Twenty-four sessions, twenty-four speakers, twenty-four different topics over just two days, and I didn’t just sit through the convention as a participant, no, I moderated the entire two day event as its Chairman. The Financial Forecasting and Planning Summit, organized by the IE Group, and held at the DoubleTree Mission Valley in San Diego, February 25-26. Whew! That was a lot of work.

As Chair, you literally do not get a break. While the participants are grabbing a coffee and a snack, you, as moderator, are busy tracking down the next set of speakers, many of whom only showed up during the middle of the prior session, learning how to mispronounce their names, finding out that they’ve changed their presentation topic since the agenda went to press, scrapping the introduction you spent twenty minutes working on the prior evening and quickly rewriting a new intro based on that new topic, and otherwise dealing with the various changes and announcements that the organizers are throwing at you, some unavoidable (ill speakers) and some evidently just to make you jump (Agenda? Isn’t that a synonym for “rough guideline”?)

Twenty-four speakers over just two days, thirty minutes each, and not a minute extra. Give into one and you lose control of the entire meeting, so out of necessity you become the Timekeeper from Hell. By lunch time of Day 1 I had all the speakers completely paranoid; exactly where I wanted them.
Continue reading "Unique business models, but common problems"

“It has just snowballed.’’

That’s how Greg Smith, Assistant Professor of Management Information Systems at Xavier University in Cincinnati, describes the business intelligence concentration his university started for Master of Business Administration students. In an 18-month time frame, the concentration grew from zero to 100 students – a full 10 percent of the school’s 1,000 part-time MBA students. The concentration includes a course in data mining and predictive modeling using SAS. The program has been so successful that the university is planning to offer an undergraduate degree in business analytics soon.

Smith credits the interest to a job market that wants employees with strong analytic skills. Research-driven companies like Kroger, dunnhumby, and Procter & Gamble make their home in Cincinnati. But Xavier’s BI concentration also draws in engineers, nurses and others who see the analytics component as critical to their education. While the university has sent out a press release about its offerings and has marketed the classes internally, it has primarily grown the program without mentions in paid advertisements.

According to Smith, it’s important to enhance analytics education for students who aren’t seeking math-dominant degrees. “There is a competing university in town that offers a master’s and PhD in the quantitative areas, but no one was doing this associated with an MBA,’’ Smith explains. While higher-level math classes are critical to creating forecasts, predictive modeling and mining can, and should, be done by students possessing more of a liberal arts background, Smith says.
Continue reading "Business analytics drives Xavier University’s MBA concentration, new undergraduate major"

I meant to blog about Harvard Business Review's Decade in Management Ideas back in January when it was first published. I bookmarked the article and jotted down a few notes in an email. And then I forgot all about it.

This week, Anna Brown, SAS Business Report Editor, mentioned HBR's best management ideas in her latest newsletter, which reminded me to re-read it and point you towards recent articles from or about SAS for each of the twelve topics.

1. Shareholder Value as a Strategy. HBR quotes Jack Welch: "Shareholder value is a result, not a strategy. Your main constituencies are your employees, your customers and your products." And I'll quote Jim Davis: "Positioning a product in the tech marketplace isn’t just about the product - you need relationships. This is where our strong employee base comes into play. Make no mistake: people want to do business with companies that treat people well."

2. IT as a Utility. HBR talks about cloud computing. In the latest issue of sascom we called it, Analytics: Hot, Fresh and On Demand.

3. The Customer Chorus. Dave Carroll's "United Breaks Guitars" video is mentioned in the HBR post. Earlier this week, Jonathan Hornby wrote about having lunch with Dave Carroll.
Continue reading "Aligning with Harvard's 12 best management ideas"

Using analytics to properly interpret the ocean of information that exists within organizations is the key to avoid drowning in the data tsunami.

“That’s the message SAS Senior Vice President and Chief Technology Officer Keith Collins delivered in a recent address to a group of computer science students at North Carolina State University.

