IBM today announced the newest version of IBM SPSS Statistics software,its integrated family of products that addresses the entire analytical process, from planning to data collection to analysis, reporting and deployment.
The new enhancements in IBM SPSS Statistics v21ensure that the most advanced analytics techniques are available to a broader group of business users, statisticians, analysts and researchers.Making it easier to access and manage big data, set up and perform analyses, and share results across the organization, IBM SPSS Statistics now includes:
�Simulation Modeling� Using Monte Carlo simulation techniques, users can now build better models and assess risk when inputs are uncertain.
�Advanced Techniques for Big Data�Quickly understand large and complex datasets using advanced statistical procedures to provide high accuracy and drive quality decision making.
�Improved Integration�Deploy analytics faster with seamlessaccess to common data types and external programming languages, including Java and IBM Cognos business intelligence.
Monte Carlo Simulation
The new simulation modeling feature is designed to account for uncertainty in data inputs, such as determining how weather conditions affect energy consumption, how costs of materials (e.g., steel prices) affect profitability of a construction project, or to better understand risks around investment planning.
By using Monte Carlo simulation, theunknown inputs and historical distributions are used to create confidence intervalsand visualizations(see graphic) to help make the best decision.
For example, energy and utilities organizations run simulations on potential weather temperatures, compared against historical weather temperatures, to then determine how much energy it would likely need to generate for an 85 degree day on August 31. This process can be repeated many times (typically thousands or tens of thousands of times), resulting in a distribution of outcomes so users can make the best decision.
Unlike other software packages, IBM SPSS Statistics doesn�tforce users to start from scratch, but allows them to leverage existing predictive models and existing data as the starting points for simulation.
IBM SPSS Statistics now makes working with big data easier, more scalable and ensures optimal performance when working with multiple predictors. By introducing a data file comparison tool, users now have the ability to compare datasets or data files to identify any discrepancies and ensure that the data values and records are compatible.
Users can now compare files for better quality control. For example, users can now find discrepancies between data sets that contain responses by the same respondents to a survey, but entered by two different people.
Also, IBM SPSS Statistics now allows operations like sorts and aggregations to be pushed back to the database, where they can be performed faster. Temporary files created by analytical procedures can be distributed across multiple disks, and large files can be compressed to save disk space when sorting, improving performance and speeding up analysis.
For example, users can run multiple analytical jobs at the same time while continuing to work on their desktops at other tasks. Users can also continue to run server jobs while disconnected from the server without sacrificing the quality of their analysis or output, then reconnect to access their completed jobs.
With IBM SPSS Statistics, users can now use a Java� plug-in to call IBM SPSS Statistics functionality from a Java application and have IBM SPSS Statistics output appear in the Java application.
Finally, IBM SPSS Statistics now provides the ability to easily import IBM Cognos business intelligence data for analysis. Users can now read custom data with or without filters, and import predefined reports from IBM Cognos directly into IBM SPSS Statistics.
Guest post from Kathy Konkel, Product Marketing and GTM Strategy, IBM Business Analytics
At one of the recent IBM Performance events, Paul DePodesta, vice president of player development with the New York Mets, talked about his experiences working with the Oakland A�s Billy Beane to create winning teams and completely change the business of professional baseball.
One of the techniques they used to test the way they were approaching the business was to relentlessly ask �the naive question.� This is a concept he credited to Peter Drucker and, in everything they did, they would ask, �If we weren't already doing it this way, is it the way we would start?�
This is not always easy to do and this question is not always met with open minds, but it can be very effective when a new kind of thinking is needed in order to survive.
I thought about this in terms of some of the challenges our customers face when it comes to deployingbusiness analyticswithin their organization � from operational process to infrastructure to culture.
Most organizations today are still not at the point where they are able to take advantage of analytics. (Those interested can measure your organization�s analytics maturity by taking theAnalytics Quotient (AQ) assessment.)
Part of this reason is that IT organizations are spending 70 percent of their resources just keeping the lights on. That�s a lot of overhead and doesn�t leave much room for innovation.
So let�s ask the naive question, �If you were starting over with your IT infrastructure � would you build it the same way?� Maybe the answers are in the cloud.
When Chet Karwatowski was building the infrastructure forSupplier Connection, a web-based portal that makes it easier for small businesses to become recognized as potential suppliers to large companies, he knew business analytics was going to play an important role in his application, but he knew he didn�t have the skills or resources to set up the infrastructure he needed. He turned toIBM cloud computingsolutions to help him deliver his solution with fewer resources and on a very aggressive schedule.
