Buddypress for Analytical Buddies??

Let us assume there are top 100 analysts in the world mostly using WordPress or Typepad or Blogger to make posts

Managing them is quite a challenge.

What is marketing ROI of analyst relationships for a Business Intelligence vendor- Curt Monash is the Aerosmith of Business Intelligence Analysts so he can tell it better.

How about a magical community where you just use their mostly Feedburner of Feedblitz RSS feeds to create a self automated community.

Serach Engine Optimization can be tricked by keeping that community website free from Google or Search Engines ( yes it can be done).

Use numerical etc as in Linkedin to spur rivalry by shifting their page positions up and down, or by clicking repeatedly on some posts to manipulate their views on blog posts.

What would SAS pay to have all SAS analysts in one webpage. or SPSS to have all SPSS analysts in one webpage.

Six months later suddenly open the website for search engines, and the RSS feed has downloaded all the posts of all the top 50 analysts of the world. Google advertsing wont matter because hey we have a mega vendor sponsor- while individual bloggers / analysts have no collective strength now as the community is too big.

So much blah blah-

What software would you use.

you can choose between

Ning.com ( but it mostly non Blog feeds based)

or Wordframe.com ( which interface and name sounds suspiciously like WordPress software)

Or you can choose a customized WordPress Solution called Buddy Press.

Here is the software-

BuddyPress

BuddyPress will transform an installation of WordPress MU into a social network platform.

BuddyPress is a suite of WordPress plugins and themes, each adding a distinct new feature. BuddyPress contains all the features you’d expect from WordPress but aims to let members socially interact. Read More ?

Note this was just a generic case study for making a case for open source based community softwares. Resemblance to any thing is a matter of coincidence – except for Curt Monash of course.

Cost of Customized WordPress Software for communties is a big zero- it is free and open source and tjousands of plugins can be installed and maintained for it.

See an existing installation here

www.decisionstats.com/community

or at www.buddypress.org

Mergers and Acqusitions: Analyzing them

Valuation of future cash flows is an inexact science- too often it relies either on flat historical numbers (we grew by 5% last year so next year we will grow by 10%)

To add to the fun is the agency conflict, manager’s priorities (in terms of stock options encashment) is different from owner’s priorities.

These are some ways you can track companies for analysis-

1) Make a Google Alert on Company Name

2) Track if there is sudden and sustained spike in activity – it may be that company may be on road show seeking like minded partners, investors or mergers.

3) Watch for sudden drop in news alerts- it may mean radio silence or company may be in negotiations

4) Watch how company starts behaving with traditional antagonists…….

The easiest word thrown in the melee is ethics, copyright violations or payments delayed.

I am pasting an extract by a noted and renowned analyst in the business intelligence field-

Curt Monash

His Professional opinion on SAP

SAP’s NetWeaver Business Warehouse software will soon run natively on Teradata’s database for high-end data warehousing and BI (business intelligence), the vendors announced Monday.

SAP and its BusinessObjects BI subsidiary already had partnerships and product integrations with Teradata. But the vendors’ many joint customers have been clamoring for more, and native Business Warehouse support is the answer, said Tim Lang, vice president of product management for Business Objects.

SAP expects the new capability to enter beta testing in the fourth quarter of this year, with general availability in the first quarter of 2010, according to a spokesman.

Under the partnership, SAP will be handling first-line support, according to Lang. Pricing was not available.

The announcement drew a skeptical response from analyst Curt Monash of Monash Research, who questioned how deeply SAP will be committed to selling its customers on Teradata versus rival platforms.

“Business Objects has long been an extremely important partner for Teradata. But SAP’s most important DBMS partner is and will long be IBM, simply because [IBM] DB2 is not Oracle,” Monash said.”

Credit-

http://www.infoworld.com/d/data-management/sap-and-teradata-deepen-data-warehousing-ties-088

and here are some words from Curt Monash’s personal views on SAP

Typical nonsense from SAP

Below, essentially in its entirety, is an e-mail I just received from SAP, today, January 3. (Emphasis mine.)

Thank you for attending SAPs 4th Annual Analyst Summit in Las Vegas. We hope you found the time to be valuable. To ensure that we continue meeting your informational needs, please take a few moments to complete our online survey by using the link below. We ask that you please complete the survey before December 20. We look forward to receiving your feedback.

