Tag: Interviews

Interview Peter J Thomas -Award Winning BI Expert

Here is an in depth interview with Peter J Thomas, one of Europe’s top Business Intelligence expert and influential thought leaders. Peter talks about BI tools, data quality, science careers, cultural transformation and BI and the key focus areas.

I am a firm believer that the true benefits of BI are only realised when it leads to cultural transformation. -Peter James Thomas

 

Ajay- Describe about your early career including college to the present.

Peter –I was an all-rounder academically, but at the time that I was taking public exams in the 1980s, if you wanted to pursue a certain subject at University, you had to do related courses between the ages of 16 and 18. Because of this, I dropped things that I enjoyed such as English and ended up studying Mathematics, Further Mathematics, Chemistry and Physics. This was not because I disliked non-scientific subjects, but because I was marginally fonder of the scientific ones. In a way it is nice that my current blogging allows me to use language more.

The culmination of these studies was attending Imperial College in London to study for a BSc in Mathematics. Within the curriculum, I was more drawn to Pure Mathematics and Group Theory in particular, and so went on to take an MSc in these areas. This was an intercollegiate course and I took a unit at each of King’s College and Queen Mary College, but everything else was still based at Imperial. I was invited to stay on to do a PhD. It was even suggested that I might be able to do this in two years, given my MSc work, but I decided that a career in academia was not for me and so started looking at other options.

As sometimes happens a series of coincidences and a slice of luck meant that I joined a technology start-up, then called Cedardata, late in 1988; my first role was as a Trainee Analyst / Programmer. Cedardata was one of the first organisations to offer an Accounting system based on a relational database platform; something that was then rather novel, at least in the commercial arena. The RDBMS in question was Oracle version 5, running on VAX VMS – later DEC Ultrix and a wide variety of other UNIX flavours. Our input screens were written in SQL*Forms 2 – later Oracle Forms – and more complex processing logic and reports were in Pro*C; this was before PL/SQL. Obviously this environment meant that I had to become very conversant with SQL*Plus and C itself.

When I joined Cedardata, they had 10 employees, 3 customers and annual revenue of just £50,000 ($80,000). By the time I left the company eight years later, it had grown dramatically to having a staff of 250, over 300 clients in a wide range of industries and sales in excess of £12 million ($20 million). It had also successfully floatated on the main London Stock Exchange. When a company grows that quickly the same thing tends to happen to its employees.

Cedardata was probably the ideal environment for me at the time; an organisation that grew rapidly, offering new opportunities and challenges to its employees; that was fiercely meritocratic; and where narrow, but deep, technical expertise was encouraged to be rounded out by developing more general business acumen, a customer-focused attitude and people-management skills. I don’t think that I would have learnt as much, or progressed anything like as quickly in any other type of organisation.

It was also at Cedardata that I had my first experience of the class of applications that later became known as Business Intelligence tools. This was using BusinessObjects 3.0 to write reports, cross-tabs and graphs for a prospective client, the UK Foreign and Commonwealth Office (State Department). The approach must have worked as we beat Oracle Financials in a play-off to secure the multi-million pound account.

During my time at Cedardata, I rose to become an executive and filled a number of roles including Head of Development and also Assistant to the MD / Head of Product Strategy. Spending my formative years in an organisation where IT was the business and where the customer was King had a profound impact on me and has influenced my subsequent approach to IT / Business alignment.

Ajay- How would you convince young people to take maths and science more? What advice would you give to policy makers to promote more maths and science students?

Peter- While I have used little of my Mathematics directly in my commercial career, the approach to problem-solving that it inculcated in me has been invaluable. On arriving at University, it was something of a shock to be presented with Mathematical problems where you couldn’t simply look up the method of solution in a textbook and apply it to guarantee success. Even in my first year I had to grapple with challenges where you had no real clue where to start. Instead what worked, at least most of the time, was immersing yourself in the general literature, breaking down the problem into more manageable chunks, trying different techniques – sometimes quite recherché ones – to make progress, occasionally having an insight that provides a short-cut, but more often succeeding through dogged determination. All of that sounds awfully like the approach that has worked for me in a business context.

Having said that, I was not terribly business savvy as a student. I didn’t take Mathematics because I thought that it would lead to a career, I took it because I was fascinated by the subject. As I mentioned earlier, I enjoyed learning about a wide range of things, but Science seemed to relate to the most fundamental issues. Mathematics was both the framework that underpinned all of the Sciences and also offered its own world where astonishing an beautiful results could be found, independent of any applicability; although it has to be said that there are few braches of Mathematics that have not be applied somewhere or other.

I think you either have this appreciation of Science and Mathematics or you don’t and that this happens early on.

Certainly my interest was supported by my parents and a variety of teachers, but a lot of it arose from simply reading about Cosmology, or Vulcanism, or Palaeontology. I watched a YouTube of Steven Jay Gould recently saying that when he was a child in the 1950s all children were “in” to Dinosaurs, but that he actually got to make a career out of it. Maybe all children aren’t “in” to dinosaurs in the same way today, perhaps the mystery and sense of excitement has gone.

In the UK at least there appears to be less and less people taking Science and Mathematics. I am not sure what is behind this trend. I read pieces that suggest that Science and Maths are viewed as being “hard” subjects, and people opt for “easier” alternatives. I think creative writing is one of the hardest things to do, so I’m not sure where this perspective comes from.

Perhaps some things that don’t help are the twin images of the Scientist as a white-coated boffin and the Mathematician as a chalk-covered recluse, neither of whom have much of a grasp on the world beyond their narrow discipline. While of course there is a modicum of truth in these stereotypes, they are far from being wholly accurate in my experience.

Perhaps Science has fallen off of the pedestal that it was placed on in the 1950s and 1960s. Interest in Science had been spurred by a range of inventions that had improved people’s lives and often made the inventors a lot of money. Science was seen as the way to a better tomorrow, a view reinforced by such iconic developments as the discovery of the structure of DNA, our ever deepening insight about sub-atomic physics and the unravelling of many mysteries of the Universe. These advances in pure science were supported by feats of scientific / engineering achievement such as the Apollo space programme. The military importance of Science was also put into sharp relief by the Manhattan Project; something that also maybe sowed the seeds for later disenchantment and even fear of the area.

The inevitable fallibility of some Scientists and some scientific projects burst the bubble. High-profile problems included the Thalidomide tragedy and the outcry, however ill-informed, about genetically modified organisms. Also the poster child of the scientific / engineering community was laid low by the Challenger disaster. On top of this, living with the scientifically-created threat of mutually-assured destruction probably began to change the degree of positivity with which people viewed Science and Scientists. People arrived at the realisation that Science cannot address every problem; how much effort has gone into finding a cure for cancer for example?

In addition, in today’s highly technological world, the actual nuts and bolts of how things work are often both hidden and mysterious. While people could relatively easily understand how a steam engine works, how many have any idea about how their iPod functions? Technology has become invisible and almost unimportant, until it stops working.

I am a little wary of Governments fixing issues such as these, which are the result of major generational and cultural trends. Often state action can have unintended and perverse results. Society as a whole goes through cycles and maybe at some future point Science and Mathematics will again be viewed as interesting areas to study; I certainly hope so. Perhaps the current concerns about climate change will inspire a generation of young people to think more about technological ways to address this and interest them in pertinent Sciences such as Meteorology and Climatology.

Ajay-. How would you rate the various tools within the BI industry like in a SWOT analysis (briefly and individually)?

Peter- I am going to offer a Politician’s reply to this. The really important question in BI is not which tool is best, but how to make BI projects successful. While many an unsuccessful BI manager may blame the tool or its vendor, this is not where the real issues lie.

I firmly believe that successful BI rests on four mutually reinforcing pillars:

  • understand the questions the business needs to answer,
  • understand the data available,
  • transform the data to meet the business needs and
  • embed the use of BI in the organisation’s culture.

If you get these things right then you can be successful with almost any of the excellent BI tools available in the marketplace. If you get any one of them wrong, then using the paragon of BI tools is not going to offer you salvation.

I think about BI tools in the same way as I do the car market. Not so many years ago there were major differences between manufacturers.

The Japanese offered ultimate reliability, but maybe didn’t often engage the spirit.

The Germans prided themselves on engineering excellence, slanted either in the direction of performance or luxury, but were not quite as dependable as the Japanese.

The Italians offered out-and-out romance and theatre, with mechanical integrity an afterthought.

The French seemed to think that bizarrely shaped cars with wheels as thin as dinner plates were the way forward, but at least they were distinctive.

The Swedes majored on a mixture of safety and aerospace cachet, but sometimes struggled to shift their image of being boring.

The Americans were still in the middle of their love affair with the large and the rugged, at the expense of convenience and value-for-money.

Stereotypically, my fellow-countrymen majored on agricultural charm, or wooden-panelled nostalgia, but struggled with the demands of electronics.

Nowadays, the quality and reliability of cars are much closer to each other. Most manufacturers have products with similar features and performance and economy ratings. If we take financial issues to one side, differences are more likely to related to design, or how people perceive a brand. Today the quality of a Ford is not far behind that of a Toyota. The styling of a Honda can be as dramatic as an Alfa Romeo. Lexus and Audi are playing in areas previously the preserve of BMW and Mercedes and so on.