Organizations like Chet�s are using the power of cloud to build enduring customer relationships, deliver IT without boundaries, improve speed and dexterity and transform the economics of innovation.
Putting the two together, cloud-based analytics could be a way to help organizations advance in their analytics sophistication � and quickly.
Part of this forum included a panel discussion with customers who had implemented analytics solutions using a cloud-based infrastructure.
The main message from all of the panel participants was the benefit of lower costs and allowing them to focus on adding value to the business instead of managing a complex IT infrastructure gave them a competitive advantage.
In addition to Chet, Kevin Hurd fromAssimil8, an IBM Business Partner, talked about the efficiencies they were able to achieve when they implemented a solution for Energy Saving Trust (EST) in the UK. Read the recent press release.
EST launched a new �Home Analytics� service based onIBM Cognosand IBM SmartCloud Enterprisethat is the primary tool in its efforts to help energy suppliers, green deal providers and local government reduce domestic CO2 emissions across the UK.
They were able to deliver a solution in just a few weeks that would have taken months if they would have had to build up the infrastructure themselves, while still satisfying its own stringent criteria for energy efficient solutions.
Like Paul Depodesta, the Supplier Network and EST, staying on top of the game means always asking the naive question � even when it�s not obvious that a change is needed.
Have you considered a cloud based infrastructure for your next set ofbusiness analyticssolutions?
And, we asked you to dream the impossible dream of a world where a single vendor might deliver a family of products, including reporting, analysis, modeling, planning and collaboration, which would also balance analytic freedom with governance and control.
This dreamland is no fairytale, and we are happy to report it does have a very happy ending.
�Individuals, who need the freedom and flexibility of personal analytics, yet want to access corporate information and easily share insights across a wider community with IBM Cognos Insight
�Workgroups and mid-sized organizations, that need to be up and running with a solution that is easy to install and manage with IBM Cognos Express
�Enterprises,that require broad analytic capabilities deployed to hundreds or thousands of userswithIBM Cognos Enterprise� an offering that brings together the integrated capabilities of IBM Cognos business intelligence and IBM Cognos TM1 performance management.
With the IBM Cognos family of Business Analytics solutions, IBM addresses the breadth of analytics with any single product in the family spanning reporting, analysis, modeling, planning and collaboration.
And, the solutions ensure that any organization can begin its journey today depending on the specific requirements, as well as providing the confidence to expand the solution � without retraining, retooling or re-implementing.
Please watch the short video below that describes how we might �prescribe� the family of solutions directly to a business.
For example, if an individual user wantsto work independently and quickly without waiting for corporate systems, and thenshare those insights or create additional reports from larger data sets, an organization can easily add server capabilities to combine insights with real-time and corporate information. Those same insights can then be shared on scorecards and dashboards and sent directly tomobile devices.
As Sister Sledge once sang, �We are family! I got all my [analytics]and me!�
We invite you to join and interact with our growing family.
We�d also love to hear how you are usingIBM�s business analytics solutions toaddress your specific business needs � fromquickly gaining insight into the business to taking action and driving results. Please tell us your story in the comments section.
I'm a sucker for anything related to analytics and sports. I�m also not alone.
Ever since the Moneyball craze, the general populous is keenly aware of the benefits and value analytics brings to the world of baseball. It�s hard not to imagine baseball without thinking about Michael Lewis, Brad Pitt, the Oakland A�s and analytics. Heck, even ESPN the Magazine this week created an entire issue dedicated to "Analytics."
I attended a Chicago Cubs and Bloomberg Sports event on Tuesday night here in Chicago where Shiraz Rehman, the new Assistant General Manager of the Chicago Cubs, discussed the team�s use of analytical tools to evaluate players for drafts and free agent signings, do advance scouting, and game planning.
I've never seen a room (of mostly men) so intently hanging on every word. Analytics is so much a part of baseball's lexicon that box scores have become an antiquated way of understanding a baseball game. The cravings have shifted from home runs and batting average to more sophisticated statistical measurements, such as UZR, WAR, VORP, OPS-plus, FIP and BAPIP.
Some of the interesting revelations from the event included:
�Mobile BIis running rampant in the clubhouse. Players love their iPads for consuming reports and evaluating video of themselves and the competition.