What makes this typical piece of SAP over-organization particularly amusing is that I didn’t actually attend the event. I was planning to, but after considerable effort I think I finally made it clear to VP of Analyst Relations Don Bulmer that I was fed up with being lied to* by him and his colleagues. In connection with that, we came to a mutual agreement, as it were, that I wouldn’t go.

*and lied about

Obviously, administrative ineptitude and dishonesty are two very different matters, united only by the fact that they both are characteristics of SAP, particularly its analyst relations group. Having said that, I should hasten to add that there are plenty of people at SAP I still trust. If Peter Zencke or Lothar Schubert tells me something, I expect it to be true. And it’s not just Germans; I feel the same way about Dan Rosenberg or Andrew Cabanski-Dunning, to name just a couple non-German SAP guys.

But I have to say this — both SAP’s ethics and its internal business processes are sufficiently screwed up as to cast doubt on SAP’s qualifications to “run the world’s best-run businesses.”

Source:

http://www.monashreport.com/2007/01/03/sap-nonsense-ethics/

Journalism ethics off course makes sure that journalists don’t get renumerance or have to compulsorily declare benefits openly.This is not true for online journalism as it is still evolving.

Curt Monash is the grand daddy of all Business Intelligence Journalists- he has been doing this and seen it all since 1981 ( I was 4 years old then).

Almost incorruptible and therefore much respected his Monash report remains closely watched.

Some techniques to thwart Business Intelligence journalists is off course tactics of

1) Fear

2) Uncertainity

3) Doubt

by planting false leaks, or favoring more pliable journalists than the ones who ask difficult questions.

Another way is to use Search Engine Optimization so the Google search is rendered ineffective for diificult journalists for people to read them.

Why did I start this thread?

Well it seems the Business Intelligence world is coming to a round of consolidations and mergers. So will the trend of mega vendors first mentioned by M Fauschette here lead to a trend of mega journalist agencies as well- like a Fox News for all business intelligence journalists to report and get a share of the booty.

The Business Intelligence companies have long viewed analyst relationships as an unnecessary and uncontrollable marketing channel which they would like to see evolve.

Television Ratings can be manipulated for advertising similarly can you manipulate views, page views, clicks on a website for website advertisement.The catch is Google Trends may just give you the actual picture, but you can lie low by choosing not to submit or ping google during initial days and then we the website is big enough in terms of viewers or contributing bloggers can then safely ping Google as the momentum would be inertial in terms of getting bigger and bigger.

http://www.mfauscette.com/software_technology_partn/2009/05/the-emergence-of-the-mega-tech-vendor-economy.html

Here are some facts as per companies-

1) For SAS Institute

a) WPS is launching its Desktop software which enables SAS language users to migrate seamlessly at 1/10 th of the cost of SAS Base and SAS Stat. It will include Proc Reg and Proc Logistic in this and have a huge documentation.

b) R – open source software is increasingly powerful to manipulate data. SAS/IML tried offering a peace hand but they would need to reconcile with the GPL conditions for R- so if it is a plugin the source code is open and so on

c)  Inference of R may be acquired by SAS to get a limited liability stake in a R based user platform.

d) Traditional Rival SPSS ( the two have dunked it out in analytics since 40 years) has a much better GUI and launched a revamped brand PASW. They are no longer distracted with a lawsuit which curiously accused them of stock manipulation and were found innocent.

e) Jim Goodnight has been dominating the industry since 1975 and has managed to stay private despite three recessions and huge inducements ( a wise miove given the mess in the markets in 2008). After Jim who will lead SAS with as much wisdom is an open question. Jim has refused Microsoft some years back, and is still very much in command despite being isolated in terms of industry alliances he remains respected. Pressure on him to rush into a merger would may just backfire.

f) The politics of envy- SAS is hated by many analytics people just as in some corners people hate America- it is because it is number 1, and been there too long.Did you mention anti-trust investigations . Well WPS is based out of UK and the European Union takes competition much more seriously.

g) Long time grudges – SAS is disliked despite its substantial R and D investments, the care it takes of its employees, and local community. Naturally people who are excluded or were excluded at some point of time have resentments.

h) SAS ambitions in Business Intelligence where curiously it is not that expensive and is actually more efficient than other players. The recent salvo fired by Jim Davis declaring business analytics as better than business intelligence- a remark much resented by cricket loving  British journalist, Peter J Thomas

http://peterthomas.wordpress.com/category/business-intelligence/sas-bi-ba-controversy/

Intellectuals can carry huge grudges for decades ( Newton and Liebnitz) or Me with people who delay my interviews.

