Through Predictive Analytics

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, Life Line Screening

Top of this page ] [ Agenda overview ]


11:35am-12:25pm
Open Source Analytics; Healthcare
Case Study: A large health care organization
The Rise of Open Source Analytics: Lowering Costs While Improving Patient Care

Rapidminer and R were the number 1 and 2 in this years annual KDNuggets data mining tool usage poll, followed by Knime on place 4 and Weka on place 6. So what’s going on here? Are these open source tools really that good or is their popularity strongly correlated with lower acquisition costs alone? This session answers these questions based on a real world case for a large health care organization and explains the risks & benefits of using open source technology. The final part of the session explains how these tools stack up against their traditional, proprietary counterparts.

Speaker: Jos van Dongen, Associate & Principal, DeltIQ Group

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12:25pm-1:25pm

Lunch / Exhibits
Room: Albert Suites


1:25pm-2:15pm
Keynote
Thought Leader:
Case Study: Yahoo! and other large on-line e-businesses
Search Marketing and Predictive Analytics: SEM, SEO and On-line Marketing Case Studies

Search Engine Marketing is a $15B industry in the U.S. growing to double that number over the next 3 years. Worldwide the SEM market was over $50B in 2010. Not only is this a fast growing area of marketing, but it is one that has significant implications for brand and direct marketing and is undergoing rapid change with emerging channels such as mobile and social. What is unique about this area of marketing is a singularly heavy dependence on analytics:

 

  • Large numbers of variables and options
  • Real-time auctions/bids and a need to adjust strategies in real-time
  • Difficult optimization problems on allocating spend across a huge number of keywords
  • Fast-changing competitive terrain and heavy competition on the obvious channels
  • Complicated interactions between various channels and a large choice of search keyword expansion possibilities
  • Profitability and ROI analysis that are complex and often challenging

 

The size of the industry, its growing importance in marketing, its upcoming role in Mobile Advertising, and its uniquely heavy reliance on analytics makes it particularly interesting as an area for predictive analytics applications. In this session, not only will hear about some of the latest strategies and techniques to optimize search, you will hear case studies that illustrate the important role of analytics from industry practitioners.

Speaker: Usama Fayyad, , Ph.D., CEO, Open Insights

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SAS2:15pm-2:35pm

Platinum Sponsor Presentation
Creating a Model Factory Using in-Database Analytics

With the ever-increasing number of analytical models required to make fact-based decisions, as well as increasing audit compliance regulations, it is more important than ever that these models can be created, monitored, retuned and deployed as quickly and automatically as possible. This paper, using a case study from a major financial organisation, will show how organisations can build a model factory efficiently using the latest SAS technology that utilizes the power of in-database processing.

Speaker: John Spooner, Analytics Specialist, SAS (UK)

Top of this page ] [ Agenda overview ]


2:35pm-2:45pm

Session Break
Room: Albert Suites


2:45pm-3:35pm

Retail
Case Study: SABMiller
Predictive Analytics & Global Marketing Strategy

Over the last few years SABMiller plc, the second largest brewing company in the world operating in 70 countries, has been systematically segmenting its markets in different countries globally in order optimize their portfolio strategy & align it to their long term country specific growth strategy. This presentation talks about the overall methodology followed and the challenges that had to be overcome both from a technical as well as from a change management stand point in order to successfully implement a standard analytics approach to diverse markets and diverse business positions in a highly global setting.

The session explains how country specific growth strategies were converted to objective variables and consumption occasion segments were created that differentiated the market effectively by their growth potential. In addition to this the presentation will also provide a discussion on issues like:

  • The dilemmas of static vs. dynamic solutions and standardization vs. adaptable solutions
  • Challenges in acceptability, local capability development, overcoming implementation inertia, cost effectiveness, etc
  • The role that business partners at SAB and analytics service partners at AbsolutData together play in providing impactful and actionable solutions

 

Speaker: Anne Stephens, SABMiller plc

Speaker: Titir Pal, AbsolutData

Top of this page ] [ Agenda overview ]


3:35pm-4:25pm

Retail
Case Study: Overtoom Belgium
Increasing Marketing Relevance Through Personalized Targeting

 

Since many years, Overtoom Belgium – a leading B2B retailer and division of the French Manutan group – focuses on an extensive use of CRM. In this presentation, we demonstrate how Overtoom has integrated Predictive Analytics to optimize customer relationships. In this process, they employ analytics to develop answers to the key question: “which product should we offer to which customer via which channel”. We show how Overtoom gained a 10% revenue increase by replacing the existing segmentation scheme with accurate predictive response models. Additionally, we illustrate how Overtoom succeeds to deliver more relevant communications by offering personalized promotional content to every single customer, and how these personalized offers positively impact Overtoom’s conversion rates.