To me this is also where the market for BI tools is at present. It is relatively mature and the differences between product sets are less than before.

Of course this doesn’t mean that the BI field will not be shaken up by some new technology or approach (in-memory BI or SaaS come to mind). This would be the equivalent of the impact that the first hybrid cars had on the auto market.

However, from the point of view of implementations, most BI tools will do at least an adequate job and picking one should not be your primary concern in a BI project.

Ajay- SAS Institute Chief Marketing Officer, Jim Davis (interviewed with this blog) points to the superiority of business analytics rather than business intelligence as an over hyped term. What numbers, statistics and graphs would you quote rather than semantics to help re direct those perceptions?

I myself use SAS,SPSS, R and find the decision management capabilities as James Taylor calls Decision Management much better enabled than by simple ETL tools or reporting and aggregating graphs tools in many BI tools.

Peter- I have expended quite a lot of energy and hundreds of words on this subject. If people are interested in my views, which are rather different to those of Jim Davis, then I’d suggest that they read them in a series of articles starting with Business Analytics vs Business Intelligence [URL http://peterthomas.wordpress.com/2009/03/28/business-analytics-vs-business-intelligence/ ].

I will however offer some further thoughts and to do this I’ll go back to my car industry analogy. In a world where cars are becoming more and more comparable in terms of their reliability, features, safety and economy, things like styling, brand management and marketing become more and more important.

As the true differences between BI vendors narrow, expect more noise to be made by marketing departments about how different their products are.

I have no problem in acknowledging SAS as a leader in Business Analytics, too many people I respect use their tools for me to think otherwise. However, I think a better marketing strategy for them would be to stick to the many positives of their own products. If they insist on continuing to trash competitors, then it would make sense for them to do this in a way that couldn’t be debunked by a high school student after ten seconds’ reflection.

Ajay- In your opinion what is the average RoI that a small, large medium enterprise gets by investing in a business intelligence platform. What advice would you give to such firms (separately) to help them make their minds?

Peter- The question is pretty much analogous to “What are the benefits of opening an office in China?” the answer is going to depend on what the company does; what their overall strategy is and how a China operation might complement this; whether their products and services are suitable for the Chinese market; how their costs, quality and features compare to local competitors; and whether they have cracked markets closer to home already.

To put things even more prosaically, “How long is a piece of string?”

Taking to one side the size and complexity of an organisation, BI projects come in all shapes and sizes.

Personally I have led Enterprise-wide, all-pervasive BI projects which have had a profound impact on the company. I have also seen well-managed and successful BI projects targeted on a very narrow and specific area.

The former obviously cost more than the latter, but the benefits are commensurately greater. In fact I would argue that the wider a BI project is spread, the greater its payback. Maybe lessons can be learnt and confidence built in an initial implementation to a small group, but to me the real benefit of BI is realised when it touches everything that a company does.

This is not based on a self-interested boosting of BI. To me if what we want to do is take better business decisions, then the greater number of such decisions that are impacted, the better that this is for the organisation.

Also there are some substantial up-front investments required for BI. These would include: building the BI team; establishing the warehouse and a physical architecture on which to deliver your application. If these can be leveraged more widely, then costs come down.

The same point can be made about the intellectual property that a successful BI team develops. This is one reason why I am a fan of the concept of BI Competency Centres [URL http://peterthomas.wordpress.com/2009/05/11/business-intelligence-competency-centres/ ].

I have been lucky enough to contribute to an organisation turning round from losing hundreds of millions of dollars to recording profits of twice that magnitude. When business managers cite BI as a major factor behind such a transformation, then this is clearly a technology that can be used to dramatic effect.

Nevertheless both estimating the potential impact of BI and measuring its actual effectiveness are non-trivial activities. A number of different approaches can be taken, some of which I cover in my article:

Measuring the benefits of Business Intelligence [URL http://peterthomas.wordpress.com/2009/02/26/measuring-the-benefits-of-business-intelligence/ ]. As ever there is no single recipe for success.

Ajay-. Which BI tool/ code are you most comfortable with and what are its salient points?

Peter –Although I have been successful with elements of the IBM-Cognos toolset and think that this has many strong points, not least being relatively user-friendly, I think I’ll go back to my earlier comments about this area being much less important than many others for the success of a BI project.

Ajay -How do you think cloud computing will change BI? What percentage of BI budgets go to data quality and what is eventual impact of data quality on results?

Peter –I think that the jury is still out on cloud computing and BI. By this I do not mean that cloud computing will not have an impact, but rather that it remains unclear what this impact will actually be.

Given the maturity of the market, my suspicion is that the BI equivalent of a Google is not going to emerge from nowhere. There are many excellent BI start-ups in this space and I have been briefed by quite a few of them.

However, I think the future of cloud computing in BI is likely to be determined by how the likes of IBM-Cognos, SAP-BusinessObjects and Oracle-Hyperion embrace the area.

Having said this, one of the interesting things in computing is how easy it is to misjudge the future and perhaps there is a potential titan of cloud BI currently gestating in the garage so beloved of IT mythology.

On data quality, I have never explicitly split out this component of a BI effort. Rather data quality has been an integral part of what we have done. Again I have taken a four-pillared approach:

  • improve how the data is entered;
  • make sure your interfaces aren’t the problem;
  • check how the data has been entered / interfaced;
  • and don’t suppress bad data in your BI.

The first pillar consists of improved validation in front-end systems – something that can be facilitated by the BI team providing master data to them – and also a focus on staff training, stressing the importance to the organisation of accurately recording certain data fields.

The second pillar is more to do with the general IT Architecture and how this relates to the Information Architecture, again master data has a role to play, but so does ensuring that the IT culture is one in which different teams collaborate well and are concerned about what happens to data when it leaves “their” systems.

The third pillar is the familiar world of after-the-fact data quality reports and auditing, something that is necessary, but not sufficient, for success in data quality.

Finally there is what I think can be one of the most important pillars; ensuring that the BI system takes a warts-and-all approach to data. This means that bad data is highlighted, rather than being suppressed. In turn this creates pressure for the problems to be addressed where they arise and creates a virtuous circle.

For those who might be interested in this area, I expand on it more in Using BI to drive improvements in data quality [URL http://peterthomas.wordpress.com/2009/02/11/using-bi-to-drive-improvements-in-data-quality/ ].

Ajay- You are well known with England’s rock climbing and boulder climbing community. A fun question- what is the similarity between a BI implementation/project and climbing a big boulder.

Peter –I would have to offer two minor clarifications.

First it is probably my partner who is better known in climbing circles, via here blog [URL http://77jenn.blogspot.com/ ] and articles and reviews that she has written for the climbing press; though I guess I can take credit for most of the photos and videos.

Second, particularly given the fact that a lot of our climbing takes place in Wales, I should acknowledge the broader UK climbing community and also mention our most mountainous region of Scotland.

Despite what many inhabitants of Sheffield might think to the contrary, there is life beyond Stanage Edge [URL http://en.wikipedia.org/wiki/Stanage ].

I have written about the determination and perseverance that are required to get to the top of a boulder, or indeed to the top of any type of climb [URL http://peterthomas.wordpress.com/2009/03/31/perseverance/ ].

I think those same qualities are necessary for any lengthy, complex project. I am a firm believer that the true benefits of BI are only realised when it leads to cultural transformation. Certainly the discipline of change management has many parallels with rock climbing. You need a positive attitude and a strong belief in your ultimate success, despite the inevitable setbacks. If one approach doesn’t yield fruit then you need to either fine-tune or try something radically different.

I suppose a final similarity is the feeling that you get having completed a climb, particularly if it is at the limit of your ability and has taken a long time to achieve. This is one of both elation and deep satisfaction, but is quickly displaced by a desire to find the next challenge.

This is something that I have certainly experienced in business life and I think the feelings will be familiar to many readers.

Biography-

 

Peter Thomas has led all-pervasive, Business Intelligence and Cultural Transformation projects serving the needs of 500+ users in multiple business units and service departments across 13 European and 5 Latin American countries. He has also developed Business Intelligence strategies for operations spanning four continents. His BI work has won two industry awards including “Best Enterprise BI Implementation”, from Cognos in 2006 and “Best use of IT in Insurance”, from Financial Sector Technology in 2005. Peter speaks about success factors in both Business Intelligence and the associated Change Management at seminars across both Europe and North America and writes about these areas and many other aspects of business, technology and change on his blog [URL http://peterthomas.wordpress.com ].

Interview Jill Dyche Baseline Consulting

Here is an interview with Jill Dyche, co-Founder Baseline Consulting and one of the best Business Intelligence consultants and analysts. Her writing is read by huge portion of the industry and has influenced many paradigms.She is also Author of e-Data, The CRM Handbook, and Customer Data Integration: Reaching a Single Version of the Truth.

BI tools are not recommended when they’re the first topic in a BI discussion.

Jill Dyche, Baseline Consulting

Ajay- What approximate Return of Investment would you give to various vendors within Business Intelligence?