Teradata

1) Teradata has been a big partner with both SAS and SAP. It has also been losing ground recently in the same scenario SAS will shortly face.

It was also spun off in 2007-8 by the parent company NCR

http://it.toolbox.com/blogs/infosphere/against-the-flow-ncr-unacquires-teradata-13842

So will SAS buy Teradata

Will SAP Buy Teradata

Will SAS merge with Teradata and acquired by SAP while reaching a compromise with both WPS and R Project.

Will SAS call the bluff, make sincere efforts with the GPL and academic community to reconcile, give away multiple SAS Base and SAS Stat licenses in colleges and universities (like Asia, India, China) by expanding their academic program globally, start offering more coverage to JMP at a reduced price, make a trust for succession.

I dont know. All I know is I like writing code and poetry. Any code that gets the job done.

Any poem that I want to write ( see scribd books on the right)

Interview SPSS Olivier Jouve

SPSS recently launched a major series of products in it’s text mining and data mining product portfolio and rebranded data mining to the PASW series. In an exclusive and extensive interview, Oliver Jouve Vice President,Corporate Development at SPSS Inc talks of science careers, the recent launches, open source support to R by SPSS, Cloud Computing and Business Intelligence.

Ajay: Describe your career in Science. Are careers in science less lucrative than careers in business development? What advice would you give to people re-skilling in the current recession on learning analytical skills?

Olivier: I have a Master of Science in Geophysics and Master of Science in Computer Sciences, both from Paris VI University. I have always tried to combine science and business development in my career as I like to experience all aspects ďż˝ from idea to concept to business plan to funding to development to marketing to sales.

There was a study published earlier this year that said two of the three best jobs are related to math and statistics. This is reinforced by three societal forces that are converging ďż˝ better uses of mathematics to drive decision making, the tremendous growth and storage of data, and especially in this economy, the ability to deliver ROI. With more and more commercial and government organizations realizing the value of Predictive Analytics to solve business problems, being equipped with analytical skills can only enhance your career and provide job security.

Ajay: So SPSS has launched new products within its Predictive Analytics Software (PASW) portfolio ďż˝ Modeler 13 and Text Analytics 13? Is this old wine in a new bottle? What is new in terms of technical terms? What is new in terms of customers looking to mine textual information?

Olivier: Our two new products — PASW Modeler 13 (formerly Clementine) and PASW Text Analytics 13 (formerly Text Mining for Clementine) ďż˝ extend and automate the power of data mining and text analytics to the business user, while significantly enhancing the productivity, flexibility and performance of the expert analyst.

PASW Modeler 13 data mining workbench has new and enhanced functionality that quickly takes users through the entire data mining process ďż˝ from data access and preparation to model deployment. Some the newest features include Automated Data Preparation that conditions data in a single step by automatically detecting and correcting quality errors; Auto Cluster that gives users a simple way to determine the best cluster algorithm for a particular data set; and full integration with PASW Statistics (formerly SPSS Statistics).

With PASW Text Analytics 13, SPSS provides the most complete view of the customer through the combined analysis of text, web and survey data.   While other companies only provide the text component, SPSS couples text with existing structured data, permitting more accurate results and better predictive modeling. The new version includes pre-built categories for satisfaction surveys, advanced natural language processing techniques, and it supports more than 30 different languages.

Ajay: SPSS has supported open source platforms – Python and R ďż˝ before it became fashionable to do so. How has this helped your company?

Olivier: Open source software helps the democratization of the analytics movement and SPSS is keen on supporting that democratization while welcoming open source users (and their creativity) into the analytics framework.

Ajay: What are the differences and similarities between Text Analytics and Search Engines? Can we mix the two as well using APIs?

Olivier: Search Engines are fundamentally top-down in that you know what you are looking for when launching a query. However, Text Analytics is bottom-up, uncovering hidden patterns, relationships and trends locked in unstructured data ďż˝ including call center notes, open-ended survey responses, blogs and social networks. Now businesses have a way of pulling key concepts and extracting customer sentiments, such as emotional responses, preferences and opinions, and grouping them into categories.