Keith’s talk, titled “How do you respond to a data tsunami?,” kicked off the 2010 Fidelity Investments “Leadership in Technology” Executive Speaker Series sponsored by the university’s Department of Computer Science.

“We talk tons about how you get information in,” Keith said. “But we’ve done very little to describe and understand processes of getting information out.”

Applying analytics in the business world

Continue reading "How do you respond to a data tsunami?"

Attending the Predictive Analytics World (PAW) Conference is truly a rewarding experience. Compliments go to Eric Siegel and the conference organizers for assembling such an interesting cast of case studies and speakers.

Day 2 kicked off with a key note from Kim Larsen from Charles Schwab & Co. on net lift (or uplift or incremental) modeling using SAS. The latter topic is a perennial favorite among data mining practitioners. Net lift models are designed to target undecided or swing customers (similar to targeting swing voters in an election campaign) to get incremental lift in revenue from marketing campaigns, while not targeting customers who would have bought it whether or not they received a promotion offer. The key learning from Kim’s session is to use appropriate variable selection and transformation methods while preparing data to maximize returns from Net Lift Modeling.

Next-up were my colleagues, Manya Mayes and Fiona McNeill, who shared a cross-industry text analytics case study and best practices for classification, sentiment analysis and search techniques in the SAS lab session.

I also hosted Birds of Feather topics on in-database analytics and rapid predictive modeling during lunch hours on each day at the conference. Other SAS topics included were Twitter analysis, sentiment and social analysis, and time series data mining. These topics generated good discussions in a short group sessions around trends, adoption and customer interest/readiness.
Continue reading "More from Predictive Analytics World"

The last time I mentioned Accenture on this blog, I linked to their recent survey results, which show that companies are recognizing the value of predictive analytics – and are planning for it.

What does that mean for business analytics vendors? In a lot of ways, it means business leaders don't need us to market the idea of analytics to them anymore. They've bought into it. They've read Competing on Analytics, The Numerati or The New Know. They've seen analytics work, and they get it.

So what do they want? They want specifics on how to start using analytics to solve problems in their organizations today.

I think Jeanne Harris and Tom Davenport were aware of this shift when they wrote their new book, Analytics at Work. Where their first book, Competing on Analytics, set out to convince readers about the benefits of analytics, this latest book describes how to deploy analytics one decision at a time. It's more of a how-to manual for bringing analytics to your day-to-day operations.

This is also why the extended partnership between SAS and Accenture is important. Both companies are planning to re-up their commitment to bring analytics into the workplace at the point where the business needs them the most - wherever that may be.

Continue reading "SAS and Accenture: why it matters"

I am attending the 2010 Predictive Analytics World event in San Francisco. Parallel to an overwhelming interest and awareness in analytics in general, the conference has been sold out.

Day 0 (Feb. 14th) kicked off with a pre-conference workshop featuring SAS Enterprise Miner with Dean Abbott. 24 attendees showed up ready to take a deep dive into data mining using KDD Cup 1998 data. The attendees came from variety of industry segments, with only a few having SAS experience. The exercises followed the steps laid out in the analytic lifecycle to develop and score a predictive model that identified donors with a high likelihood of responding, to make fundraising cost effective. We received invaluable feedback on the key role analytic data preparation plays in building better, effective models. One of the attendees commented, “SAS Enterprise Miner is so easy to use that it has set the bar for me for any other data mining package.”
Continue reading "Reporting from Predictive Analytics World"

With more and more people talking about unstructured data, you may have started to come across terms like natural language processing, content categorization and semantic analysis. But what business value could you possibly get from such academic-sounding technologies? You'd be surprised. Today's SAS press announcement about the newest release of SAS Text Analytics says: The Associated Press, eBay, Factiva, Forbes.com, HP, NY Times Company, Reed Business Information, Sony, Tribune Interactive, washingtonpost.com, Wolters Kluwer, the World Bank and Yahoo! use SAS to analyze unstructured data and understand customers, market opportunities, internal operations and supply chains.
More specifically, here's a list of five interesting things you can do with text analytics:

1. Pair online borrowers with investors: Unlike traditional loan applications, Agata's forms for lenders and borrowers include a lot of open-ended questions. SAS Text Miner made it possible for the online social lending and credit scoring marketplace to analyze unstructured data and interpret the traditional score using information from community participants and their experience profile taken from the Web.
   