�Old school scouts and new school analytical thinking co-exist peacefully in the front office and rely on each other's insight to make smarter decisions.
�Even with all the analytical tools, baseball teams still miss "all the time" on prospects, especially for 18-21 year olds, where it's still difficult to predict behaviors.
�Teams might be equipped with the best analytical tools and data, but if they don't have the people with the right skill sets and creativity, they will fail.
If you want more insight into how a baseball team is using business analytics, register for an upcoming IBM Performance or IBM Finance Forumevent to hear Paul DePodesta, VP of Player Development & Amateur Scouting for the New York Mets. He'll be speaking at various cities throughout the United States and Canada (San Francisco; Dallas; Morristown, NJ; Huntington Beach, CA; Montreal; Charlotte).
While baseball might be the analytical poster child, all sports are wildly interested in using this technology for competitive advantage on the field/hardwood/ice, and to run their business operations. In fact, the Mecca for those in this profession is the annualMIT Sloan Sports Analytics Conferencetaking place this weekend in Boston.
Based on IBM's experience, below are a few other ways business analytics is transforming the sports world:
�Improving the customer experience.The Miami Dolphins are integrating IBM analytics technology into Sun Life Stadium, enhancing the overall experience for fans of sports, music and media. As a result, officials can gain immediate insight into all stadium operations including visitor traffic, fan spending preferences and weather patterns, as well as social media sentiment.Readthe press release and watch the video below.
�Guiding draft selections.By assessing future player performance and then leveraging the insights from the analytics to create business rules, teams can decide who to select based on positional needs, previous draft selections, and other factors.
�Maximizing schedules and ticket pricing.Analytics helpsteams optimally balance revenue generation and travel efficiencies, as well as optimizing ticket prices based on days of the week and opponents.
�Optimizing performance.Hockey teams are using analytics to evaluate how players perform in specific situations, such as at the end of a close game or during a power play. This analysis helps coaches determine which players should be on the ice at certain times of the game.
�Simulating winners.Seen the IBM SlamTracker?It�s alive scoring and analysis tool that applies IBM business analytics to give fans a virtual seat at the tournament. It allows millions of worldwide fans to track players' progress and see the Keys to the Match that shows the particular strategy players should take to improve their chances of winning.
As you can see, analytics is finding its way into games in many ways. For more information, visit the IBM Smarter Analytics website.
But, let�s not forget that�s it�s soon to be baseball season and hope, like analytics, springs eternal for all teams.
And now that the Chicago Cubs have Theo Epstein, Shiraz Rehman and their band of analytical savants�all I can say is �watch out!�
A hundred plus years of misery are only an algorithm away�or so I hope.
Guest post from Becky Smith, Product Marketing, IBM Business Analytics
In a way, doesn't everyone in business analytics have a little bit of Don Quixote in them?
We're all on a bit of quest to find answers hidden in our never-ending, growing piles of data. And often, we find ourselves tilting at windmills and fighting futile battles with IT, with spreadsheets or with silo'd applications that only do one specific task.
Close your eyes for a minute and let yourself dream about a world where there is a single vendor that delivers a family of products including reporting, analysis, modeling, planning and collaboration.
What if that family of products not only has a common set of capabilities but is also integrated and talks to other members of the family so they all live happily together? And, what if a mid-sized business could get the same self-service experience, what-if scenario modeling and the ability to discover and assemble their data across both business intelligence and performance management as a large enterprise?
This is a notion we call "right sized analytics." An enterprise solution might be too big and expensive for your organization, while an individual point solution might be too small and limiting and unable to provide the needed integration with a mid-sized or larger enterprise solution.
Right sized analytics means having an entire family of products built on a common foundation that enables individuals, workgroups and enterprises to access and analyze corporate information and easily share insights across the organization. Basically, it doesn't matter where you begin your analytic journey, as long as you have the comfort knowing that the solution will grow with you.
For example, an organization might have an issue with customer retention. Through the analysis of support calls, an individual user might uncover that there is a 15 percent increase in dissatisfied customers due a product defect. This information can then be shared back into the analytics solution so the manufacturing and support organizations can improve product quality, and plan to offer customers special promotions and increase customer service for the entire customer base, respectively.
Does this scenario only exist in your subconscious?
That one man, scorned and covered with scars,
Still strove, with his last ounce of courage,
To reach ... the unreachable star ...