For instance, a call center manager will have a hard time extracting why customers are unhappy and churn by using a search engine for millions of call center notes. What would be the query? But, by using Text Analytics, that same call center agent will discover the main reasons why customers are unhappy, and be able to predict if they are going to churn.

Ajay: Why is Text Analytics so important?  How will companies use it now and into the future?
Olivier –
Actually, the question you should ask is, “Why is unstructured data so important?” Today, more than ever, people love to share their opinions — through the estimated 183 billion emails sent, the 1.6 million blog posts, millions of inquiries captured in call center notes, and thousands of comments on diverse social networking sites and community message boards. And, letďż˝s not forget all data that flows through Twitter. Companies today would be short-sighted to ignore what their customers are saying about their products and services, in their own words. Those opinions ďż˝ likes and dislikes ďż˝ are essential nuggets and bear much more insights than demographic or transactional data to reducing customer churn, improving satisfaction, fighting crime, detecting fraud and increasing marketing campaign results.

Ajay: How is SPSS venturing into cloud computing and SaaS?

Olivier: SPSS has been at the origin of the PMML standard to allow organizations to provision their computing power in a very flexible manner � just like provisioning computing power through cloud computing. SPSS strongly believes in the benefits of a cloud computing environment, which is why all of our applications are designed with Service Oriented Architecture components.  This enables SPSS to be flexible enough to meet the demands of the market as they change with respect to delivery mode.  We are currently analyzing business and technical issues related to SPSS technologies in the cloud, such as the scoring and delivery of analytics.  In regards to SaaS, we currently offer hosted services for our PASW Data Collection (formerly Dimensions) survey research suite of products.

Ajay: Do you think business intelligence is an over used term? Why do you think BI and Predictive Analytics failed in mortgage delinquency forecasting and reporting despite the financial sector being a big spender on BI tools?

Oliver: There is a big difference between business intelligence (BI) and Predictive Analytics. Traditional BI technologies focus on what�s happening now or what�s happened in the past by primarily using financial or product data. For organizations to take the most effective action, they need to know and plan for what may happen in the future by using people data � and that�s harnessed through Predictive Analytics.

Another way to look at it � Predictive covers the entire capture, predict and act continuum � from the use of survey research software to capture customer feedback (attitudinal data), to creating models to predict customer behaviors, and then acting on the results to improve business processes. Predictive Analytics, unlike BI, provides the secret ingredient and answers the question, �What will the customer do next?�

That being said, financial institutions didn�t need to use Predictive Analytics to see
that some lenders sold mortgages to unqualified individuals likely to default. Predictive Analytics is an incredible application used to detect fraud, waste and abuse. Companies in the financial services industry can focus on mitigating their overall risk by creating better predictive models that not only encompass richer data sets, but also better rules-based automation.

Ajay: What do people do at SPSS to have fun when they are not making complex mathematical algorithms?
Oliver: SPSS employees love our casual, friendly atmosphere, our professional and talented colleagues, and our cool, cutting-edge technology. The fun part comes from doing meaningful work with great people, across different groups and geographies. Of course being French, I have ensured that my colleagues are fully educated on the best wine and cuisine. And being based in Chicago, there is always a spirited baseball debate between the Cubs and White Sox. However, I am yet to convince anyone that rugby is a better sport.

Biography

Olivier Jouve is Vice President, Corporate Development, at SPSS Inc. He is responsible for defining SPSS strategic directions, growth opportunities through internal development, merger and acquisitions and/or tactical alliances. As a pioneer in the field of data and text mining for the last 20 years, he has created the foundation of Text Analytics technology for analyzing customer interactions at SPSS. Jouve is a successful serial entrepreneur and has had his works published internationally in the area of Analytical CRM, text mining, search engines, competitive intelligence and knowledge management.

PASW 13 :The preview

Here are some previews of the PASW – the new suite of softwares by SPSS.

 

Auto Cluster

The Auto Cluster feature in PASW Modeler 13 creates, ranks, browses and visualizes models to identify which clusters offer the most effective cross-sell/up-sell opportunities, or reduce the propensity to churn.

Automatic Data Preparation

Automatic Data Preparation, a one-click feature in PASW Modeler 13, quickly flags problems such as missing data and recommends which sets of data to use for optimal results.