   
2. Automate online recruitment: ChinaHR.com, the first company to offer online recruiting services in China, uses text analytics to extract data from résumés regardless of what format they are in, and identifies key information requested by employers. “SAS helps us stay a leading force in online recruitment in China and across Asia,’’ says VP Hai Yang.
   
   
3. Reduce workplace injuries: AFA Insurance is analyzing free-form, handwritten text on insurance claims forms to find connections among thousands of documents and terms and present results in meaningful population clusters. Text analytics has decreased administration costs, reduced workplace injuries and improved the quality of analyses.
   
   
4. Anticipate and address public complaints: The Hong Kong Government's Efficiency Unit analyzes citizen complaints in multiple languages to better understand underlying issues and quickly respond even as situations evolve. “The solution consolidates all information and uncovers hidden relationships through statistical modeling analyses,” says the Efficiency Unit’s Assistant Director, W. F. Yuk. “It helps us understand hidden social issues so that government departments can discover them before they become serious, and thus seize the opportunities for service improvement.”
   
   
5. Quickly classify and tag content: Major US media companies automate the process of grouping and tagging content for hundreds of items per day at TV and newspaper Web sites across the country. One leading daily paper reports that all content is automatically tagged, articles are showing up higher in search engine displays, and e-mail news alerts have a 50 percent click-through ratio.

Using these examples as inspiration, how might you use text analytics? What unstructured data source could you analyze or classify to improve customer support, market opportunities or product development?

Friday’s webcast on “Preparing for the Recovery” from Cornell Center for Hospitality Research and SAS was somewhat of a wake-up call for me. It made me realize that our industry, hospitality and gaming, will not just magically sail into the recovery. (OK, to be fair, I certainly suspected this, but I was reminded of how much work is left to come!) It will be an uphill climb. I heard Bill Carroll, Senior Lecturer Cornell School of Hotel Administration, equate it to hiking the Grand Canyon. We’ve made it to the bottom, but it’s still a long way to go to get back up to the top. Here are my top five takeaways:
Continue reading "Top 5 takeaways from "Preparing for the Recovery""

The National Association of State CIOs has just released an issue brief that has me very excited. “DO YOU THINK? OR DO YOU KNOW? Improving State Government Operations Through Business Analytics” gives an overview of business analytics and includes examples of effective implementations.

The brief’s title paraphrases the quote “Do we think or do we know?" from Jeanne Harris and Tom Davenport’s book Competing on Analytics, where it is attributed to Gary Loveman, the CEO of Harrah's. This simple quote gets at a common problem in organizations, government or not. Are you operating on instinct, past assumptions or inertia? Or are you analyzing data to get at the truth?

States are facing unprecedented budget shortfalls, and we’ve had many conversations with NASCIO educating them about how business analytics can help increase revenues and decrease expenses. In fact, you will see a graph that we often use at SAS to show the different types of analytics on page 9 of the report.

The North Carolina Office of State Personnel is the subject of one of the case studies (on page 8 of the report). Employing business analytics in workforce planning, as NCOSP has done, is just one area where SAS can help. In addition, reducing fraud, optimizing tax and revenue collection and improving efficiencies can all be accomplished with business analytics, and these are priority areas for my team in 2010.

I smiled when I read a part of the report that described business analytics as “beyond business intelligence.” Hmm…Beyond BI…where have I heard that before? Oh yeah, it was a marketing slogan SAS used years ago! I’ve enjoyed my conversations with the folks at NASCIO and it’s gratifying to see them offer to their members such a thorough and informative summary of our core strength.

You have seen it in the news: A major automaker recalls millions of vehicles. The recalls spread beyond U.S. to Asia and Europe. Sales and production of a number of models gets suspended. The company faces intense federal scrutiny.