Jill- You don’t kid around do you, Ajay? In general the answer has everything to do with the problem BI is solving for a company. For instance, we’re working on deploying operational BI at a retailer right now. This new program is giving people in the stores more power to make decisions about promotions and in-store events. The projected ROI is $300,000 per store per year—and the retailer has over 1000 stores. In another example, we’re working with an HMO client on a master data management project that helps it reconcile patient data across hospitals, clinics, pharmacies, and home health care. The ROI could be life-saving. So, as they say in the Visa commercials: Priceless.

Ajay- What is impact of third party cloud storage and processing do you think will be there on Business Intelligence consulting?

Jill- There’s a lot of buzz about cloud storage for BI, most of it is coming from the VC community at this point, not from our clients. The trouble with that is that BI systems really need control over their storage. There are companies out there—check out a product called RainStor—that do BI storage in the cloud very well, and are optimized for it. But most “cloud” environments geared to BI are really just hosted offerings that provide clients with infrastructure and processing resources that they don’t have in-house.  Where the cloud really has benefits is when it provides significant processing power to companies that can’t build it easily themselves.

Ajay- What are the top writing tips would you give to young struggling business bloggers especially in this recession.

Jill- I’d advise bloggers to write like they talk, a standard admonishment by many a professor of Business Writing. So much of today’s business writing—especially in blogs—is stilted, overly-formal, and pedantic. I don’t care if your grammar is accurate; if your writing sounds like the Monroe Doctrine, no one will read it. (Just give me one quote from the Monroe Doctrine. See what I mean?) Don’t use the word “leverage” when you can use the word “use.” Be genuine and conversational. And avoid clichés like the plague.

Ajay-  How would you convince young people especially women to join more science careers. Describe your own career journey.

Jill- As much as we need those role models in science, high-tech, and math careers, I’d tell them to only embrace it if they really love it. My career path to high-tech was unconventional and unintentional. I started as a technical writer specializing in relational databases just as they were getting hot. One thing I know for sure is if you want to learn about something interesting, be willing to roll up your sleeves and work with it. My technical writing about databases, and then data warehouses, led to some pretty interesting client work.

Sure I’ve coded SQL in my career, and optimized some pretty hairy WHERE clauses. But the bigger issue is applying that work to business problems. Actually I’m grateful that I wasn’t a very good programmer. I’d still be waiting for that infinite loop to finish running.

Ajay- What are the areas within an enterprise where implementation of BI leads to the most gains. And when are BI tools not recommended?

Jill- The best opportunities for BI are for supporting business growth. And that typically means BI used by sales and marketing. Who’s the next customer and what will they buy? It’s answers to questions like these that can set a company apart competitively and contribute to both the top and bottom lines.

Not to be too heretical, but to answer your second question: BI tools are not recommended when they’re the first topic in a BI discussion. We’ve had several “Don’t go into the light” conversations with clients lately where they are prematurely looking at BI tools rather than examining their overall BI readiness. Companies need to be honest about their development processes, existing skill sets, and their data and platform infrastructures before they start phoning up data visualization vendors. Unfortunately, many people engage BI software vendors way before they’re ready.

Ajay- You and your partner Evan wrote what was really the first book on Master Data Management. But you’d been in the BI and data warehousing world before that. Why MDM?

Jill- We just kept watching what our clients couldn’t pull off with their data warehouses. We saw the effort they were going through to enforce business rules through ETL, and what they were trying to do to match records across different source systems. We also saw the amount of manual effort that went into things like handling survivor records, which leads to a series of conversations about data ownership.

Our book (Customer Data Integration: Reaching a Single Version of the Truth, Wiley) has as much to do with data management and data governance as it does with CDI and MDM. As Evan recently said in his presentation at the TDWI MDM Insight event, “You can’t master your data until you manage your data.” We really believe that, and our clients are starting to put it into practice too.

Ajay- Why did you and Evan choose to focus on customer master data (CDI) rather than a more general book on MDM?

Jill- There were two reasons. The first one was because other master data domains like product and location have their own unique sets of definitions and rules. Even though these domains also need MDM, they’re different and the details around implementing them and choosing vendor products to enable them are different. The second reason was that the vast majority of our clients started their MDM programs with customer data. One of Baseline’s longest legacies is enabling the proverbial “360-degree view” of customers. It’s what we knew.

Ajay- What’s surprised you most about your CDI/MDM clients?

Jill- The extent to which they use CDI and MDM as the context for bringing IT and the business closer together. You’d think BI would be ideal for that, and it is. But it’s interesting how MDM lets companies strip back a lot of the tool discussions and just focus on the raw conversations about definitions and rules for business data. Business people get why data is so important, and IT can help guide them in conversations about streamlining data quality and management. Companies like Dell have used MDM for nothing less than business alignment.

Ajay- Any plan to visit India and China for giving lectures?

Jill- I just turned down a trip to China this fall because I had a schedule conflict, which I’m really bummed about. Far as India is concerned, nothing yet but if you’re looking for houseguests let me know.(Ajay- sure I have a big brand new house just ready- and if I visit USA may I be a house guest too?)

About Jill Dyche-

Jill blogs at http://www.jilldyche.com/. where she takes the perpetual challenge of business-IT alignment head on in her trenchant, irreverent style.

Jill Dyché is a partner and co-founder of Baseline Consulting. Her role at Baseline is a combination of best-practice expert, industry gadfly, key client advisor, and all-around thought leader. She is responsible for key client strategies and market analysis in the areas of data governance, business intelligence, master data management, and customer relationship management. Jill counsels boards of directors on the strategic importance of their information investments.

Author

Jill is the author of three books on the business value of IT. Jill’s first book, e-Data (Addison Wesley, 2000) has been published in eight languages. She is a contributor to Impossible Data Warehouse Situations: Solutions from the Experts (Addison Wesley, 2002), and her book, The CRM Handbook (Addison Wesley, 2002), is the bestseller on the topic.

Jill’s work has been featured in major publications such as Computerworld, Information Week, CIO Magazine, the Wall Street Journal, the Chicago Tribune and Newsweek.com. Jill’s latest book, Customer Data Integration (John Wiley and Sons, 2006) was co-authored with Baseline partner Evan Levy, and shows the business breakthroughs achieved with integrated customer data.

Industry Expert

Jill is a featured speaker at industry conferences, university programs, and vendor events. She serves as a judge for several IT best practice awards. She is a member of the Society of Information Management and Women in Technology, a faculty member of TDWI, and serves as a co-chair for the MDM Insight conference. Jill is a columnist for DM Review, and a blogger for BeyeNETWORK and Baseline Consulting.

Interview Alison Bolen SAS.com

My biggest editing soapbox right now is to encourage brevity. We’re so used to writing white papers, brochures and magazine articles that the concept of throwing down 200 words on a topic from your day is a very foreign exercise. –

 

Alison Bolen  Editor-in-Chief sascom

Here is an interview with Alison Bolen the editor-in-chief of SAScom , online magazaine of the SAS Institute. Alison talks of the challenges in maintaining several of the topmost expertise blogs on SAS ,Business Analytics and Business Intelligence.

Ajay- Describe your career in the technology writing and publishing area. What advice would you give to young Web publishers and content producers just entering the job market in this recession? Describe your journey within SAS.

Alison- I started at SAS in 1999 as a summer student working as a contributing editor for SAS Communications magazine. Before the end of the year, I came on full time and soon transitioned to writing and editing for the Web. At that time, we were just developing the strategy for the customer support site and e-newsletters. As the first editor for the SAS Tech Report, I led marketing efforts that brought in 15,000 opt-in subscribers within six months. A year later, I switched to writing and editing customer success stories, which I enjoyed doing until I took on the role of Editor-in-Chief for sascom® magazine in 2006. We started our blogging program in 2007, and I’ve been actively involved in coaching SAS bloggers for the past two years.

Outside of SAS, I’ve written for Southwest Hydrology Magazine, the Arizona Daily Star and other regional papers. My bachelor’s degree is in magazine journalism and my master’s degree is in technical and business communications.

If you’re just beginning your career as a writer, start a blog and stick with it. There’s no better way to get daily writing practice, learn the basics of search engine optimization and start to understand what works online.

Ajay www.SAS.com/Blogs has many, many blogs by experts, RSS feeds and even covers the annual SAS conference with video content. In terms of social media adaptation, what prompts you to stay ahead of the competition in ensuring marketing and technical communications for brand awareness?

What do you think are the basics of setting up a social media presence for a company, regardless of size?

Alison- Social media excites me because you can cut through the clutter and be real. Our new business forecasting blog by Michael Gilliland is a good example. Teaching people how to forecast better is his top priority, not selling software. Our overarching goal for the blogging program is similar: to share and develop expertise.

We’re big advocates of aligning your social media presence with existing marketing goals. We have a few grass-roots teams interested in social media, and we have a director-level Marketing 2.0 Council that our Social Media Manager Dave Thomas leads to determine broad guidelines and strategies. But the overarching concept is to look at the goals of your individual marketing campaigns first, and then determine which social media channels might help you reach those goals.