Comments

The new Comments feature is an invaluable collaborative tool that enables users to post quick notes directly into a particular model stream and communicate detail behind the logic used to create it.

PASW Statistics Integration

Now all the PASW Statistics modules and functionality can be used directly within Modeler 13 to conduct all statistical analysis without having to switch between applications.

The images were courtesy SPSS PR. But the website itself talks of much more

http://www.spss.com/software/modeling/

(Ajay- Much better revamped website for much better revamped  software 🙂 )

SPSS launches PASW 13

SPSS launches a new product.

From the official PR release –

PASW Modeler 13 (formerly Clementine) and PASW Text Analytics 13 (formerly Text Mining for Clementine) extend and automate the power of data mining and text analytics to the business user, while significantly enhancing the productivity, flexibility and performance of the expert analyst.

So Clementine users now get to use PASW Modeler 13.

Predictive Analytics Software, PASW, is the new name for the complete portfolio of SPSS Predictive Analytics products. This new naming standard unifies the product families under consistent and descriptive nomenclatures to reflect the broad functionality and seamless integration among all SPSS products.

The entire SPSS software portfolio will carry the PASW naming standard beginning with the releases of PASW Modeler 13 and PASW Text Analytics 13. Over the next year, new naming will be introduced at each release of the other SPSS products, including: PASW Statistics (formerly SPSS Statistics), PASW Data Collection (formerly Dimensions) and PASW Collaboration and Deployment Services (formerly Predictive Enterprise Services).

Jack Noonan, SPSS chairman, president and CEO, said, “SPSS is the only Predictive Analytics vendor to deliver the depth and breadth of software to capture customer feedback, predict behaviors and then act on the results by improving business processes. With important and valued feedback from customers, we have created a new, over-arching product portfolio name that builds on our 40 year legacy of innovation, enhanced performance, and robust deployment capabilities in Predictive Analytics.”

But is this just a re branding exercise or is there fresh meat behind the fresh name?

Stay tuned….

Interview –Jon Peck SPSS

JonPeck

 

I was in the middle of interviewing people as well as helping the good people in my new role as a community evangelist at Smart Data Collective when I got a LinkedIn Request to join the SDC group  from Jon Peck .

SPSS Inc. is a leading worldwide provider of predictive analytics software and solutions. Founded in 1968, today SPSS has more than 250,000 customers worldwide, served by more than 1,200 employees in 60 countries .Now Jon is a legendary SPSS figure and a great teacher in this field .I asked him for an interview he readily agreed.

Jon Peck is a Principal Software Engineer and Technical Advisor at SPSS. He has been working with SPSS since 1983  and in the interview he talks from the breadth of his perspective and experience on things in analytics and at SPSS .

Ajay – Describe your career journey from college to today. What advice would you give to young students seeking to be hedge fund managers rather than scientists.  What are the basic things that a science education can help students with , in your opinion ?

Jon– After graduating from college with a B.A. in math, I earned a Ph. D in Economics, specializing in econometrics, and taught at a top American university for 13 years in the Economics and Statistics Departments and the School of Organization and Management.  Working in an academic environment all that time was a great opportunity to grow intellectually.  I was increasingly drawn to computing and eventually decided to join a statistical software company.  There were only two substantial ones at the time.  After a lot of thought, I joined SPSS as it seemed to be the more interesting place and one where I would be able to work in a wider variety of areas.  That was over 25 years ago!  Now I have some opportunities to teach and speak again as well as working in development, which I enjoy a lot.

I still believe in getting a broad liberal arts education along with as much quantitative training as possible.  Being able to work in very different areas has been a big asset for me.  Most people will have multiple careers, so preparing broadly is the most important career thing you can do.  As for hedge fund jobs – if there are any left, I’d say not to be starry-eyed about the money.  If you don’t choose a career that really interests you, you won’t be very successful anyway. Do what you love – subject to earning a living.

Math and scientific reasoning skills are preparation for working in many areas as well as being helpful in making the many decisions with quantitative aspects in life.  Math, especially, provides a foundation useful in many areas.  The recently announced program in the UK to improve general understanding of probability illustrates some practical value.

Ajay- What are SPSS’s contribution to Open Source software . What ,if you can disclose are any plans for further increasing that involvement.