Speaker: Dr. Geert Verstraeten, Python Predictions

Top of this page ] [ Agenda overview ]


4:25pm-4:50pm

Break / Exhibits
Room: Albert Suites


4:50pm-5:40pm
Uplift Modelling:
Case Study: Lloyds TSB General Insurance & US Bank
Uplift Modelling: You Should Not Only Measure But Model Incremental Response

Most marketing analysts understand that measuring the impact of a marketing campaign requires a valid control group so that uplift (incremental response) can be reported. However, it is much less widely understood that the targeting models used almost everywhere do not attempt to optimize that incremental measure. That requires an uplift model.

This session will explain why a switch to uplift modelling is needed, illustrate what can and does go wrong when they are not used and the hugely positive impact they can have when used effectively. It will also discuss a range of approaches to building and assessing uplift models, from simple basic adjustments to existing modelling processes through to full-blown uplift modelling.

The talk will use Lloyds TSB General Insurance & US Bank as a case study and also illustrate real-world results from other companies and sectors.

 

Speaker: Nicholas Radcliffe, Founder and Director, Stochastic Solutions

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5:40pm-6:30pm

Consumer services
Case Study: Canadian Automobile Association and other B2C examples
The Diminishing Marginal Returns of Variable Creation in Predictive Analytics Solutions

 

Variable Creation is the key to success in any predictive analytics exercise. Many different approaches are adopted during this process, yet there are diminishing marginal returns as the number of variables increase. Our organization conducted a case study on four existing clients to explore this so-called diminishing impact of variable creation on predictive analytics solutions. Existing predictive analytics solutions were built using our traditional variable creation process. Yet, presuming that we could exponentially increase the number of variables, we wanted to determine if this added significant benefit to the existing solution.

Speaker: Richard Boire, BoireFillerGroup

Top of this page ] [ Agenda overview ]


6:30pm-7:30pm

Reception / Exhibits
Room: Albert Suites


Tuesday November 16, 2010
All conference sessions take place in Edward 5-7

8:00am-9:00am

Registration, Coffee and Danish
Room: Albert Suites


9:00am-9:55am
Keynote
Multiple Case Studies: Anheuser-Busch, Disney, HP, HSBC, Pfizer, and others
The High ROI of Data Mining for Innovative Organizations

Data mining and advanced analytics can enhance your bottom line in three basic ways, by 1) streamlining a process, 2) eliminating the bad, or 3) highlighting the good. In rare situations, a fourth way – creating something new – is possible. But modern organizations are so effective at their core tasks that data mining usually results in an iterative, rather than transformative, improvement. Still, the impact can be dramatic.

Dr. Elder will share the story (problem, solution, and effect) of nine projects conducted over the last decade for some of America’s most innovative agencies and corporations:

    Streamline:

  • Cross-selling for HSBC
  • Image recognition for Anheuser-Busch
  • Biometric identification for Lumidigm (for Disney)
  • Optimal decisioning for Peregrine Systems (now part of Hewlett-Packard)
  • Quick decisions for the Social Security Administration
    Eliminate Bad:

  • Tax fraud detection for the IRS
  • Warranty Fraud detection for Hewlett-Packard
    Highlight Good:

  • Sector trading for WestWind Foundation
  • Drug efficacy discovery for Pharmacia & UpJohn (now Pfizer)

Moderator: Eric Siegel, Program Chair, Predictive Analytics World

Speaker: John Elder, Ph.D., Elder Research, Inc.

Also see Dr. Elder’s full-day workshop

 

Top of this page ] [ Agenda overview ]


9:55am-10:30am

Break / Exhibits
Room: Albert Suites


10:30am-11:20am
Telecommunications
Case Study: Leading Telecommunications Operator
Predictive Analytics and Efficient Fact-based Marketing

The presentation describes what are the major topics and issues when you introduce predictive analytics and how to build a Fact-Based marketing environment. The introduced tools and methodologies proved to be highly efficient in terms of improving the overall direct marketing activity and customer contact operations for the involved companies. Generally, the introduced approaches have great potential for organizations with large customer bases like Mobile Operators, Internet Giants, Media Companies, or Retail Chains.

Main Introduced Solutions:-Automated Serial Production of Predictive Models for Campaign Targeting-Automated Campaign Measurements and Tracking Solutions-Precise Product Added Value Evaluation.

Speaker: Tamer Keshi, Ph.D., Long-term contractor, T-Mobile

Speaker: Beata Kovacs, International Head of CRM Solutions, Deutsche Telekom

Top of this page ] [ Agenda overview ]


11:20am-11:25am

Session Changeover


11:25am-12:15pm
Thought Leader
Nine Laws of Data Mining

Data mining is the predictive core of predictive analytics, a business process that finds useful patterns in data through the use of business knowledge. The industry standard CRISP-DM methodology describes the process, but does not explain why the process takes the form that it does. I present nine “laws of data mining”, useful maxims for data miners, with explanations that reveal the reasons behind the surface properties of the data mining process. The nine laws have implications for predictive analytics applications: how and why it works so well, which ambitions could succeed, and which must fail.