Most of all, take off your marketing hat when you enter the blog, network or forum. Social media consists of individuals, for the most part, and not companies, so be sure to offer value as a colleague and build relationships.

Ajay- I noticed that SAS.com/ Blogs are almost ad free – even of SAS products – apart from a simple banner of the company. Was this a deliberate decision, and if so, why?

Alison- Yes, most of the SAS blogs were intentionally created to help establish the individual blogger’s expertise – not to promote SAS products or services. One positive side effect is that SAS – by extension – builds credibility as well. But we really do see the blogs as a place to discuss concepts and ideas more than products and tools.

Ajay- What distinguishes good writers on blogs from bad writers on blogs? How about some tips for technical blog writing and especially editing (since many writers need editors more than they realize)?

Alison- The best blog writers know how to simplify and explain even the most mundane, everyday processes. This is true of personal and technical blog writing. If you can look at your life or your work and see what piece of it others would find interesting or want to know more about – and then know how to describe that sliver of yourself clearly – you have what it takes to be a good blogger. Chris Hemedinger does this well on The SAS Dummy blog.

My biggest editing soapbox right now is to encourage brevity. We’re so used to writing white papers, brochures and magazine articles at SAS that the concept of throwing down 200 words on a random topic from your day is a very foreign exercise. You have to learn how to edit your day – not just your writing – to find those topics and distill those thoughts into quick snippets that keep readers interested. And don’t forget it’s okay to have fun!

Ajay- I balance one blog, small consulting assignments and being a stay-at-home dad for an 18-month old. How easy is it for you to balance being editor of sascom, given the huge content your sites create, and three kids? Does working for SAS and its employee-friendly reputation help you do so?

Alison- I couldn’t balance work and kids without a whole lot of help from friends and family, that’s for sure. And the employee-friendly benefits help too. The biggest benefit is the cultural mindset, though, not any individual policy. My boss and my boss’ boss are both working mothers, and they’re balancing the same types of schedules. There’s an understanding about finding a healthy work-life balance that permeates SAS from top to bottom.

Ajay- As a social media consultant it is a weekly struggle for me to convince companies to discontinue registration for normal content (but keep it for special events), use a lot more video tutorials and share content freely across the Web. Above all, convincing busy senior managers to start writing a blog or an article is an exercise in diplomacy itself. How do you convince senior managers to devote time to content creation?

Alison- In a lot of areas, the content is already being created for analyst presentations, press interviews and consulting briefs. It’s really a matter of understanding how to take those existing materials and re-present them in a more personal voice. Not everyone can – or should – do it. You have to decide if you have the voice for it and whether or not it will bring you value beyond what you’re getting through your existing channels.

Ajay- Any plans to visit India and have a SAS India blogathon?

Alison- Alas, not this year.

Maybe I will visit Cary,NC then 🙂


Bio:
Alison Bolen is the Editor of sascom magazine and the sascom voices blog, where SAS experts publish their thoughts on popular and emerging business and technology trends worldwide. Since starting at SAS in 1999, Alison has edited print publications, Web sites, e-newsletters, customer success stories and blogs.

Alison holds a bachelor’s degree in magazine journalism from Ohio University and a master’s degree in technical writing from North Carolina State University.

1) Describe your career in the technology writing and publishing area. What advice would you give to young Web publishers and content producers just entering the job market in this recession? Describe your journey within SAS.

I started at SAS in 1999 as a summer student working as a contributing editor for SAS Communications magazine. Before the end of the year, I came on full time and soon transitioned to writing and editing for the Web. At that time, we were just developing the strategy for the customer support site and e-newsletters. As the first editor for the SAS Tech Report, I led marketing efforts that brought in 15,000 opt-in subscribers within six months. A year later, I switched to writing and editing customer success stories, which I enjoyed doing until I took on the role of Editor-in-Chief for sascom® magazine in 2006. We started our blogging program in 2007, and I’ve been actively involved in coaching SAS bloggers for the past two years.

Outside of SAS, I’ve written for Southwest Hydrology Magazine, the Arizona Daily Star and other regional papers. My bachelor’s degree is in magazine journalism and my master’s degree is in technical and business communications.

If you’re just beginning your career as a writer, start a blog and stick with it. There’s no better way to get daily writing practice, learn the basics of search engine optimization and start to understand what works online.
2) SAS.com/Blogs has many, many blogs by experts, RSS feeds and even covers the annual SAS conference with video content. In terms of social media adaptation, what prompts you to stay ahead of the competition in ensuring marketing and technical communications for brand awareness?

What do you think are the basics of setting up a social media presence for a company, regardless of size?

Social media excites me because you can cut through the clutter and be real. Our new business forecasting blog by Michael Gilliland is a good example. Teaching people how to forecast better is his top priority, not selling software. Our overarching goal for the blogging program is similar: to share and develop expertise.

We’re big advocates of aligning your social media presence with existing marketing goals. We have a few grass-roots teams interested in social media, and we have a director-level Marketing 2.0 Council that our Social Media Manager Dave Thomas leads to determine broad guidelines and strategies. But the overarching concept is to look at the goals of your individual marketing campaigns first, and then determine which social media channels might help you reach those goals.

Most of all, take off your marketing hat when you enter the blog, network or forum. Social media consists of individuals, for the most part, and not companies, so be sure to offer value as a colleague and build relationships.


3) I noticed that SAS.com/ Blogs are almost ad free – even of SAS products – apart from a simple banner of the company. Was this a deliberate decision, and if so, why?

Yes, most of the SAS blogs were intentionally created to help establish the individual blogger’s expertise – not to promote SAS products or services. One positive side effect is that SAS – by extension – builds credibility as well. But we really do see the blogs as a place to discuss concepts and ideas more than products and tools.
4) What distinguishes good writers on blogs from bad writers on blogs? How about some tips for technical blog writing and especially editing (since many writers need editors more than they realize)?

The best blog writers know how to simplify and explain even the most mundane, everyday processes. This is true of personal and technical blog writing. If you can look at your life or your work and see what piece of it others would find interesting or want to know more about – and then know how to describe that sliver of yourself clearly – you have what it takes to be a good blogger. Chris Hemedinger does this well on The SAS Dummy blog.

My biggest editing soapbox right now is to encourage brevity. We’re so used to writing white papers, brochures and magazine articles at SAS that the concept of throwing down 200 words on a random topic from your day is a very foreign exercise. You have to learn how to edit your day – not just your writing – to find those topics and distill those thoughts into quick snippets that keep readers interested. And don’t forget it’s okay to have fun!
5) I balance one blog, small consulting assignments and being a stay-at-home dad for an 18-month old. How easy is it for you to balance being editor of sascom, given the huge content your sites create, and three kids? Does working for SAS and its employee-friendly reputation help you do so?

I couldn’t balance work and kids without a whole lot of help from friends and family, that’s for sure. And the employee-friendly benefits help too. The biggest benefit is the cultural mindset, though, not any individual policy. My boss and my boss’ boss are both working mothers, and they’re balancing the same types of schedules. There’s an understanding about finding a healthy work-life balance that permeates SAS from top to bottom.

6) As a social media consultant it is a weekly struggle for me to convince companies to discontinue registration for normal content (but keep it for special events), use a lot more video tutorials and share content freely across the Web. Above all, convincing busy senior managers to start writing a blog or an article is an exercise in diplomacy itself. How do you convince senior managers to devote time to content creation?

In a lot of areas, the content is already being created for analyst presentations, press interviews and consulting briefs. It’s really a matter of understanding how to take those existing materials and re-present them in a more personal voice. Not everyone can – or should – do it. You have to decide if you have the voice for it and whether or not it will bring you value beyond what you’re getting through your existing channels.

7) Any plans to visit India and have a SAS India blogathon?

Alas, not this year.

Interview Karim Chine BIOCEP (Cloud Computing with R)

Here is an interview with Karim Chine of http://www.biocep.net/

Working with an R or Scilab on clusters/grids/clouds becomes as simple as working with them locally-

Karim Chine, Biocep.

Ajay- Please describe your career in the field of science. What advice would you give to young science graduates in this recession.

Karim- My original background is in theoretical Physics, I did my Master’s thesis at the Ecole Normale’s Statistical Physics Laboratory where I worked on phase separation in two-dimensional additive mixtures with Dr Werner Krauth. I came to computer science after graduating from the Ecole Polytechnique and I spent two years at TELECOM ParisTech studying software architecture and distributed systems design. I worked then for the IBM Paris Laboratory (VisualAge Pacbase applications’ generator), Schlumberger (Over the Air Platform and Web platform for smartcards personalization services), Air France (SSO deployment) and ILOG (OPL-CPLEX-ODM Development System). This gave me the intense exposure to real world large-scale software design. I crossed the borders of cultural, technical and organizational domains several times and I worked with a broad palette of technologies with some of the best and most innovative engineers. I moved to Cambridge in 2006 and I worked for the European Bioinformatics Institute. It’s where I started dealing with the integration of R into various types of applications. I left the EBI in November 2007. I was looking for an institutional support to help me in bringing into reality a vision that was becoming clearer and clearer about a universal platform for scientific and statistical computing. I failed in getting that support and I have been working on BIOCEP full time for most of the last 18 months without being funded. Few days of consultancy given here and there allowed me to keep going. I spent several weeks at Imperial College, at the National Center for e-Social Sciences and at Berkeley’s department of statistics during that period. Those visits were extremely useful in refining the use cases of my platform. I am still looking for a partner to back the project. You asked me to give advice. The unique advice I would give is to be creative and to try again and again to do what you really want to do. Crisises come and go, they will always do and extreme situations are part of life. I believe hard work and sincerity can prevail anything.