The impact? Billions of dollars in sales and warranty costs, potential loss of entire markets and – most importantly – a loss of reputation. For a company that built its reputation on quality and dependability, these recalls can amount to existential uncertainty.

Market watchers and industry analysts can argue about what caused this crisis. Was it management’s excessive focus on cost cutting? A change in sourcing strategies from dependable suppliers to unfamiliar, new ones? Or was it the desire for a rapid expansion to gain the No. 1 automaker spot in the world? The reality is that the once revered company is facing its biggest crisis since its inception. And while the starting point may have many causes, the deeper underlying issue is the disconnect between the manufacturer’s strategy and the execution, caused by a dissonance between the performance metrics at the operational level and at the strategic level.
Continue reading "Supply chain performance management: ignore analytics at your own peril!!"

Manya Mayes, a Solutions Architect and Chief Text Mining Strategist at SAS, just gave a wonderful presentation about using SAS Text Miner with SAS Content Categorization. Both products have been used successfully by SAS customers for some time. But Manya and our clients are now using them to solve old problems by using a few new tricks.

Manya invited me to watch the presentation because we're both interested in gleaning as much information as possible from our Twitter and social media conversations. Manya has been doing a great deal of research into sentiment analysis, which is mining data, including messages such as e-mail, text messages, call center traffic and Twitter, to determine how an audience “feels” about a topic. She wanted to show me how her research applies to our shared social media interests and to an organization's need to understand what customers are thinking and feeling.

Continue reading "If only you knew what I was thinking …"

Last week was a busy one in the world of business analytics. The biggest news for SAS is our ranking as a leader in predictive analytics and data mining by an independent analyst firm. In The Forrester Wave: Predictive Analytics and Data Mining Solutions, Q1 2010, SAS earned top overall ranking in all three categories – current offering, strategy and market presence – including perfect scores for functionality, professional services, licensing and cost, direction, and company financials criteria.

Separately, new research launched last week from our friends at Accenture shows that most global organizations are failing to use analytics to make informed decisions and predict future business events.

What are we to make of these two divergent studies? On the one hand, you have a report that says there are at least nine qualified vendors that provide mature products for predictive analytics. On the other, you have survey results that say most executives are still primarily trusting their instincts. In fact, their organizations are encumbered with "siloed data, outdated technology and a lack of analytical talent."

Are most businesses in a hopeless situation, buried in data, organized chaotically and too overwhelmed to find insights? Or are there still opportunities to re-prioritize and start making decisions based on predictive insights?

Continue reading "It's not too late for predictive insight"

When I attend a conference as a participant, one constructive practice I have acquired is to, immediately after completing the post-conference evaluation form, create my own personal “take away” worksheet. Nothing complicated, just two columns which can be labeled left/right, debit/credit, sooner/later, or plain/peanut. Don’t attempt to create this worksheet until after you’ve seen all the presentations and participated in all the discussions, workshops and roundtables - there is too much of a tendency to get overly excited about what you are immersed in at the moment; wait until you have gained some perspective.

The left hand column consists of those things that you’ve learned you are doing wrong and need to stop doing, or need to replace with an easy to implement change/alternative, and those things you feel you need to change or improve that can be accomplished without a project plan.

The right hand column consists of those areas where you want to improve, enhance or make major process or cultural changes that might, and probably will, require a project plan. Three to five items in each column, and once completed, circle ONE, and only one, from each column, for immediate action. This circled item is the one to which you will commit yourself to accomplishing no matter what; even if most or many of the others turn out to be impractical or inapplicable, you WILL commit to one short term and one medium term result. Lastly, write the words “WATCH IT!” underneath the list (to be explained).

In my participant ‘role’ as head of finance at the CFO Corporate Performance Management Conference held earlier this week in New York, this is what my final list looked like:

Continue reading "Pick one from each column: A CFO's post-conference to-do list"

I kept hearing that the Big Ideas session at NRF was standing room only, but until now I hadn't read a good recap. Retail TouchPoints comes through, describing the guest intelligence presentation from Eric Bibelnieks, group manager for guest data and analytical services at TARGET Corporation.