 

Speaker: Tom Khabaza, khabaza.com

 

Top of this page ] [ Agenda overview ]


12:15pm-1:30pm

Lunch / Exhibits
Room: Albert Suites


1:30pm-2:25pm
Expert Panel: Kaboom! Predictive Analytics Hits the Mainstream

Predictive analytics has taken off, across industry sectors and across applications in marketing, fraud detection, credit scoring and beyond. Where exactly are we in the process of crossing the chasm toward pervasive deployment, and how can we ensure progress keeps up the pace and stays on target?

This expert panel will address:

  • How much of predictive analytics’ potential has been fully realized?
  • Where are the outstanding opportunities with greatest potential?
  • What are the greatest challenges faced by the industry in achieving wide scale adoption?
  • How are these challenges best overcome?

 

Panelist: John Elder, Ph.D., Elder Research, Inc.

Panelist: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd

Panelist: Udo Sglavo, Global Analytic Solutions Manager, SAS

Panel moderator: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World


2:25pm-2:30pm

Session Changeover


2:30pm-3:20pm
Crowdsourcing Data Mining
Case Study: University of Melbourne, Chessmetrics
Prediction Competitions: Far More Than Just a Bit of Fun

Data modelling competitions allow companies and researchers to post a problem and have it scrutinised by the world’s best data scientists. There are an infinite number of techniques that can be applied to any modelling task but it is impossible to know at the outset which will be most effective. By exposing the problem to a wide audience, competitions are a cost effective way to reach the frontier of what is possible from a given dataset. The power of competitions is neatly illustrated by the results of a recent bioinformatics competition hosted by Kaggle. It required participants to pick markers in HIV’s genetic sequence that coincide with changes in the severity of infection. Within a week and a half, the best entry had already outdone the best methods in the scientific literature. This presentation will cover how competitions typically work, some case studies and the types of business modelling challenges that the Kaggle platform can address.

Speaker: Anthony Goldbloom, Kaggle Pty Ltd

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3:20pm-3:50pm

Breaks /Exhibits
Room: Albert Suites


3:50pm-4:40pm
Human Resources; e-Commerce
Case Study: Naukri.com, Jeevansathi.com
Increasing Marketing ROI and Efficiency of Candidate-Search with Predictive Analytics

InfoEdge, India’s largest and most profitable online firm with a bouquet of internet properties has been Google’s biggest customer in India. Our team used predictive modeling to double our profits across multiple fronts. For Naukri.com, India’s number 1 job portal, predictive models target jobseekers most relevant to the recruiter. Analytical insights provided a deeper understanding of recruiter behaviour and informed a redesign of this product’s recruiter search functionality. This session will describe how we did it, and also reveal how Jeevansathi.com, India’s 2nd-largest matrimony portal, targets the acquisition of consumers in the market for marriage.

 

Speaker: Suvomoy Sarkar, Chief Analytics Officer, HT Media & Info Edge India (parent company of the two companies above)

 

Top of this page ] [ Agenda overview ]


4:40pm-5:00pm
Closing Remarks

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

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Wednesday November 17, 2010

Full-day Workshop
The Best and the Worst of Predictive Analytics:
Predictive Modeling Methods and Common Data Mining Mistakes

Click here for the detailed workshop description

  • Workshop starts at 9:00am
  • First AM Break from 10:00 – 10:15
  • Second AM Break from 11:15 – 11:30
  • Lunch from 12:30 – 1:15pm
  • First PM Break: 2:00 – 2:15
  • Second PM Break: 3:15 – 3:30
  • Workshop ends at 4:30pm

Speaker: John Elder, Ph.D., CEO and Founder, Elder Research, Inc.

 

Google Raise What

Google recently did the following-

1 Raised salaries by 1000 $ across board, and gave a 10% increase at lower levels to reportedly 30% increase at higher levels.

The surprise 1000$ cash bonus , was a simple application of expectation management, people love a surprise 1000$ raise, but hate if told they would be getting a 90$ raise in their monthly salary from next quarter.

Ex Googlers or GoogleX as the groups is called have helped create a lot of not so evil value at Facebook, and at Twitter. Even the rest of the World made more money on Map Reduce than Google itself did

And Google refuses to do simple things like sell Android )s at 10 bucks a pop, or Google Maps at 0.99 cents a pop. Not even a paid content search by integrating syndicating sources like Factiva, Bloomberg etc

The book scanning project would be out soon , hey when, but they could better get some health record scanning contracts to help cut digital costs

And the A/B experiment to move to pay per conversion rather than pay per click will hurt spamboy advertisers in Facebook or Bing more than Google.

and will someone remove the 100$ limit in Adsense minimum revenue-the internet long tail doesnt end at the round number

But Google ‘s rumors of firing the guy who leaked the raise rumor is totally deception –

seems they are just plugging the leaks for hot new features to counter Gmail killers (where did we heard this phrase before) by

Mark “Still dont have a diploma from Harvard”

speaking of which if Facebook has 500 million unique customers logging and clicking ads (right)- how many unique customers search and click ads on Google. A histogram using a Monte Carlo would be nice- 🙂

 

 

Image using png package courtesy Romain Francois at http://romainfrancois.blog.free.fr/