Ajay- Describe BIOCEP’s scope and ambition.

What are the current operational analytics that can be done by users having data.

Karim- My first ambition with BIOCEP is to deliver a universal platform for scientific and statistical computing and to create an open, federative and collaborative environment for the production, sharing and reuse of all the artifacts of computing. My second ambition is to enhance dramatically the accessibility of mathematical and statistical computing, to make HPC a commonplace and to put new analytical, numerical and processing capabilities in the hands of everyone (open science).

The Open source software Conquest has gone very far. Environments like R or Scilab, technologies like Java, Operating Systems like Linux-Ubuntu, and tools like OpenOffice are being used by millions of people. Very little doubt remains about the OSS’s final victory in some domains. The cloud is already a reality and it will take computing to a whole new realm. What is currently missing is the software that, by making the Cloud’s usage seamless, will create new ecosystems and will provide rooms for creativity, innovation and knowledge discovery of an unprecedented scale.

BIOCEP is one more building block into this. BIOCEP is built on top of R and Scilab and anything that you can do within those environments is accessible through BIOCEP. Here is what you have uniquely with this new R/Scilab-based e-platform:

– High productivity via the most advanced cross-platform workbench available for the R environment.

– Advanced Graphics: with BIOCEP, a graphic transducer allows the rendering on client side of graphics produced on server side and enables advanced capabilities like zooming/unzooming/scrolling for R graphics. a client side mouse tracker allows to display dynamically information related to the graphics and depending on coordinates. Several virtual R Devices showing different data can be coupled in zooming/scrolling and this helps comparing visually complex graphics.

– Extensibility with plug-ins: new views (IDE-like views, analytical interfaces…) can be created very easily either programmatically or via drag-and-drop GUI designers.

– Extensibility with server-side extensions: any java code can be packaged and used on server side. The code can interact seamlessly with R and Scilab or provide generic bridges to other software. For example, I provide an extension that allows you to use openoffice as a universal converter between various files formats on server side.

– Seamless High Performance Computing: working with an R or Scilab on clusters/grids/clouds becomes as simple as working with them locally. Distributed computing becomes seamless, creating a large number R and Scilab remote engines and using them to solve large scale problems becomes easier than ever. From the R console the user can create logical links to existing R engines or to newly created ones and use those logical links to pilot the remote workers from within his R session. R functions enable using the logical links to import/export variables from the R session to the different workers and vice versa. R commands/scripts can be executed by the R workers synchronously or asynchronously. Many logical R links can be aggregated into one logical cluster variable that can be used to pilot the R workers in a coordinated way. A cluster.apply function allows the usage of the logical cluster to apply a function to a big data structure by slicing it and sending elementary execution commands to the workers. The workers apply the user’s function to the slices in parallel. The elementary results are aggregated to compose the final result that becomes available within the R session.

– Collaboration: your R/scilab server running in the cloud can be accessed simultaneously by you and your collaborators. Everything gets broadcasted including Graphics. A spreadsheet enables to view and edit data collaboratively. Anyone can write plug-ins to take advantage of the collaborative capabilities of the frameworks. If your IP address is public, you can provide a URL to anyone and get him connect to your locally running R.

– Powerful frameworks for Java developers: BIOCEP provides Frameworks and tools to use R as if it was an Object Oriented Java Toolkit or a Web Toolkit for R-based dynamic application.

– Webservices for C#, Perl, Python users/developers: Most of the capabilities of BIOCEP including piloting of R/Scilab engines on the cloud for distributed computing or for building scalable analytical web application are accessible from most of the programming languages thanks to the SOAP front-end.

– RESTful API: simple URLs can perform computing using R/Scilab engines and return the result as an XML or as graphics in any format. This works like google charts and has all the power of R since the graphic is described with an R script provided as a parameter of the URL. The same API can be exposed on demand by the workbench. This allow for example to integrate a Cloud-R with Excel or OpenOffice. The workbench works as a bridge between the cloud and those applications.

– Advanced Pooling framework for distributed resources: useful for deploying pools of R/scilab engines on multi nodes systems and get them used simultaneously by several distributed client processes in a scalable/optimal way. A supervision GUI is provided for a user friendly management of the pools/nodes/engines.

– Simultaneous use of R and Scilab: Using java scripting, data can be transferred from R to Scilab and vice versa.

Ajay- Could you tell us about a successful BIOCEP installation and what it led to? Can BIOCEP be used by the rest of the R community for other packages? What would be an ideal BIOCEP user /customer for whom cloud based analytics makes more sense ?

Karim- BIOCEP is still in pre-beta stage. However it is a robust and polished pre-Beta that several organizations are already using. Janssen Pharmaceutica is using it to create and deliver statistical applications for drug discovery that use R engines running on their backend servers. The platform is foreseen there as the way to go for an ultimate optimization of some of their data analysis pipelines. Janssen’s head of statistics said to be very much interested in the capabilities given by BIOCEP to statisticians to create their own analytical User Interfaces and deliver them with their models without needing specific software development skills. Shell is creating BIOCEP-based applications prototypes to explore the feasibility and advantages of migrating some of Shell’s applications to the Cloud. One group from Shell Global Solutions is planning to use BIOCEP for running scilab in the cloud for Corrosion simulation modeling. Dr Ivo Dinov’s team at UCLA is studying the migration of some the SOCR applications to the BIOCEP platform as plug-ins and extensions. Dr Ivo Dinov also applied for an important grant for building DISCb (Distributed Infrastructure for Statistical Computing in Biomedicine). If the grant application is successful, BIOCEP will be the backbone at software architecture level of that new infrastructure. In cooperation with the Institute of Biostatistics, Leibniz University of Hannover, Bernd Bischl and Kornelius Rohmeyer have developed a framework to user friendly R-GUIs of different complexity. The toolkit uses BIOCEP as an R-backend since release 2.0. Several small projects have been implemented using this framework and some are in production such as an application for education in biostatistics at the University of Hannover. Also the ESNATS project is planning to use the BIOCEP frameworks. Some development is being done at the EBI to customize the workbench and use it to give to the end user the possibility to run R and Bioconductor on the EBI’s LSF cluster.

I’ve been in touch with Phil Butcher, Sanger’s head of IT and he is considering the deployment of BIOCEP on Sanger’s systems simultaneously with Eucalyptus. The same type of deployment has been discussed with the director of OMII-UK, Neil Chue Hong. BIOCEP’s deployment is probably going to follow the deployment of the Eucalyptus System on NGS. Tena Sakai deployed BIOCEP at the Ernest Gallo Clinic and Research Centre and he is currently exploring the usage of the R on the Cloud via BIOCEP (Eucalyptus / AWS). The platform has been deployed by a small consultancy company specializing in R on several London-based investment banks’ systems. I have had a go ahead form Nancy Wilkins Diher (Director for Science Gateways, SDSC) for deploying on TeraGrid, a deployment on EGEE has been discussed with Dr Steven Newhouse (EGEE Technical Director). Both deployments are in standby at the moment.

Quest Diagnostics is planning to use BIOCEP extensively. Sudeep Talati (University of Manchester) is doing his Master’s project on BIOCEP. He is supervised by Professor Andy Brass and he is exploring the use of a BIOCEP-based infrastructure to deliver microarray analysis workflows in a simple and intuitive way to biologists with and without the Cloud. In Manchester, Robin Pinning (e-Science team leader, Research Computing Services) has the deployment of BIOCEP on Manchester’s research cluster on his agenda…

As I have said, anything that you can do with R including installing, loading and using any R package is accessible through BIOCEP. The platform aims to be universal and to become a tool for productivity and collaboration used by everyone dealing with computing/analytics with or without the cloud.

The Cloud whether it is public or private will be generalized and everyone will become a cloud user in one way or another

Ajay- What motivated you to build BIOCEP and mash cloud computing and R. What scope do you see for cloud computing in developing countries in Asia and Africa?

Karim– When I was at the EBI, I worked on the integration of R within scalable web applications. I explored and tested the available frameworks and tools and all of them were too low level or too simple to answer the problem. I decided to build new frameworks. I had the opportunity to be able to stand on the shoulders of giants.

Simon Urbanek’s packages already bridged the C-API of R with Java reliably. Martin Morgan’s RWebsevices package defined class mappings between R types, including S4 classes, and java.

Progressively R became usable as a Java object oriented toolkit, then as a Java Server. Then I built a pooling framework for distributed resources that made it possible for multiple clients to use multiple R engines optimally.

I started building a GUI to validate the server’s increasingly sophisticated API. That GUI became progressively the workbench.