Pre-conference materials said, "In this session, you'll learn how Target uses guest intelligence to optimize marketing and merchandising processes – with the ultimate goals of enhancing guests' shopping experiences, driving store performance and creating brand cachet that's the envy of the industry."

Read the Retail TouchPoints article to find more details about these nine lessons TARGET learned along the way about optimization:

1. Analytics.
   
2. Data Quality & Standards.
   
3. Financial Resources.
   
4. Clearly Defined Roles.
   
5. Training.
   
6. Hire Analytical, Reporting and Data Analysis Talent.
   
7. Prototype, Learn then Develop.
   
8. Test, Learn then Scale.
   
9. Balance the Art and Science of Retail.

Looking for more tidbits from NRF? The Big Idea blog ran a great post about the business analytics talk with Chris McCann and Tom Davenport, titled Ten tidbits from today’s business analytics session.

Day one of the 2010 CFO Corporate Performance Management Conference in New York is in the books, and while the day’s presentations and discussions should rightly merit being the prime subjects of this post, those events have been overshadowed by one of even greater magnitude: dinner with Thornton May. Where does one start? Where does one end? Before the salad course was finished the topic for the evening had been laid on the table for critique: “SIM City for business decisions.”

Thornton and I were joined in this dialogue by Douglas Hubbard, a specialist in decision analytics and the author of several books on the subject. The impetus for this topic was the acknowledgment, supported by Hubbard’s data, that very few businesses are measuring and monitoring metrics and KPI’s that actually matter. Most businesses are completely surprised to find that the primary driver of their principle objective is one that they have not considered nor recognized as being even slightly important. While many organizations struggle to trim their initial 400 KPI’s down to a more manageable 30 or so, a statistical analysis of their data would generally show that fewer than a dozen are truly meaningfully significant from a cause and effect perspective, and would suffice to manage their performance against.

The unreliability of human judgment is borne out with studies that show judgment-only forecasts are less accurate than the most basic of simple forecasting techniques, and further, that a model that simply averages these human judgments is more accurate than the judgments themselves. In short, human judgment tends to be too optimistic, too confident in its own abilities, and completely miscalculates associated risks. As they say, “Experience is inevitable, learning is not.”

The conversation narrowed its focus a bit during an informative discussion regarding the high efficacy of Monte Carlo simulations in aiding forecast accuracy and in improving decision making. Nuclear power plant simulators are a great example of using simulation to train operators to make better decisions under pressure and over a wide range of simple and multiple system failures. Captain Sullenberger’s heroic landing of his plane on the Hudson was most certainly not a case a good fortune; it was a case of hours and hours in a simulator practicing just such maneuvers.

As the final coffees were being cleared from the table, the consensus was building that management science, and specifically decision making, would only come to fulfill its promise when the power of analytics and simulation was brought to bear. “SIM City for business decisions,” was Thornton’s summation of what is needed to augment human intelligence and judgment in order to significantly improve business decision making. The learning may not be inevitable, but with analytics it certainly becomes much more probable.

In case you missed them, here's what was hot in January on this blog, from sascom magazine and on all SAS blogs.

The top three posts from the sascom voices blog:

1. SAS employee reactions to the FORTUNE news
   
2. Take time to learn about analytics
   
3. Analytics for beginners and beyond

The three most popular articles from sascom magazine:

1. Understanding analytics
   
2. Getting started with analytics
   
3. Hot, fresh and on demand

The top three posts from all SAS blogs:

1. The seven deadly sins of partnering
   
2. The Best Karts in “Mario Kart Wii”
   
3. SAS 9.2 and SAS Enterprise Guide 4.2 on Windows 7
   

I think I see a theme there. Analytics anyone?

AnalyticsCamp is an unconference started by Nathan Gilliatt after a group of us met at a networking meeting in Raleigh last year called Web Analytics Wednesday. The first AnalyticsCamp will take place at UNC's Kenan-Flagler Business School in Chapel Hill on Saturday, February 6th, hosted by UNC's MBA Marketing and Business Technology Clubs. It is themed around bridging analytics silos to bring analysts of all stripes together on one day.

