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Predictive Analytics World announces new full-day workshops coming to San Francisco March 13-19, amounting to seven consecutive days of content.

These workshops deliver top-notch analytical and business expertise across the hottest topics.

Register now for one or more workshops, offered just before and after the full two-day Predictive Analytics World conference program (March 14-15). Early Bird registration ends on January 31st – take advantage of reduced pricing before then.

Driving Enterprise Decisions with Business Analytics – March 13, 2011
James Taylor, CEO, Decision Management Solutions
NEW – R for Predictive Modeling: A Hands-On Introduction – March 13, 2011
Max Kuhn, Director, Nonclinical Statistics, Pfizer
The Best and Worst of Predictive Analytics: Predictive Modeling Methods and Common Data Mining Mistakes – March 16, 2011
John Elder, Ph.D., CEO and Founder, Elder Research, Inc.
Hands-On Predictive Analytics – March 17, 2011
Dean Abbott, President, Abbott Analytics
NEW – Net Lift Models: Optimizing the Impact of Your Marketing – March 18-19, 2011
Kim Larsen, VP of Analytical Insights, Market Share Partners

Download the Conference Preview or view the Predictive Analytics World Agenda online

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Interview James Taylor Decision Management Expert (Updated)

Quick update

James is hosting a webinar series on decision manaement, predictive analytics and business rules this fall. You can check out the webinars and register for some or all at

Here is an interview with James Taylor, a leading consultant and evangelist in the emerging field of converging decision management.

Ajay- Describe your career in science. What fascinates you with reporting on this segment. How would you interest freshmen students in taking up statistics and math courses.

James- I took Geological Geophysics and Mathematics in college but graduated in a year when the oil price was in free fall and never worked in geophysics. Since then I have worked in computers, mostly focused on how they can be applied rather than on how they work. I am not sure I would say that this represents a career in science so much a career enabled by science and, increasingly, watching science.

As far as math goes I actually think the problem is at the other end of the spectrum. Far too many people leave school without a feel for math – it is taught in a very narrow way and leaves far too many feeling that math is something that other people do. In a world with more and more data, and more and more statistics/data-driven decisions this is not ok. We need everyone in business to be able to consume math intelligently, even if they can’t develop mathematical models themselves. Continuing with traditional math teaching in high school and college is just excluding most people and that has to end.

Ajay- What are the various stages of evolution that you have seen in the Decision Management Industry, including the prevailing jargon name.

James- Decision Management applications have been around for years, albeit primarily in the financial services industry. They used to all have their own categories – fraud systems, origination systems, account management systems – and this was the beginning of the category. One of the first things I did at FICO was describe all these applications as a set – recognizing that the same approach and the same cluster of technologies was being used in each case. Back in 2002 I and some colleagues started calling this approach Enterprise Decision Management. Back then most decision management was enabled by these packaged applications and the tools that could be used to build custom applications were talked about separately – business rules, optimization, predictive analytics.

Over the last 6 years the focus on decisions in each of these areas has increased – more rules people talk about managing decisions with rules and there’s more talk of improving operational decisions in predictive analytics and optimization circles. There’s more talk of using the tools/technologies together and a growing range of integrated suites/platforms.

Where most companies stand today is wanting the kind of capabilities that can only be delivered by applying decision management techniques and technologies but they are not yet asking for decision management. They want, for instance, consistent personalized offers across channels but they are not asking for centralized decision management. Based on previous experience I think this will change steadily over the next year or two with the number of companies asking explicitly for decision management capabilities rising.

From a name perspective we have evolved too. Over time it has become clear that the “Enterprise” was misinterpreted as a call for Enterprise-wide implementation of decision management when it was meant as a call from enterprise ownership of decisions. As a result some folks talk about Business Decision Management and I just like to talk about Decision Management.

Ajay- Why is Decision Management more important than say performance management, business intelligence, predictive analytics.

James- I am not sure it is more important. Most organizations need business intelligence to understand what happened in their business and they need performance management to monitor what is happening now. This kind of understanding is important in successful decision management implementations. And decision management is a management discipline designed, in part, to put predictive analytics to work in operational systems.