When I was at Imperial, I worked with the National Grid Service team at the Oxford e-Research Centre to deploy my platform on Oxford’s core cluster. That deployment led to many changes in the architecture to meet all the security requirements.

It was obvious that the next step was to make BIOCEP available on Amazon’s Cloud. Academic Grids are for researchers and the cloud is for everyone. Making the platform work seamlessly on EC2 took few months. With the cloud came the focus on collaborative features (collaborative views, graphics, spreadsheets…).

I can only talk about the example of a country I know, Tunisia, and I guess some of this applies to Asian Countries. Even if the broadband is everywhere today and is becoming accessible and affordable by a majority of Tunisians, I am not sure that the adoption of the cloud would happen soon.

Simple considerations like the obligation to pay for the compute cycles in dollars (and not in dinars) are a barrier for adoption. Spending foreign currencies is subject to several restrictions in general for companies and for individuals; few Tunisians have credit cards that can be used to pay Amazon. Companies would prefer to buy and administer their own machines because the cost of operation and maintenance is lower in Tunisia than it is in Europe/US.

Even if the cloud would help in giving Tunisian researchers access to affordable Computing cycles on demand, it seems that most of them have learned to live without HPC resources and that their research is more theoretical and less computational than it could be. Others are collaborating with research groups in Europe (France) and they are using those European groups’ infrastructures.

Ajay- How would BIOCEP address the problem of data hygiene, data security and privacy. Is encrypted and compressed data transfers supported or planned?

Karim- With BIOCEP, a computational engine is exposed as a distributed component via a single mono-directional HTTP port. When you run such an engine on an EC2 instance you have two options:

  • 1/ totally sandbox the machine (via the security group) and leave only the SSH port open.
  • Private Key authentication is required to access the machine. In this case you use an SSH Tunnel (created with a tool like Putty for example) which allows you to see the engine as if it was running on your local machine on a port of your choice, the one specified for creating the Tunnel.
  • When you start the Virtual Workbench and connect in Http mode to your local host via the specified port, you are effectively connecting to the EC2-R engine. 100% of the information exchanged between your workbench and the engine, including your data, is ciphered thanks to the SSH tunnel.
  • The virtual workbench embeds JSCH and can create the Tunnel for you automatically. This mode doesn’t allow collaboration since it requires the private key to let the workbench talk to the EC2 R/Scilab engine.
  • 2/ tell the EC2 machine at startup (via the “user data”) to require specific credentials from the user. When the machine starts running, the user needs to provide those credentials to get a session ID and to be able to pilot a virtual EC2 R/Scilab engine. This mode enables collaboration. The client (workbench/scripts) connects to the EC2 machine instance via HTTP (will be HTTPS in a near future).

Ajay- Suppose I have 20 gb per month of data and my organization decided to cut back on the number of annual expensive software. How can the current version of BIOCEP help me do the following?

Karim– Ways BIOCEP can help you right now.

1) Data aggregation and Reporting in terms of spreadsheet, presentation and graphs

  • BIOCEP provides a highly programmable server side spreadsheet.
  • It can be used interactively as a view of the workbench and simple clicks allow the transfer of data form cells to R variables and vice versa. It can be created and populated from R (console / scripts).
  • Any R function can be used within dynamically computed cells. The evaluation of those dynamic cells is done on server side and can use high performance computing functions. Macros allow adding reactivity to the spreadsheets.
  • A macro allows the user to execute any R code in response to a value change of an R variable or of the content of a range within a spreadsheet. Variables docking macros allow the mirroring of R variables of any type (vectors, matrixes, data frames..) with ranges within the spreadsheet in Read/Write mode

. Several ready-to-use User Interface components can be created and docked anywhere within the spreadsheet. Those components include

  • an R Graphics viewer (PDF viewer) showing Graphics produced by a user-defined R script and reactive on user-defined variables and cell ranges changes,
  • customizable sliders mirroring R variables,
  • Buttons executing user-defined R code when pressed,
  • Combo boxes mirroring factor variables ..

The spreadsheet-based analytical user interface can pilot an R running at any location (local R, Grid R, Cloud R…). It can be created in minutes just by pointing, clicking and copy/pasting.

Cells content+macros+reactive docked components can be saved in a zip file and become a Workbench plug-ins. Like all BIOCEP plug-ins, the spreadsheet-based GUI can be delivered to the end user via a simple URL. It can use a cloud-R or a local R created transparently on the user’s machine.

2) Build time series models, regression models

BIOCEP’s workbench is extensible and I am hoping that contributors will soon start writing plug-ins or converting available GUIs to BIOCEP plug-ins in order to make the creation of those models as easy as possible.

Biography-

Karim Chine
Karim chine graduated from the French Ecole Polytechnique and TELECOM ParisTech. He worked at Ecole Normale Supérieure-LPS (phase separation in two-dimensional additive mixture), IBM (VisualAge Pacbase), Schlumberger (Over the Air Platform and Web platform for smartcards personalization services), Air France (SSO deployment), ILOG (OPL-CPLEX-ODM Development System), European Bioinformatics Institute (Expression Profiler, Biocep) and Imperial College London-Internet Center (Biocep). He contributed to open source software (AdaBroker) and he is the author of the Biocep platform. He currently works on the seamless integration of the new platform within utility computing infrastructures (Amazon EC2), its deployment on Grids (NGS) and its usage as a tool for education and he tries to build collaborations with academic and industrial partners.

You can view his resume here http://www.biocep.net/scan/CV_Karim_Chine_June_2009.pdf

Interview Gary Cokins SAS Institute

Here is an interview with Gary Cokins , a well respected veteran of the Business Intelligence industry working with the SAS Institute. Gary has just launched his sixth book (wow!) and the gentlemen he is , he agreed to answer these questions en route to his constant traveling.Gary is the expert on performance measurement so we decided to quiz him a bit on this.

CIO’s need to shift their mindset from a technical one to a managerial one.- Gary Cokins, SAS Institute

Gary_Cokins_SAS_05

Ajay -Gary, please describe your career journey from a freshman in college to your position today. What are the key items of advice that you would give to high school students to encourage taking science careers in this recession?

COKINS: I have been very fortunate. After receiving my MBA in 1974 from the Northwestern University Kellogg Graduate School of Management, I worked in industry for ten years. I had the luck of being a financial controller at Fortune 100 corporation division and then becoming operations manager at the same location. I then had to “eat the financial data I was serving,” and it was a true wake-up call – much of the information was at best useless and at worst misleading. Later with Deloitte I was trained on the theory of constraints (TOC) methodology which indicted cost accounting as “enemy number one of productivity.” I learned about the shortcomings with how accountants make assumptions.

In 1988, when Professor Kaplan struck an exclusive relationship with KPMG Peat Marwick, I was recruited to KPMG with about three others with similar operational backgrounds as I to implement activity based cost management (ABC/M) systems but with using an ABC/M modeling software tool. I learned from experience. Four years later, my mentor Bob Bonsack, who had moved on from Deloitte to Electronic Data Systems (EDS) recruited me to head EDS’ cost management consulting. With about fifteen consultants, I was exposed to over a hundred implementations of cost systems. It was there that I experimented with creating a two day “ABC/M rapid prototyping” method that was radically different from the multi-month approach. By starting with a quick vision of what their ABC/M system would look like, companies could iteratively re-model to the level of detail, granularity, and accuracy needed to support analysis and decisions. It did not initially require a huge system, which was why some ABC/M system implementations got into trouble. My major self-realization is that costing is accomplished by modeling cost consumption relationships – an insight that continues to evade many accountants.

When I began to see the application of strategy maps and the balanced scorecard, more light bulbs went off in my brain. I then began truly seeing the organization as a “system” where all the performance improvement methodologies and core processes are inter-connected. I realized that the technologies are no longer the impediment because they are proven. The obstacle is the organization’s thinking – and the mindset of senior management who is presumably doing the leading.

My advice to high school students take your studies more seriously than you even imagine, and spend less time text-messaging everyone you know and focus on the more meaningful relationships. They will eventually be your friends rather than just acquaintances. And take math courses!

Ajay- So what exactly do you do at SAS? And name some interesting anecdotes that led to a lot of value as well as fun for both your company and clients. How does Gary spend his daily day at SAS Institute?

COKINS: My primary role with SAS is to create and deliver thought leadership content about Performance Management leveraging business analytics. I present webinars and write articles, blogs, presentations and also books. For the last four years I have averaged visiting roughly 40 international cities where SAS offices are located to present seminars and meet SAS customers to educate them on the concepts and benefits from Performance Management methodologies.

Recent examples of having fun and providing value to organizations involved providing expert advice to the International Monetary Fund (IMF) in Washington DC and the European Patent Office (EPO) in Brussels. The IMF is at the beginning of implementing an activity based cost management (ABC/M) system whereas the EPO is completing their ABC/M system design. Both organizations were seeking tips for success and pitfalls to avoid. One of my major recommendations was to not under-estimate the natural resistance to change of managers and employees. That is, they need to focus much more on getting their buy-in than worrying if the system is perfect. The value to them is realizing that Performance Management methodologies are much more social than technical.

