Interview with Rob La Gesse Chief Disruption Officer Rackspace

Here is an interview with Rob La Gesse ,Chief Disruption Officer ,Rackspace Hosting.
Ajay- Describe your career  journey from not finishing college to writing software to your present projects?
Rob- I joined the Navy right out of High School. I had neither the money for college, or a real desire for it. I had several roles in the Navy, to include a Combat Medic station with the US Marine Corps and eventually becoming a Neonatal Respiratory Therapist.

After the Navy I worked as a Respiratory Therapist, a roofer, and I repaired print shop equipment. Basically whatever it took to make a buck or two.  Eventually I started selling computers.  That led me to running a multi-line dial-up BBS and I taught myself how to program.  Eventually that led to a job with a small engineering company where we developed WiFi.

After the WiFi project I started consulting on my own.  I used Rackspace to host my clients, and eventually they hired me.  I’ve been here almost three years and have held several roles. I currently manage Social Media, building 43 and am involved in several other projects such as the Rackspace Startup Program.

Ajay-  What is building43 all about ?

Rob- Building43 is a web site devoted to telling the stories behind technology startups. Basically, after we hired Robert Scoble and Rocky Barbanica we were figuring out how best we could work with them to both highlight Rackspace and customers.  That idea expanded beyond customers to highlighting anyone doing something incredible in the technology industry – mostly software startups.  We’ve had interviews with people like Mark Zuckerberg, CEO and Founder of FaceBook.  We’ve broken some news on the site, but it isn’t really a news site. It is a story telling site.

Rackspace has met some amazing new customers through the relationships that started with an interview.

Ajay-  How is life as Robert Scoble’s boss. Is he an easy guy to work with? Does he have super powers while he types?

Rob- Robert isn’t much different to manage than the rest of my employees. He is a person – no super powers.  But he does establish a unique perspective on things because he gets to see so much new technology early.  Often earlier than almost anyone else. It helps him to spot trends that others might not be seeing yet.
Ajay – Hosting companies are so so many. What makes Rackspace special for different kinds of customers?
Rob- I think what we do better than anyone is add that human touch – the people really care about your business.  We are a company that is focused on building one of the greatest service companies on the planet.  We sell support.  Hosting is secondary to service. Our motto is Fanatic Support®

and we actually look for people focused on delivering amazing customer experiences during our interviewing and hiring practices. People that find a personal sense of pride and reward by helping others should apply at
Rackspace.  We are hiring like crazy!

Ajay – Where do you see technology and the internet 5 years down the line? (we will visit the answers in 5 years 🙂 )?
Rob- I think the shift to Cloud computing is going to be dramatic.  I think in five years we will be much further down that path.  The scaling, cost-effectiveness, and on-demand nature of the Cloud are just too compelling for companies not to embrace. This changes business in fundamental ways – lower capital expenses, no need for in house IT staff, etc will save companies a lot of money and let them focus more on their core businesses. Computing will become another utility.  I also think mobile use of computing will be much more common than it is today.  And it is VERY common today.  Phones will replace car keys and credit cards (they already are). This too will drive use of Cloud computing  because we all want our data wherever we are – on whatever computing device we happen tobe using.
Ajay- GoDaddy CEO shoots elephants. What do you do in your  spare time, if any.
Rob- Well, I don’t hunt.  We do shoot a lot of video though! I enjoy playing poker, specifically Texas Hold ’em.  It is a very people oriented game, and people are my passion.

Brief Biography- (in his own words from http://www.lagesse.org/about/)

My technical background includes working on the development of WiFi, writing wireless applications for the Apple Newton, mentoring/managing several software-based start-ups, running software quality assurance teams and more. In 2008 I joined Rackspace as an employee – a “Racker”.  I was previously a 7 year customer and the company impressed me. My initial role was as Director of Software Development for the Rackspace Cloud.  It was soon evident that I was better suited to a customer facing role since I LOVE talking to customers. I am currently the Director of Customer Development Chief Disruption Officer.  I manage building43 and enjoy working with Robert Scoble and Rocky Barbanica to make that happen.  The org chart says they work for me.  Reality tells me the opposite :)

Go take a look – I’m proud of what we are building there (pardon the pun!).