I do think a focus on decision is vital to all of them, however. If you don’t understand the decisions you are making it is hard for me to see how you can judge the effectiveness of either business intelligence or performance management. And predictive analytics should be even more decision-centric if it is to be effective. So a focus on decisions is a necessary prerequisite and the management of those decisions, using rules and analytics, is a great way to maximize their value in operational systems.

Ajay- What are your views on offshoring 1) High quality research 2) Labor Arbitrage technical work 3) Cost cutting driven

James- Well I think offshoring is an inevitable consequence of an interconnected world. I also think that companies that offshore simply to reduce cost deserve the employee and customer loyalty they will get as a consequence!

I do think that companies should make thoughtful decisions about what to do where, when something must be handled centrally and when it can be pushed to different localities etc. I think that smarter systems – systems that manage decisions explicitly – can help in this and help companies have a real DNA when it comes to decision making.

Ajay- What are the top 5 principles of Decision Management , as you would explain to a class of business graduates and CEO’s


1. Little decisions add up

The day to day decisions that drive operational behavior, customer interactions, transactional systems are more important than the big, strategic decisions beloved of management consultants. Each one seems unimportant but they happen so often that their total value swamps anything else you do. If you get these decisions wrong it won’t matter what you get right.

2. The purpose of information is to decide

Deming has a famous quote that “The ultimate purpose of collecting the data is to provide a basis for action or a recommendation”. The reason you collect data, report on data, analyze data is to make better decisions. Otherwise it’s just a cost. And unless you know which decision you are making, and what will make it a good or a bad one, then all the data in the world (and all the data management or data analysis) will not help you.

3. You cannot afford to lock up your logic

Decision making logic- the policies, regulations, best practices and customer preferences that drive decision making – cannot be locked up in code you cannot read, systems you do not understand. No matter what else might be handled by your IT people, business decision making logic must not be. You must at least be able to collaborate with your IT folks and manage it with them. You must be responsible for this logic.

4. No answer, no matter how good, is static

Organizations must realize that they have to constantly analyze, reassess and challenge their decision making process. The effectiveness of a decision can often not be determined for some time and even a good decision can be degraded by a change in the behavior of a competitor or a change in the market. As such constant challenging of the decision making approach, constant A/B testing or adaptive control is essential if decisions are to remain effective.

5. Decision making is a process to be managed

The way you make decisions is something you must understand, document, automate and analyze. Good managers, good staff, have a good decision making process. Good outcomes might result from luck or circumstance but you don’t want to rely on that. Instead you want to focus on quality decision making processes. And like many repeatable processes, automating decision making makes it easier to analyze and improve it over time.


James has agreed to schedule a free webinar to explain it more fully. Anyone who wants can register at

Ajay- What does James Taylor do when not in front of a computer, a podium or an airport. How important do you think is work life balance particularly for young people

James- Well I am a parent, a partner and an avid reader and between them those use up most of my non-work time. I really enjoy my work which makes it hard to stop sometimes. I think life/work balance is important but so is enthusiasm for what one does. Perhaps I am kidding myself but I think there is a difference between putting a lot of hours into something about which you are passionate and putting a lot of work into something just to get ahead or to avoid the rest of your life.

Ajay- Do you think BI world is male dominated. What could be the reasons.

James- Yes. The usual sexism of business combined with the average age of BI people (younger groups seem more mixed in general).

Ajay- Green economy and stimulus macro economics. How can both these fields benefit from Decision Management

James- From a macro stimulus point of view I think the key thing is that governments around the world throw money at companies specializing in decision management. <smile>

The green economy, however, is more interesting. Personally I don’t see how smart grids can be made to work without a solid core of powerful decisioning. Green marketing requires personalization and targeting to avoid waste (more decisioning) while helping consumers make better decisions about products based on green criteria needs to be built into shopping engines like Amazon’s if it is to make a real difference. Being green is all about making greener decisions and making systems make greener decisions takes decision management and decisioning technology.