Regarding my daily activities, when I am not traveling, I am mainly reading articles written by other experts or journalists and then translating my relevant takeaways into content that I can educate others with. I also respond to questions and requests both internally within SAS and externally from customers, management consultants, and university faculty.

Ajay- When you were a young employee, what was the toughest challenge that you faced? What was your worst mistake and how did you overcome it? What lessons did you learn from it?

COKINS: In my first few years in business following my university graduation, my toughest challenge was persuading my supervisors, usually older men than I, to accept my new ideas. I have always been a creative thinker, almost a dreamer; and I was not accustomed to the resistance that managers have to innovations, particularly those suggested by young inexperienced employees fresh from their university schooling.

My worst mistake was developing a computer program that automatically suggested treasury cash balance transfers to optimize the corporate cash management system of my first employer, a large Fortune 100 corporation. My computer program was basically replacing the decisions made by the corporate cash manager and part of his job. I overcame this disappointment by learning what needs the corporate cash manager did have and developing a different computer program that solved his needs. With its success, he eventually accepted the first computer program.

My lesson was one should first understand what people may want rather than trying to impose on them what you think they need without involving them.

Ajay- Looking back on your distinguished career, what project are you proud of the most? What project would you do over again if given the chance?

COKINS: In 1973 I became a financial controller of a large division of another Fortune 100 manufacturer. I created a rolling financial planning and forecast software program, using pre-spreadsheet software from a mainframe (years before personal computers and Excel). The program modeled product line sales forecasts by month and integrated both the income statement and balance sheet. It became a valuable tool for the executive team to suggest and immediately see varying sales levels as a “what if” scenario builder to calculate the different profit and working capital results. The executive team marveled at how analytical software, in contrast to our transactional ERP-like system, could make sense of the complexity of our operations with thousands of products and customers.

Regarding a project that fell short of expectations, I actually did get a chance to do it over again. As a consultant with Deloitte, I lead a project designing and implementing an activity based cost management (ABC/M) system using the client’s general ledger accounting software. It took many months, and when finished it was too complex for the client to fully understand. Several years later with a similar project I applied a rapid prototyping with iterative re-modeling approach that involved the company’s managers from the first day. (I mentioned this approach in my reply to the first question.) We completed the ABC/M system in just a few weeks, and everyone understood it and also how to interpret the information for analysis and decisions. I have since been a proponent of this type of rapid learning and system design approach.

Ajay- What do people do for fun at SAS Institute do when not creating or selling algorithms? How is SAS reaching out to other members of the analytics community in terms of basic science and development?

COKINS: SAS employees are inspired by our CEO, Dr. Jim Goodnight, who founded SAS roughly 35 years ago. Dr. Goodnight loves solving problems of all flavors. For fun, but also part of our jobs, SAS employees search for problems that only computer software can solve.

SAS’ offerings evolve by listening to our customers, who are typically scientists, researchers, and business analysts. Drug development and marketing analysts are examples. Our customers are our “community.” We motivate them, with formal methods of collecting input from them, to share with us enhancements to our future versions of our software.

Ajay- Describe your new book on Performance Management from the point of a beginner. Assume that I am a college student who does not know why I should read it. Then assume that I am a CIO and have little time to read it. What is in it for a CIO?

COKINS: This is my sixth book I have written. My first four books were about activity based cost management (ABC/M) and the last two about Performance Management. What is different about this second book is it immediately clarifies the confusion and ambiguity about what Performance Management is and is not. It is also written in a humorous and simplified way with lots of analogies and metaphors, such as all of the Performance Management methodologies integrated together like gears in an automobile engine and with a GPS for predictive navigation and dashboards for feedback. Beginners perceive each methodology, such as a balanced scorecard or customer relationship management system, are stand-alone tools. There is synergy when they are integrated.

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CIOs have similar needs. They need to shift their mindset from a technical one to a managerial one. Just a few chapters from this book can help CIOs see the broad picture of how all of their organizations processes fit together, and how they can be aligned to efficiently execute the ever-adjusting strategy that the executives continuously formulate with operations.


Biography and Contact Information

Gary Cokins, CPIM

(gary.cokins@sas.com; phone 919 531 2012)

http://blogs.sas.com/cokins

Gary Cokins is a global product marketing manager involved with performance management solutions with SAS, a leading provider of performance management and business analytics software headquartered in Cary, North Carolina. Gary is an internationally recognized expert, speaker, and author in advanced cost management and performance improvement systems. Gary received a BS degree with honors in Industrial Engineering/Operations Research from Cornell University in 1971. He received his MBA from Northwestern University’s Kellogg School of Management in 1974.

Gary began his career as a strategic planner FMC’s Link-Belt Division and then served as Financial Controller and Operations Manager. In 1981 Gary began his management consulting career first with Deloitte Consulting. Next with KPMG Peat Marwick, Gary was trained on ABC by Harvard Business School Professors Robert S. Kaplan and Robin Cooper. More recently, Gary headed the National Cost Management Consulting Services for Electronic Data Systems (EDS)/ A.T. Kearney.

Gary was the lead author of the acclaimed An ABC Manager’s Primer (ISBN 0-86641-220-4) sponsored by the Institute of Management Accountants (IMA). Gary’s second book, Activity Based Cost Management: Making it Work (ISBN 0-7863-0740-4), was judged by the Harvard Business School Press as “read this book first.” A reviewer for Gary’s third book, Activity Based Cost Management: An Executive’s Guide (ISBN 0-471-44328-X) said, Gary has the gift to take the concept that many view as complex and reduce it to its simplest terms.” This book was ranked number one in sales volume of 151 similar books on BarnesandNoble.com. Gary has also written Activity Based Cost Management in Government (ISBN 1-056726-110-8). His latest books are Performance Management: Finding the Missing Pieces to Close the Intelligence Gap (ISBN 0-471-57690-5) and Performance Management: Integrating Strategy Execution, Methodologies, Risk, and Analytics (ISBN 978-0-470-44998-1).

Mr. Cokins participates and serves on committees including: CAM-I, the Supply Chain Council, the International Federation of Accountants (IFAC), and the Institute of Management Accountants. Mr. Cokins is a member of Journal of Cost Management Editorial Advisory Board. Cokins can be reached at gary.cokins@sas.com . His blog is at http//:blogs.sas.com/cokins

and his latest book can also be previewed at http://www.sas.com/apps/pubscat/bookdetails.jsp?catid=1&pc=62401

Decisionstats Interviews

Here is a list of interviews that I have published- these are specific to analytics and data mining and include only the most recent interviews. If I have missed out any notable recent interview related to analytics and data mining, kindly do let me know. Hat Tip to Karl Rexer, for this suggestion .

Date    Name of Interviewee    Designation and Organization

09-Jun    Karl Rexer                          President, Rexer Analytics
05-Jun    Jim Daves                          CMO, SAS Institute
04-Jun    Paul van Eikeren                 President and CEO, Blue Reference
29-May    David Smith                      Director of Community, REvolution Computing
17-May    Dominic Pouzin                 CEO, Data Applied
11-May    Bruno Delahaye                 VP, KXEN
04-May    Ron Ramos                        Director, Zementis
30-Apr    Oliver Jouve                       VP, SPSS Inc
21-Apr    Fabian Dill                         Co- Founder, Knime.com
18-Apr    Alicia Mcgreevey                 Head Marketing, Visual Numerics
27-Mar    Francoise Soulie Fogelman    VP, KXEN
17-Mar    Jon Peck                            Principal Software Engineer, SPSS Inc
06-Mar    Anne Milley                        Director of product marketing, SAS Institute
04-Mar    Anne Milley                        Director of product marketing, SAS Institute
03-Feb    Phil Rack                            Creator, Bridge to R,and CEO Minequest
03-Feb    Michael Zeller                     CEO, Zementis
31-Jan    Richard Schultz                   CEO, Revolution Computing
21-Jan    Bob Muenchen                    Author, R for SAS and SPSS Users
13-Jan    Dr Graham Williams           Creator, Rattle GUI for R
05-Jan    Roger Haddad                    CEO, KXEN
26-Sep    June Dershewitz                  VP, Semphonic
04-Sep    Vincent Granville                 Head, Analyticbridge

The URl’s to specific interviews are also in this sheet.

http://spreadsheets.google.com/pub?key=rWTqcMe9mqwHeFv1e4GS_yg&single=true&gid=0&range=a1%3Ae24&output=html

Interview Karl Rexer -Rexer Analytics

Here is an interview with Karl Rexer of Rexer Analytics. His annual survey is considered a benchmark in the data mining and analytics industry. Here Karl talks of his career, his annual survey and his views on the industry direction and trends.

Almost 20% of data miners report that their company/organizations have only minimal analytic capabilities – Karl Rexer

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Ajay- Describe your career in science. What advice would you give to young science graduates in this recession? What advice would you give to high school students choosing from science – non science careers?