Jon-  I wish I could talk about SPSS future plans, but I can’t.  However, the company is committed to continuing its efforts in Python and R.  By opening up the SPSS technology with these open source technologies, we are able to expand what we and our users can do.  At the same time, we can make R more attractive through nicer output and simpler syntax and taking away much of the pain.  One of the things I love about this approach is how quickly and easily new things can be produced and distributed this way compared to the traditional development cycle.  I wrote about productivity and Python recently on my blog at insideout.spss.com.

Ajay – How happy is the SPSS developer community with Python . Are there any other languages that you are considering in the future.

Jon- Many in the SPSS user community were more used to packaged procedures than to programming (except in the area of data transformations).  So Python, first, and then R were a shock.  But the benefits are so large that we have had an excellent response to both the Python and R technologies.  Some have mastered the technology and have been very successful and have made contributions back to the SPSS community.  Others are consumers of this technology, especially through our custom dialogs and extension commands that eliminate the need to learn Python or R in order to use programs in these languages.  Python is an outstanding language.  It is easy to get started with it, but it has very sophisticated features.  It has fewer dark corners than any other language I know.  While there are a few other more popular languages, Python popularity has been steadily growing, especially in the scientific and statistical communities.  But we already have support for three high-level languages, and if there is enough demand, we’ll do more.

Some of our partners prefer to use the lower-level C language interfaces we offer.  That’s fine, too.  We’re not Python zealots (well, maybe, I am).  Python, as a scripting language, isn’t as fast as a compiled language.  For many purposes this does not matter, and Python itself is written in C.  I recently wrote a Python module for TURF analysis.  The computations are simple but computationally explosive, so I was worried that it would be too slow to be useful.   It turned out to be pretty fast because of the way I could use some of Python’s built-in data structures and algorithms.  And the popular numPy and SciPy scientific and numerical libraries are written in C.

Users who would not think of themselves as developers sometimes find that a small Python effort can automate manual work with big time and accuracy improvements.  I got a note recently from a user who said, "I got it to work, and this is FANTASTIC! It will save me a lot of time in my survey analysis work."

Ajay- What are the areas where SPSS is not a good fit for using. What areas suit SPSS software the most compared to other solutions.

Jon- SPSS Statistics, the product,  is not a database.  Our strength is in applying analytical methods to data for model building, prediction, and insight.  Although SPSS Statistics is used in a wide variety of areas, we focus first on people data and think of that first when planning and designing new features.  SPSS Statistics and other SPSS products all work well with databases, and we have solutions for deploying analytics into production systems, but we’re not going to do your payroll.  One thing that was a surprise to me a few years ago is that we have a significant number of users who use SPSS Statistics as a basic reporting product but don’t do any inferential statistics.  They find that they can do customized reporting – often using the Custom Tables module – very quickly.  With Version 17, they can also do fancier and dynamic output formatting without resorting to script writing or manual editing, which is proving very attractive.

Ajay- Are there any plans for SPSS to use Software as a Service Model . Any plans to use advances in remote and cloud computing for SPSS ?

Jon- We are certainly looking at cloud computing.  The biggest challenge is being able to put things in the cloud that will be robust and reliable.

Ajay- What are SPSS’s Asia plans ? Which
country has the maximum penetration of SPSS in terms of usage.

Jon- SPSS, the company, has long been strong in Japan, and Taiwan, and Korea is also strong.  China is increasingly important, of course.  We have a large data center in Singapore.  Although India has a strong, long, history in statistical methodology, it is a much less well-developed market for us.  We have a presence there, but I don’t know the numbers. (Ajay – SPSS has been one of my first experiences in statistical software when I came up with it at my business school in 2001. In India SPSS has been very active with academia licensing and it introduced us to the nice and easy menu driven features of SPSS.)

Biography – Jon earned his Ph. D. from Yale University and taught econometrics and statistics there for 13 years before joining SPSS.

Jon joined the SPSS company in 1983 and worked on many aspects of the very first SPSS DOS product, including writing the first C code that SPSS ever shipped. Among the features he has designed are OMS (the Output Management System), the Visual Bander, Define Variable Properties, ALTER TYPE, Unicode support, and the Date and Time Wizard. Jon is the author of many of the modules on Developer Central. He is an active cyclist and hiker.