James Taylor is a leading expert in Decision Management and an independent consultant specializing in helping companies automate and improve critical decisions. Previously James was a Vice President at Fair Isaac Corporation where he developed and refined the concept of enterprise decision management or EDM. Widely credited with the invention of the term and the best known proponent of the approach, James helped create the Decision Management market and is its most passionate advocate.

James has 20 years experience in all aspects of the design, development, marketing and use of advanced technology including CASE tools, project planning and methodology tools as well as platform development in PeopleSoft’s R&D team and consulting with Ernst and Young. He has consistently worked to develop approaches, tools and platforms that others can use to build more effective information systems.

James is an active consultant, speaker and author. He is a prolific blogger, with regular posts at and He also has an Expert Channel – Decision Management – on the BI Network.

His articles appear in industry magazines, he has contributed chapters to “The Business Rules Revolution:Doing Business The Right Way” (Happy About, 2006) and “Business Intelligence Implementation : Issues and Perspectives” (ICFAI University Press, 2006), and is the co-author of “Smart (Enough) Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions ” (Prentice Hall, 2007) with Neil Raden .

James is a highly sought speaker, appearing frequently at industry conferences, events and seminars. He is also a lecturer at the University of California, Berkeley.

James has an M.S. in Business Systems Analysis and Design from City University, London; a B.S. in Geological Geophysics and Mathematics from the University of Reading, England; and a “Mini-MBA” certificate from the Silicon Valley Executive Business Program at San Jose State University.

You can contact James at

Interview Neil Raden Founder of Hired Brains Inc

Here is an interview with one terrific person who has always inspired my writing ( or atleast my attempts to write) on data and systems. Neil Raden is a giant in the publishing and consulting space for business intelligence ,analytics, and decision management. In a nice interview Neil talks of his passion for his work, his prolific authoring of white papers, his seminal work with James Taylor and how he sees the BI space evolve.

The history of BI pretty much follows the history of computing platforms. First we had time-sharing, then mainframes, then mini’s, then client-server vs. PC, then a number passes at distributed computing, such as CORBA, then SOA and now the cloud.- Neil Raden

Ajay- Describe your career in math and technology and your current activities. How would you explain what you do for a living to a group of high school students who are wondering to take up mathematical and technical subjects or not.

Neil- I didn’t earn a dime at the career I was meant for, consulting, until I was 33 years old. So I would tell college students not to be in such a hurry to corner themselves into a career. It may take a while to figure out what you really want.

Though I went to college to study theatre, within a few weeks I was inspired by a math professor and switched my major. From that point on, it was pads of paper and sharp pencils. I was totally in my own head with math. I never took a statistics course, or even differential equations, because I was consumed by discrete math (graph theory too), topology and logic and later game theory/economics.

When I went looking for a job in 1974, in the midst of a deep recession, I was confronted with the stark reality (in New York ) that I could be a COBOL programmer or an actuary. I chose the latter. Working at AIG in New York in the 70’s was pretty exciting. We broke new ground in commercial property and casualty insurance and reinsurance every week. I was part of a small R&D group under the chief actuary, who reported directed to Maurice Greenberg, the legendary (but now maligned) inventor of AIG, and I loved the work.

I had to go back and teach myself probability and statistics to get through the exams, but ultimately, two kids and one on the way in NYC on one not-so-great salary was a deal-breaker. I left AIG and joined a software company doing modeling and prediction. The rest, as they say, is history. I formed my own consulting company in 1985 and I’m still at it.

To me, consulting isn’t something you do between jobs or a title you get because you implement software for clients. Consulting is a craft, it’s a career and it is rather easy to do but very difficult to learn. I work very hard to teach this to people who work for me. It’s about commitment, hard work and, most of all, ethics and being authentic with your client.

Ajay- Writing books is a lonely yet rewarding work. Could you briefly elucidate on your recent book, Smart (Enough) Systems?