Karl- My interests in science began as a child. My father has multiple science degrees, and I grew up listening to his descriptions of the cool things he was building, or the cool investigative tools he was using, in his lab. He worked in an industrial setting, so visiting was difficult. But when I could, I loved going in to see the high-temperature furnaces he was designing, the carbon-fiber production processes he was developing, and the electron microscope that allowed him to look at his samples. Both of my parents encouraged me to ask why, and to think critically about both scientific and social issues. It was also the time of the Apollo moon landings, and I was totally absorbed in watching and thinking about them. Together these things motivated me and shaped my world-view.

I have also had the good fortune to work across many diverse areas and with some truly outstanding people. In graduate school I focused on applied statistics and the use of scientific methods in the social sciences. As a grad student and young academic, I applied those skills to researching how our brains process language. But on the side, I pursued a passion for using the scientific method and analytics to address ….well anything I could. We called it “statistical consulting” then, but it often extended to research design and many other parts of the scientific process. Some early projects included assisting people with AIDS outcome studies, psycholinguistic research, and studies of adolescent adjustment.

My first taste of applying these skills outside of an academic environment was with my mentor Len Katz. The US Navy hired us to help assess the new recruits that were entering the submarine school. Early identification of sailors who would excel in this unusual and stressful environment was critical. Perhaps even more important was identifying sailors who would not perform well in that environment. Luckily, the Navy had years of academic and psychological testing on many sailors, and this data proved quite useful in predicting later job performance onboard the submarines. Even though we never got the promised submarine ride, I was hooked on applying measurement, scientific methods, and analytics in non-academic settings.

And that’s basically what I have continued to do – apply those skills and methods in diverse scientific and business settings. I worked for two banks and two consulting firms before founding Rexer Analytics in 2002. Last year we supported 30 clients. I’ve got great staff and they have great quant skills. Importantly, we also don’t hesitate to challenge each other, and we’re continually learning from each other and from each client engagement. We share a love of project diversity, and we seek it out in our engagements. We’ve forecasted sales for medical devices, measured B2B customer loyalty, identified manufacturing problems by analyzing product returns, predicted which customers will close their bank accounts, analyzed millions of tax returns, helped identify the dimensions of business team cohesion that result in better performance, found millions of dollars of B2B and B2C fraud, and helped many companies understand their customers better with segmentations, surveys, and analyses of sales and customer behavior.

The advice I would give to young science grads in this recession is to expand your view of where you can apply your scientific training. This applies to high school students considering science careers too. All science does not happen in universities, labs and other traditional science locations. Think about applying scientific methods everywhere! Sometimes our projects at Rexer Analytics seem far away from what most people would consider “science.” But we’re always asking “what data is available that can be brought to bear on the business issue we’re addressing.” Sometimes the best solution is to go out and collect more data – so we frequently help our clients improve their measurement processes or design surveys to collect the necessary data. I think there are enormous opportunities for science grads to apply their scientific training in the business world. The opportunities are not limited to physics wiz-kids making models for Wall Street trading or computer science students moving to Silicon Valley. One of the best analytic teams I ever worked on was at Fleet Bank in the late 90s. We had an economist, two physicists, a sociologist, a psychologist, an operations research guy, and person with a degree in marketing science. We were all very focused on data, measurement, and analytic methods.

I recommend that all science grads read Tom Davenport’s book Competing on Analytics *. It illustrates, with compelling examples, how businesses can benefit from using science and analytics. Several examples in Tom’s book come from Gary Loveman, CEO of Harrah’s Entertainment. I think that Gary also serves as a great example of how scientific methods can be applied in every industry. Gary has a PhD in economics from MIT, he’s worked at the Federal Reserve Bank, he’s been a professor at Harvard, but more recently he runs the world’s largest casino and gaming company. And he’s famously said many times that there are three ways to get fired at Harrah’s: steal, harass women, or not use a control group. Business leaders across all industries are increasingly wanting data, analytics and scientific decision-making. Science grads have great training that enables them to take on these roles and to demonstrate the success of these methods.

Ajay- One more survey- How does the Rexer survey differentiate itself from other surveys out there?

Karl- The Annual Rexer Analytics Data Miner Survey is the only broad-reaching research that investigates the analytic behaviors, views and preferences of data mining professionals. Each year our sample grows — in 2009 we had over 700 people around the globe complete our survey. Our participants include large numbers of both academic and business people.

Another way our survey is differentiated from other surveys is that each year we ask our participants to provide suggestions on ways to improve the survey. Incorporating participants’ suggestions improves our survey. For example, in 2008 several people suggested adding questions about model deployment and off-shoring. We asked about both of these topics in the 2009 survey.

Ajay -Could you please share some sneak previews of the survey results? What impact is the recession likely to have on IT spending?

Karl- We’re just starting to analyze the 2009 survey data. But, yes, here’s a peek at some of the findings that relate to the impact of the recession:

* Many data miners report that funding for data mining projects can sometimes be a problem.
* However, when asked what will happen in 2009 if the economic downturn continues, many data miners still anticipate that their company/organization will conduct more data mining projects in 2009 than in previous years (41% anticipate more projects in 2009; 27% anticipate fewer projects).
* The vast majority of companies conduct their data mining internally, and very few are sending data mining off-shore.

I don’t have a crystal ball that tells me about the trends in overall corporate spending on IT, Business Intelligence, or Data Mining. It’s my personal experience that many budgets are tight this year, but that key projects are still getting funded. And it is my strong opinion that in the coming years many companies will increase their focus on analytics, and I think that increasingly analytics will be a source of competitive advantage for these companies.

There are other people and other surveys that provide better insight into the trends in IT spending. For example, Gartner’s recent survey of over 1,500 CIOs (http://www.gartner.com/it/page.jsp?id=855612 ) suggests that 2009 IT spending is likely to be flat. I’m personally happy to see that in the Gartner survey, Business Intelligence is again CIOs’ top technology priority, and that “increasing the use of information/analytics” is the #5 business priority.

Ajay- I noticed you advise SPSS among others. Describe what an advisory role is for an analytics company and how can small open source companies get renowned advisors?

Karl- We have advised Oracle, SPSS, Hewlett-Packard and several smaller companies. We find that advisory roles vary greatly. The biggest source of variation is what the company wants advice about. Example include:

* assessing opportunity areas for the application of analytics
* strategic data assessments
* analytic strategy
* product strategy
* reviewing software

Both large and small companies that look to apply analytics to their businesses can benefit from analytic advisors. So can open source companies that sell analytic software. Companies can find analytic advisors in several ways. One way is to look around for analytic experts whose advice you trust, and hire them. Networking in your own industry and in the analytic communities can identify potential advisors. Don’t forget to look in both academia and the business world. Many skilled people cross back and forth between these two worlds. Another way for these companies to obtain analytic advice is to look in their business networks and user communities for analytic specialists who share some of the goals of the company – they will be motivated for your company to succeed. Especially if focused topic areas or time-constrained tasks can be identified, outside experts may be willing to donate their time, and they may be flattered that you asked.

Ajay- What made you decide to begin the Rexer Surveys? Describe some results of last year’s surveys and any trends from the last three years that you have seen.

Karl- I’ve been involved on the organizing committees of several data mining workshops and conferences. At these conferences I talk with a lot of data miners and companies involved in data mining. I found that many people were interested in hearing about what other data miners were doing: what algorithms, what types of data, what challenges were being faced, what they liked and disliked about their data mining tools, etc. Since we conduct online surveys for several of our clients, and my network of data miners is pretty large, I realized that we could easily do a survey of data miners, and share the results with the data mining community. In the first year, 314 data miners participated, and it’s just grown from there. In 2009 over 700 people completed the survey. The interest we’ve seen in our research summaries has also been astounding – we’ve had thousands of requests. Overall, this just confirms what we originally thought: people are hungry for information about data mining.

Here is a preview of findings from the initial analyses of the 2009 survey data:

* Each year we’ve seen that the most commonly used algorithms are decision trees, regression, and cluster analysis.
* Consistently, some of the top challenges data miners report are dirty data and explaining data mining to others. Previously, data access issues were also reported as a big challenge, but in 2009 fewer data miners reported facing this challenge.
* The most prevalent concerns with how data mining is being utilized are: insufficient training of some data miners, and resistance to using data mining in contexts where it would be beneficial.
* Data mining is playing an important role in organizations. Half of data miners indicate their results are helping to drive strategic decisions and operational processes.
* But there’s room for data mining to grow – almost 20% of data miners report that their company/organizations have only minimal analytic capabilities.

Bio-

Karl Rexer, PhD is President of Rexer Analytics, a small Boston-based consulting firm. Rexer Analytics provides analytic and CRM consulting to help clients use their data to make better strategic and tactical decisions. Recent projects include fraud detection, sales forecasting, customer segmentation, loyalty analyses, predictive modeling for cross-sell and attrition, and survey research. Rexer Analytics also conducts an annual survey of data miners and freely distributes research summaries to the data mining community. Karl has been on the organizing committees of several international data mining conferences, including 3 KDD conferences, and BIWA-2008. Karl is on the SPSS Customer Advisory Board and on the Board of Directors of the Oracle Business Intelligence, Warehousing, & Analytics (BIWA) Special Interest Group. Karl and other Rexer Analytics staff are frequent invited speakers at MBA data mining classes and conferences.

To know more do check out the website on www.rexeranalytics.com

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