In feedback from our customers, they've talked about the battles scars they've received in their quest for a common set of systems working seamlessly together. Stay tuned for part 2 of this post and hear why that business analytics star is no longer unreachable and how a complete family of products can:
� Address the needs for your organization � regardless of size
� Empower individual users, workgroups and enterprises
� Allow the organization to start anywhere and go everywhere
One of the first things I ask people on the subject of data is �What do you want it to look like?�
I don't mean for the question to be complex, but I generally get an odd look and response in return. �What do you mean how do I want it to look? It�s data, it has to be accurate and structured.�
So why is it when we talk about data we picture streams of numbers, columns and rows of calculations filtering through servers or built out over multiple spreadsheets? Not all business users have the time or skills to interpret large enterprise or spreadsheet data sets.
Why is it we can't be asked the question, �What do you want it to look like?� and answer with a personal perspective? I tend to believe it's because we don't think of data as having a personality. In fact, data has quite a bit of personality.
While often quite shy and reclusive, data will talk your ear off with just a little nudge. It can also be kind of a gossip revealing interesting insight into customer behavior or an organization�s financial information. And it�s those individual users running the data analysis who can easily unleash that personality� for the good of the organization.
That�s why organizations are realizing the value and achievements that come about as a result of having a complete analytic solution built not only for the enterprise, but also for the individual user in mind.
The notion of personal analytics is about bringing agile analysis capabilities to people in an easy-to-use manner without having to rely on IT. Business users can now take advantage of solutions that bring exceptional capabilities to their desktop in terms of personalizing how they display local or enterprise data and how they solve individual or workgroup challenges � all on their terms.
Analytics is definitely becoming a more personal experience. Being able to explore data and format it in a presentation layer of the user�s choice, add built-in calculations, apply scenario modeling and do write-back on the fly, or creating traffic lights that represent key metrics that are important to the individual are all a means to answering my question, "How do you want it to look?"
Take the distribution industry, for example. What if you had the freedom to model out different scenarios based on the price of diesel fuel? An individual user can now identify the key drivers of the business, like fuel cost, then test different assumptions and identify best case, worst case and probable outcomes.
One can only imagine how this could affect you personally, with regard to your line of business in a distribution center. But what if it also affected the manufacturing floor in terms of energy prices for production costs? Would the same scenario be important to other areas of the enterprise?
In a way, building the right analytics competency is like building a business from the ground up. You need to create a growth path that combines personal analytics with enterprise scope and IT values. By providing the necessary foundation of analytics along with limited barriers of usage, you can turn your business users out to the world to explore, discover and grow as analytics professionals with a personalized capability that brings meaning and life to the data.
Knowing that these business users can turn data exploration into action by aligning their discoveries with the enterprise challenges the silos of information that personal analytics has typically produced.
Business users have traditionally created and held onto spreadsheets or data files that only they maintain and which are not reflected across workgroups for greater use. Today's organizations demand a bridge between what line of business users want and what IT requires to run a smooth enterprise environment.
Personal analytics creates that bridge.
So the next time someone asks you, "What do you want your data to look like?" tell them you want it to look interesting and attractive, prescriptive and distinctive, honest and meaningful, and actionable.
But above all else, tell them you want it to have personality!
Have you ever had that awkward conversation with a significant other where they tell you they just want to be friends?
Sometimes the news is hard to swallow. It forces you to ask yourself, �What could I have done better?�
This same tough conversation needs to happen with certain software applications too. People just stay in relationships with software for too long. That said, it�s time to have the �friend talk� and break up with spreadsheets.
You�ve never really loved them. It�s been a relationship of convenience � they just showed up one day on your laptop and the rest was history. Yes, they�re nice and have a good personality (as much as software can), but it�s time to cut the cord and just be friends.
Disclaimer:I am not attempting to disparage or declare war on spreadsheets. They serve a useful purpose and will always be a staple inside organizations, but they are not the analytic application you want to bring home and introduce to your parents.
Spreadsheets have been widely used for financial and cost accounting, data collection and analysis, and mathematics. But, when they are called upon to perform a task for which they are not designed or beyond the limit of their capabilities, spreadsheets can actually be a fatal attraction.
Mark Smith, CEO and Chief Research Officer at Ventana Research says that spreadsheets �can be one of the most expensive pieces of technology because of the risk and wrong decisions that are made due to their numerous errors.�
In fact, a number of studies have indicated that 90 percent or more of spreadsheets contained errors.