Jon Peck blogs on  SPSS Inside-Out.

Interview – Anne Milley, SAS Part 1

Anne Milley has been a part of SAS Institute’s core strategy team.

She was in the news recently with an article by the legendary Ashlee Vance in the Bits Blog of  New York Times http://bits.blogs.nytimes.com/2009/02/16/sas-warms-to-open-source-one-letter-at-a-time/

In the article,  Ms. Milley said, “I think it addresses a niche market for high-end data analysts that want free, readily available code. We have customers who build engines for aircraft. I am happy they are not using freeware when I get on a jet.”

To her credit, Ms. Milley addressed some of the critical comments head-on in a subsequent blog post.

This sparked my curiosity in knowing Anne ,and her perspective more than just a single line quote and here is an interview. This is part 1 of the interview . Anne_Milley

Ajay -Describe your career journey , both out of and in SAS Institute. What advice would you give to young high school students to pursue careers in science. Do you think careers in science are as rewarding as other careers.

Anne-

Originally, I wanted to major in international business to leverage my German (which is now waning from lack of use!).  I found the marketing and management classes at the time provided little practical value and happily ended up switching to the college of social science in the economics department, where I was challenged with several quantitative courses and encouraged to always have an analytical perspective.  In school, I was exposed to BASIC, SPSS, SHAZAM, and SAS.  Once I began my thesis (bank failure prediction models and the term structure of interest rates) and started working, it was SAS that served as the best software investment, both in banking (Federal Home Loan Bank of Dallas) and in retail (7-Eleven Corp.).  After 5+ years in Dallas, my husband wanted to move back to New England and SAS happened to be opening an office at the time.  From there, I enjoyed a few years as a pre-sales technical consultant, many years in analytical product management, and most recently in product marketing.  All the while, it has been a great motivating factor to work with so many talented people focused on solving problems, revealing opportunities and doing things better—both within and outside of SAS.

For high school and college students, I urge them to invest in studying some math and science, no matter the career they’re pursuing.  Whether they are interested in banking/finance, medicine and the life sciences, engineering or other fields, courses that will help them explore and analyze data, and come up with new approaches, new solutions, new advances based on a more scientific approach will pay off.

Course work in statistics, operations research, computer science and others will help hone skills for today’s data- and analytics-driven world.  One example of this idea in action:  North Carolina State University’s (NCSU) Institute for Advanced Analytics is seeing a huge increase in interest.  Its first graduating class last year saw higher average salaries than other graduate programs and multiple job offers per graduate.  Why?  Because there is still a huge demand for graduates with the ability to manipulate and analyze data in order to make better, more informed decisions.  I personally think careers in math and science are especially rewarding, but we need many diverse skills to make the world go round :o)

Ajay- Big corporations versus Startups. Where do you think is the balance between being big in terms of stability and size and being swift and nimble in terms of speed of product roll outs. What are the advantages and disadvantages of being a big corporation in a fast changing technology field.

Anne-

Ever a balancing act, with continuous learning along the way.  The advantage of being big (and privately held) is that you can be more long-term-oriented.  The challenge with fast-changing technology is to know where to best invest.  While others may go to market faster with new capabilities, we seek to provide superior implementations (we invest in ‘R’ (Research) AND ‘D’ (Development), making capabilities available on a number of platforms. 

In today’s economy, I think the big vs. small comparison is becoming less and less relevant.  Big corporations need to be agile and innovative, like their smaller rivals.  And small- to medium-sized businesses (SMBs) need to use the same techniques and technologies as the “big boys.”

First, on the big side, I’ll use an example of which I’m very familiar:  At SAS, a company founded more than 30 years ago as an entrepreneurial venture, we’ve certainly changed over the decades.  SAS started out in a small office with a handful of people.  It’s now a global company with hundreds of offices and thousands of employees around the world.  Yet one thing that has not changed for SAS in all this time:  a laser-like focus on the customer.  This has been the key to SAS’ success and uninterrupted growth .Not really a “secret sauce.” Just a simple yet profound approach: listen carefully to your customers and their changing needs, and innovate, develop and adapt based on these needs.

Of course, being large has its advantages:  we have more ideas from more people, and creativity and innovation knows no borders.  From Sydney to Warsaw, Săo Paulo to Singapore, Shanghai to Heidelberg, SAS employees work closely with customers to meet their business needs today and in the future.