Neil- I have to credit my partner, James Taylor, with the concept for the book. He was working at Fair Isaac (now FICO) at the time and this was exactly what he was doing there. It was a little tangential to my work, but when James approached me, he said he wanted a partner who was proficient in the data integration and analytics aspects of EDM (Enterprise Decision Management).

James made it pretty easy because

1) he is very prolific and 2) he took most of my comments and integrated them without argument.

I’d say I was pretty lucky and it went very well. I don’t know if I’ll ever write another book. I suppose I won’t know until the idea hits me. I’m sure it will be more difficult doing it on my own.

Ajay- What are the various stages that you have seen the BI industry go through. What are the next few years going to bring to us-

What is your wishlist for changes the industry makes for better customer ROI.

Neil- The history of BI pretty much follows the history of computing platforms. First we had time-sharing, then mainframes, then mini’s, then client-server vs. PC, then a number passes at distributed computing, such as CORBA, then SOA and now the cloud. But while the locus of BI storage, computing and presentation has changed, it’s focus changes very slowly.

Historically, there have been two major subject areas in BI: f inance and sales/marketing, All of the other subject areas still rest on periphery.

Complex Event Processing ( CEP ) for example, is making a lot of noise lately , but not much implementation. Visualization is here to stay . When the BI app and the Web a pp are the same, BI will be everywhere, but it will be a sort of pyrrhic victory because it won’t be recognized as such. Now you can take all of this with a grain of salt because I don’t really follow the industry per se, I’m more interested in how my clients can apply the technology to get the results they need.

Ajay- There is a lot of buzz about predictive analytics lately. Do you think it will have a noticeable impact or is it just the latest thing?

Neil- There are only so many people who understand quant itative meth ods and it isn’t going to grow very much. This puts a damper on PA (Predictive Analytics) because no manager is going to act on the recommendations of a black box without an articulate quant who can explain the methodology and the limits of its precision.

That isn’t a bad thing, and those who practice in predictive analytics will prosper.

On the other hand, I believe there will be an expansion of the use of generic PA models that have been vetted in practice. The FICO score is a good example, and the ability to develop and implement these applications (it’s much easier now thanks to PA software and computing environments in general) should allow for a nice market to develop around them. This is especially true with decision automation systems, like logistics, material handling, credit authorization, etc.

Ajay- What were your most interesting projects as an implementer? Most rewarding?

Neil- Most Interesting: I was the Chairman of an Advisory Board at Sandia National Laboratories for a few years.Our goal was to encourage the lab to adopt more modern and effective information management tools for their dual purpose of

1) designing and manufacturing nuclear weapons (frightening isn’t it?) and

2) certification of nuclear waste repositories.

I was able to work with scientists, physicists, engineers, geologists and computer sciences, all from backgrounds very different from those I normally engaged. The problems were monumental.

Most rewarding: We developed a data warehouse to capture the daily sales of products at the most detailed level for a cosmetics company. They never had this information before because the retailers were counters in hundreds of department stores. Thus they were able for the first time to truly understand the “sell through” of their products. Beyond just allowing a better understanding of the flow, they could tailor their promotions and, not much later, implement a continuous replenishment system.

The president of the company came to the launch and explained how we had allowed the company to do things it had never done before which would change it for the better. You don’t get those accolades from the CEO very often.

Ajay- You’ve written forty white papers. That’s a lot. What impact do you think they’ve had?

Neil- I couldn’t tell you. I don’t track downloads, my website doesn’t even require registration. I don’t see them quoted or cited very often, but then, people don’t quote or cite other’s work in this field very often anyway. I can say that I have many repeat customers among the vendors, so they must be deriving some value from them.

Ajay- What are your views on creating a community for the top 100 BI analysts in the world – a bit like a Reuters or a partnership firm. How pleased do you think will BI vendors be by this.

Neil- I was actually involved in an effort like this about a dozen years ago, called BI Alliance . Doug Hackney and I started it, and we had about a dozen BI luminaries in the organization. I’ll try to remember some: Sid Adelman, David Marco, Richard Winter, David Foote, Herb Edelstein.