And Bruce McCullough, the software editor for the International Journal of Forecastingwrote that �Professional statisticians continue to write books with titles like �Statistics with Excel,� but they now warn students not to bet their jobs on Excel�s accuracy. They advise students to use a real statistical package when they need to do statistics.�
So, I guess you have to ask yourself, do you want a meaningful relationship with your data, such as being able to perform detailed analysis, find hidden patterns or make reliable forecasts, instead of a dangerous liaison that gives you little in return, besides frustration?
Speaking of meaningful relationships:
�Elie Tahari, a global fashion brand, found that its retail controllers were struggling with monthly budget reports because its 22 locations submitted spreadsheets separately. By turning this task over to a more robust business analytics solution, they were able to create a seamless reporting framework that provides granular, real-time information from the sales floor to its suppliers� inventory and production schedules. They reduced their reporting cycle from as many as two days to a few minutes, and saw a 30 percent reduction in supply chain and logistics costs. (Read the case study.)
�Checkers Drive-In Restaurants Inc., the largest chain of double drive-thru restaurants in the United States, relied on spreadsheets for financial planning processes that were taking up to three months each year. By breaking away from this burden, they are now able to get the same jobs completed in three weeks, do better forecasting and more quickly respond to changing economic conditions. (Read the case study.)
It�s been said that once you break up with someone, remaining friends is almost impossible. Things just get weird.
Not true with spreadsheets. They�ll still be hanging out on the laptop, going to the same meetings and most importantly, will play a prominent role in sharing the results of the analysis across the organization (if you so choose).
But they will be frustrated by their shortcomings and say, �I wish I could�ve done better.�
For more information:
� Registerfor the upcoming webinar: �The Risks of Using Spreadsheets for Statistical Analysis.� (February 15 at 12:00 pm ET)
� Readthe whitepaper: �The Risks of Using Spreadsheets�
� Attendour upcoming IBM Innovations in Business Analytics Virtual Launch (March 7, 2012) to see new solutions that will give you a more personal relationship with your data.
It has almost become a daily occurrence when I arrive home from work and go through the mail to find yet another credit card offer from my bank, even though I already have a credit card with that very same bank.
Shouldn't they already know I have one of their credit cards? Do they even know me? Or, care to?
That�s the problem.
And according to Mark Smith, CEO and Chief Research Officer, atVentana Research, it�s imperative that banks and insurance providers anticipate and align their business around the customer.
�This is whybusiness analyticshas become a required must-have,� said Smith. �Business analytics is a significant set of technologies that is going through a huge transformation. It now plays a key role in everyday business processes, drives improvement and helps meet customer expectations and satisfaction.�
This is especially true for today�s customers who are savvier and price sensitive, and far less loyal. Customer experience now goes a long way.
Whether its banks or insurance providers (or any industry), business analytics is forcing disparate parts of those businesses to speak to each other, share data and create a personal experience for the customer.
However, according to research from Ventana, the problem is that only 1 in 5 banks and insurance companies are using business analytics at an innovative level of performance.
Smith said that these firms either have great people with skills, but struggle with technology, or have the technology but aren�t using it to drive improvements.
�Firms need a balanced approached across these elements in order to improve their analytics maturity,� said Smith.
What is holding these organizations back from taking the next step?
According to Ventana�s banking and insurance benchmarks, only 42 percent of banks and 37 percent of insurance providers are satisfied with their current analytic process.
Smith points to three main barriers that halt analytic success:
� Wasted time due to data related activities (preparation, fixing errors)
� Lack of intersection between the business and IT (read a recent blog post on this rivalry)
� Continued use of spreadsheets that increase risk factors and contribute to poor decisions
What can banks and insurance providers do to generate better value from their analytics?
According to Smith, 68 percent of companies surveyed said the most popular use of business analytics today is in customer service. What is most interesting, however, are the least popular uses which include customer profitability, voice of the customer, marketing campaigns, communications channel usage and social media (at a lowly 4 percent).
These are the areas where the use of customer analytics can have exponential effects, and according to Smith, become a true measure of innovative maturity.
This is when the analytic process gets deeply integrated into every business process and customer touch point to make every interaction personalized.
IBM recently conducted tests in its labs that revealedIBM Cognos BI v 10.1.1 to be at least on par and better by 14 to 46 percent when compared to Microsoft Windows 2008 Server.