SAS provides the stability and proven success that businesses look for, particularly in troubled economic times.  Being large and privately held enables SAS to grow when others are cutting back, and continue to invest in R&D at a high rate – 22% of revenues in 2008.

Yet with our annual subscription licensing model, SAS cannot rest on its laurels.  Each year, customers vote with their checkbooks:  if SAS provided them with business benefits, results and a positive ROI, they renew; if not, they can walk away.  Happily for SAS, the overwhelming majority of customers keep coming back.  But the licensing model keeps SAS on its toes, customer-focused, and always listening and innovating based on customer feedback.

As for SMBs, they are rapidly adopting the technologies used by large companies – such as business analytics – to compete in the global economy.  Two examples of this:

BGF Industries is a manufacturer of high-tech fabrics used in jet fighters, bullet-proof vests, movie-theater screens and surfboards, based in Greensboro, NC. BGF turned to SAS business analytics to help it deal with foreign competition.  BGF created a cost-effective, easy-to-use early-warning system that helps it track quality and productivity.  Per BGF, data is now available in minutes instead of hours.  And in the business world, this speed can be the difference between success and failure.  Per Bobby Hull, a BGF systems analyst: “The early-warning system we built with SAS allowed us to go from nothing to everything.  SAS allows us to focus away from clerical tasks to focus on the quality and process side of the job. Because of SAS, we’re never more than three clicks away from finding an answer.”

For Los Angeles-based The Wine House, installing a SAS-powered
inventory-management system helped it discover nearly $400,000 in “lost” inventory sitting on warehouse shelves.  For an SMB with annual sales of $20 million, that was a major find.  Business analytics helps it to compete with major retail and grocery chains.  Per Bill Knight, owner of The Wine House: “The first day the SAS application was live, we identified approximately 1,000 cases of wine that had not moved in over a year. That’s significant cash tied up in inventory.  We had a huge sale to blow it out, and just in time, because in today’s economy, we would be choking on that inventory.”

So regardless of size, businesses must remain agile, listen to their customers, and use technologies like business analytics to make sense of and derive value from their data – whether on the quality of surfboard covers or the number of cases of Oregon Pinot Noir in stock.

3) SAS Institute has been the de-facto leader in both market volume share as well as market value share in the field of data analytics. What are some of the factors do you think have contributed to this enduring success. What have been the principal challengers over the years.(Any comments on the challenge from SAS language software WPS please ??)

At SAS, we seek to provide a complete environment for analytics—from data collection, data manipulation, data exploration, data analysis, deployment of results – and the means to manage that whole process.  Competition comes in many forms and it pushes us to keep delivering value.  For me, one thing that sets SAS apart from other vendors is that we care so deeply about the quality of results.  Our Technical Support, Education and consulting services organizations really do partner with customers to help them achieve the best results.  That kind of commitment is deep in the DNA of SAS’ culture.

The good thing about competition is that it forces you to re-examine your value proposition and rethink your business strategy.  Customers value attributes of their analytics infrastructure in varying degrees— speed, quality, support, flexibility, ease of migration, backward and forward compatibility, etc.  Often there are options to trump any one or a subset of these and when that aligns with the customers’ priorities of what they value, they will vote with their pocketbooks.  For some customers with tight batch-processing windows, speed trumps everything.  In tests conducted by Merrill Consultants, an MXG program running on WPS runs significantly longer, consumes more CPU time and requires more memory than the same MXG program hosted on its native SAS platform.

While it’s easy to get caught up in fast-changing technology, one has to also consider history.  Some programming languages come and go; others have stood the test of time.  Even the use of different flavors of analysis ebbs and flows.  For instance, when data mining was all the rage almost a decade ago, many asked the very good question, “Why so much excitement about analyzing so much opportunistic data when design of experiments offers so much more?”  Finally, experimental design is being more readily adopted in areas like marketing.

At the end of the day, innovation is the only sustainable competitive advantage.  As noted above in question 2, SAS has remained firmly committed to customer-driven innovation.  And SAS has “stuck to its knitting” with respect to analytics.  A while back, SAS used to stand for “Statistical Analysis System.” If not literally, then philosophically, Analytics remains our middle name.

(Ajay- to be continued)