I do a lot of other stuff at Rackspace – mostly because they let me!  I love a company that lets me try. Rackspace does that.Going further back, I have been a Mayor (in Hawaii). I have written successful shareware software. I have managed employees all over the world. I have been all over the world. I have also done roofing, repaired high end print-shop equipment, been a Neonatal Respiratory Therapist, done CPR on a boat, in a plane, and in a hardware store (and of course in hospitals).

I have treated jumpers from the Golden Gate Bridge – and helped save a few. I have lived in Illinois (Kankakee), California (San Diego, San Francisco and Novato), Texas (Corpus Christi and San Antonio), Florida (Pensacola and Palm Bay), Hawaii (Honolulu/Fort Shafter) and several other places for shorter durations.

For the last 8+ years I have been a single parent – and have done an amazing job (yes, I am a proud papa) thanks to having great kids.  They are both in College now – something I did NOT manage to accomplish. I love doing anything someone thinks I am not qualified to do.

I can be contacted at rob (at) lagesse (dot) org

you can follow Rob at http://twitter.com/kr8tr

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.

Profits from Closed Customers


Closed Customers aren’t really closed; they stay on in your database.

Database marketing can help you win revenue even after a customer relationship is discontinued. This is illustrated by the following example – A prominent global financial services giant, with nearly 100 years of history, faced a unique problem while operating in India. While it had been one of the earliest entrants in the credit card industry in India, it had rapidly been losing market share to newer and nimbler more aggressive local competitors.

Indian customers have one of the lowest levels of debt worldwide due to cultural aversion to debt and lack of competition in the pre 1990 era. The credit cards receivables business in India is also a loss making operation as of 2006, because of rampant competition and discounting on annual fees and charges. Lending in India is complicated because the credit bureau CIBIL was only in nascent stages, and declared income and actual income of people varied due to the tax laws and ‘black money’ economy.

However the average receivables per card had been steadily increasing in India and it had potential to make huge profits once Indian customers became comfortable with rotating balance and paying finance charges. The credit card division also had a culture of conservative lending only to prime customers, with a good track record. On the other hand, the company’s personal loan business was making great strides in both revenue and profitability growth due to aggressive selling to both prime and sub prime customers. As a result of this the company had built up a database of 3 million customers, out of which nearly 2 million had paid off their loans.

To improve the profitability of the credit card division, and offer its customers a more value added portfolio of financial services, the company embarked on a data mining project of cross selling to its closed personal customers. After extensive tests and research based on selective tele-calling to its customer database, the company found out the following analytical findings-

1) Customers who had paid back their loans on time were the customers who were good credit customers. These customers had also increased their income since the time they had closed their personal loan.

2) People who had closed their personal loans were targeted for re churning by the person loans business. However after 6 months of closing their loans, if the customer did not take another personal loan, they were unlikely to ever take a personal loan. Thus if these customers were called again for personal loan, it would be unprofitable since the incremental expenses were not justified by incremental revenues.

3) People who bounced cheques but paid off their entire loan were bad credit risks, especially for a revolving line of credit as in for credit cards.

4) People who were called by the credit card division had better brand recall if they had an earlier relationship with personal loans division. Since they paid off their loans on time, their experiences with the company as a whole were very positive. This goodwill of the company’s brand helped to trigger higher response ratios (almost 20 % of such people took the credit card compared to only 5 % for the general population)

5) De to regulatory reasons both the credit card division and the personal loan division had to maintain an arm’s length distance. In order to do so, the credit card division decided on a transfer price of 600 rupees plus 1% of average receivables to the personal loan division. This helped track the profitability of the exercise better.

As a result of the exercise the company managed to sell an extra fifty thousand credit cards. The program was such a success that it was adopted world wide. The personal loan division earned tens of millions of rupees from its closed customer database, and the credit card division managed to increase its market share slightly.

Thus mining its own database of customers helped the company achieve the following-

a) Increase profitability
b) Improve brand recall and enhance the existing relationship
c) Cut down on marketing costs by targeting more responsive customers
d) Improve the life time value of revenues earned from each customer

This article  builds up an argument for using internal data at a customer level for decreasing marketing costs and enhancing brand recall.