You could only join if you were an independent or the head of your own firm.

It was a useful marketing tool as we were able to 1) share references and 2) staff projects. But it sort of lost its inertia after a few years.

But a few hundred BI analysts? Are there that many?? LOL I don’t know how the vendors would react, but I sort of doubt this sort of organization would have any kind of clout – too many divergent opinions.

Ajay- Do you think the work you do matters?

Neil- It certainly has an economic impact on my family! LOL I don’t know, I hope it does and proportionate to my income versus the size of the industry, yes, I guess it does. Not necessarily directly though .

A company in Dayton or Macon doesn’t make a decision because I said so, but I think I do influence some analysts and vendor s a nd to the extent I influence them, then I guess I do . I limit my analysis to my clients. If they think this work matters, then it does.


Neil Raden, consultant, analyst and author is followed by technology providers, consultants and even other analysts. His knowledge of the analytical applications is the result of thirty years of intensive work. He is the founder of Hired Brains, a research and advisory firm in Santa Barbara, CA, offering research and analysis services to technology providers as well as providing consulting and implementation services. Mr. Raden began his career as a casualty actuary with AIG before moving into software engineering and consulting in the application of analytics in fields as diverse as health care to nuclear waste management to cosmetics marketing. His blog can be found at He is the author of dozens articles and white papers and he has has contributed to numerous books and is the co-author of “Smart (Enough) Systems” (Prentice Hall, 2007) with James Taylor.

Alternatively you can just follow Neil Raden at his twitter id neilraden

Reactions to IBM -SPSS takeover.

The business intelligence -business analytics- data mining industry ( or as James Taylor would say Decision Management Industry) have some reactions on IBM – SPSS ( which was NOT a surprise to many including me). Really.

From SAS Institute, Anne Milley

Besides SAS, SPSS was one of the last independent analytic software companies. A colleague says, “It’s the end of the analytics cold war.”

I’ve been saying all along that analytics is required for success. Yes, data integration, data quality, and query & reporting are important too but, as W. Edwards Deming says, “The object of taking data is to provide a basis for action.”

The end of the analytics cold war- hmm. We all know what the end of real cold war brought us- Google, Cloud Computing, and other non technical issues.

From KXEN, Roger Hadaad

“The price paid for SPSS of four times revenues and 25 times earnings shows just how valuable this sector really is,” says Haddad. “But the deal has also created a tremendous opportunity for the sector’s remaining independent vendors that

KXEN is well placed to capitalize on. “There is no For Sale sign hanging in our window,” continues Haddad. “We launched KXEN in 1998 to democratize the benefits of data mining and predictive analytics, making them practical and affordable across the whole enterprise and not just the exclusive preserve of a few specialists. It’s going to take up to two years for the dust to settle following the IBM

“Former SPSS partners, systems integrators and distributors will face uncertainty.”

I think the PE multiple was still low- SPSS was worth more if you count the client base, active community, brand itself in the valuation. Tremendous cross sell opportunities and IBM with it’s nice research and development is a good supporter of pure science.  Yes, next two years would be facing increasing consolidation and more “surprising” news. At 4 times earnings, anyone can be bought in the present market if it is a public listed company. 😉

From the rather subdued voices on SPSS list, some subjective and non quantitative ‘strategic” forecasts.

I think the Ancient Chinese said it best “May you live in interesting times”.

Having worked with some flavors of Cognos and SPSS, I think there could be areas for technical integration for querying and GUI based forecasting as well, apart from financial mergers and administrative re adjustments. I mean people pull data not just to report it, but to estimate what comes next as well.

This could also spell the end of uni platform skilled analysts. You now need to learn atleast two different platforms like SAS,SPSS or KXEN, R or Cognos, Business Objects to hedge your chances of getting offshored (Note- I worked in offshoring for almost 4 years in India in data analytics).

Answering what IBM will do with SPSS and it’s open source commitment to R and consequences for employees, customers, vendors,partners who have more choices now than ever.

…. well it depends. Who is John Galt?

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