SAS is a sponsor of the event, and I and several other folks from SAS including Manya Mayes, Richard Foley, Angela Hall, and Varsha Chawla have volunteered to lead sessions and help organize some of the behind-the-scenes logistics. In this guest post, I'll be interviewing Nathan about the unconference:

Nathan Gilliatt, Net Savvy ExecutiveWhat is AnalyticsCamp?
AnalyticsCamp is a day for people who work in different analytics specialties to meet and learn from each other. We have great sessions lined up, but it's really about the people who show up and what they do with the day.

How did the idea come about?
Talk about AnalyticsCamp started after a panel on social media at Web Analytics Wednesday, when we realized that we had too many interesting topics for the quarterly meeting schedule. I had been to several unconferences, and the format seemed perfect for a day filled with all the analytics topics we wanted to talk about. We connected with a couple of the student clubs at the UNC Kenan-Flagler Business School, and soon we had a perfect place for the event. With a full day and multiple classrooms, we can explore 30 topics and attract many more participants than we get at weeknight events.

Why the theme “bridging analytic silos”?
I've noticed closely related specialties that seem to be kept apart by a modifier--web analytics, email analytics, social media analytics, customer analytics... and that's just in marketing! They're chasing similar objectives and using similar methods, but the modifiers keep knowledge and practices trapped in analytics silos. By de-emphasizing the modifiers and focusing on analytics, we're creating an environment for people to learn from the other specialties and, in the process, meet interesting people they might not otherwise meet.
Continue reading "All about AnalyticsCamp"

Bringing in a new software package or expanding the use of an existing one is an exciting endeavor for a company. The benefits SAS can bring your organization are extensive and will, without a doubt, outpace the expense many times over. But for SAS to fully deliver on its promise of immediate and significant ROI, your analytical staff must learn how to use the software. Training your user base on the effective use of SAS can be one of the highest return-on-investment endeavors you can make in your company.

In the paper, "Are you getting the most out of your SAS software," I describe the benefits of training your SAS users and the negative costs of not training them. Citing research from a number of well-respected groups including the Gartner Group, ICD, and the American Society for Training and Development, this paper outlines the 11 reasons to invest in training. You can download the complete paper for more details (and for a full list of references).

Continue reading "11 reasons to invest in training"

Welcome to Communications’ Survivor: Marketing Edition. I'm your host, Becca Goren. Today’s teams come to us from the marketing department within a large communications service provider with offices worldwide. The Chief Marketing Officer, Suzie Pass will be our judge. She’s been tasked to cut 15 percent of marketing’s operational budget.

To survive, these teams will need to do more than make cuts – that’s too easy. Instead, they need to ensure they don’t sacrifice long-term profits as well. Suzie has selected two divisions under her to take on the bulk of the challenge. The teams will be armed with a personal analytics coach from the company’s analytics team and an array of SAS business analytics to guide decision making. The survivor will get to keep his/her job.

Episode 1: The team strategies

Team 1: Business to Consumer Marketing led by Director Maxie Prospect
Maxie: Our inspiration came from a telecom service provider a lot like us. They use SAS to optimize monthly promotional campaigns for DSL, wireless, cable and phone service – maximizing customer lifetime value. The company reported $6 million a month profit gains during the trial phase alone.*

Our strategy is twofold:
1. Reduce Costs: Analyze then eliminate our redundant and ineffective campaigns.
2. Grow Revenue: Restructure campaigns to offer the right product/service to the right customer at the right time with the right channel.

This will improve our return on campaign and increase revenue flow - even with fewer campaign implementations. I really believe that if we have the analysis to support our theories we’ll be able to implement this strategy and overcome our cultural obstacles.

Suzie: That sounds nice. In theory. But you’re making quite a few assumptions. If this is such a great strategy, why didn’t you implement it last year? We’ll see if you really can turn this around.


Continue reading "Communications’ Survivor: Marketing Edition. Cutting Costs, Not Profits."