IBM Cognos BI application performance between similarly configured IBM POWER6 and IBM POWER7 systems showed significant performance advantages for IBM POWER7 servers.
IBM conducted a variety of tests to match the different ways of using IBM Cognos Business Intelligence services and system resources. The test systems used similar server configurations and current processor generation. Download the free report here.
Other findings included:
�Performance improvements of as much as 41 percent for workloads such as running HTML and PDF-based reports and portal navigation
�Performance improvements of as much as 26 percent for workloads such as running large and highly formatted PDF reports, locally processed calculations, interactive analysis activities and complex queries mixed with lighter workloads
For example, an IBM customer had developed a Cognos Business Intelligence application to distribute PDF based reports by email; as implemented and before optimization this application was performing at a rate of 11 multi-page reports per minute.
After the customer applied recommended AIX tuning parameters, the application performance improved to 150 multi-page PDF reports per minute.
On average, most applications might see performance improve two or three fold by applying AIX level tuning.
To provide a comprehensive view of the potential performance impact of optimizations made in Cognos Business Intelligence v 10.1.1, IBM used a broad range of tests. See the graphic that lists the performance improvements for the 20 different tests used.
For more information:
�Downloadthe whitepaper, �Best Practices and Advantages of IBM Power Systems for Running IBM Cognos Business Intelligence,� to see the full performance results.
NOTE:Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors.
Some people might argue, but former rapper and musician Vanilla Ice was a visionary.
Truth be told, he probably wasn�t talking about business analytics when he eloquently penned those famous lyrics in �Ice, Ice Baby.� But, he could have been.
We live in a collaborative world today�whether we like it or not. The realm of �social� is slowly morphing personal and professional, ultimately making life more efficient and transparent.
And some people and organizations are still rejecting this notion altogether.
Which is why at a company of approximately 400,000, with team members spread across the world, collaboration is a way of life, and a necessity in the IBM survival kit.
It bridges the gap of the world of social with the world of business. It allows us to now connect people and insights to gain alignment inside of the organization, as well as hold people accountable.
Decision making is no longer a game of telephone where important elements of that decision are lossed as it is passed on�one person at a time. When the decision is finally executed, does anyone even know if it was right, if the right people were involved, who made the decision, or why?
That�s where the power of business analytics and collaboration come together.
Organizations can lose tremendous productivity as they search for invaluable information hidden in various meeting notes, manual processes, emails and people�s notebooks.
Collaborative business intelligence(BI) streamlines and improves decision-making by providing capabilities for forming communities, capturing annotations and opinions, and sharing insights with others around the information itself.
It also allows organizations to communicate and coordinate tasks to engage the right people at the right time.
In fact, industry analyst Dave Menninger from Ventana Research commented that �innovative organizations recognize the processes involved in BI are as important as the technology and take steps to provide collaborative support to their BI activities.�
With built-in collaboration and social networking, collaborative BI harnesses the collective intelligence of the organization to connect people and insights and gain alignment.
What was once a dysfunctional buffet style decision making process is now a formal dining experience, with collaborative BI as the lazy susan passing reports and dashboards around the table for feedback and discussion.
Everyone now has input into the process, can easily connect with and understand context with others who are relevant to the decisions being made,and can now learn from history with a centralized corporate memory.
But realistically, before we can all sit down and enjoy this collaborative feast, it must be an accepted practice in the organization.
Culture is at the heart of this. It has to want to happen. Collaboration cannot be forced.
And, once you have embraced it�well, there�s no turning back.
Before too long, you have access to the people and expertise you need to discuss and refine ideas, data and information for the best results.
Had Vanilla Ice lived in today�s world of social networks and business analytics, he might have been able to lengthen his career, better market himself, sell more records, write better songs, connect with fans and shave less eyebrows.
Ok, maybe not.
But, he would have lived true to his mantra of collaborating with his producers and writers and listening to the general collective before making any decisions.
(I apologize if you now have Vanilla Ice stuck in your head for the rest of the day, but at least you�ll be thinking about how you can establish collaborative BI processes across the organization.)
Learn more about IBM Cognos Collaboration by:
� Registering for the January 17 IBM TechTalk: �Enabling Better Decision Making Through Highly Collaborative BI� (Begins at 12:00 pm ET)
� Watching the demo to see how to use built-in collaboration and social networking tools to connect people and insights