When Jack Noonan took over Chicago-based SPSS in 1992, his goal was simple: Survival.
“When I started, we were about a $34 million company with $20 million in debt, and we were out of cash,” says Noonan. “My vision was very short-term. It had all to do with profitability and getting some new technology out the door.”
Noonan also was saddled with the company’s financial responsibilities.
“I was either lucky enough or unlucky enough that the day I was introduced to the board, the CFO resigned,” says Noonan. “So I walked through the door and became CEO and CFO and signed every check. You’d be surprised what you learn doing that.”
Noonan brought the cash burn-rate under control by putting a stop to the ordering of everything from paper clips to PCs, and he required a written justification for all supplies and capital purchases. He also eliminated the use of contractors, consultants and temporary labor, required executive review of all travel and reduced the costs of product packaging. He personally reviewed every invoice, looking for the nice-to-haves versus the need-to-haves.
SPSS, which stands for Statistical Package for the Social Sciences, is software created by three Stanford University graduates to analyze the massive amounts of raw data collected by researchers. The founders incorporated in 1975 as demand for the product grew and new uses were found. The software could analyze data, then predict possible outcomes, allowing for anything from NASA measuring the likelihood of part failures to the National Forest Service measuring incidences of injuries and bear encounters.
By 1992, the founders realized it was time to bring in professional leadership, and Noonan was hired. And once he brought stability to the company, he took it public to pay off its debt.
“We were instantly profitable, and it was a lot easier to manage the business,” he says. “The IPO was a very pragmatic decision. We only raised enough money to pay off the debt. We then did a follow-on offering the following year and raised enough money to do some acquisitions and move forward.”
Acquisitions were important, because when Noonan took over, SPSS had just one product. Diversifying the product base was one challenge, but Noonan also had to create a vision for an industry niche that didn’t exist; there was no other company to model itself after. The potential of predictive analytics was huge, because the software was now being applied to predict consumer behavior and was of great interest to retailers.
“One of the things we’ve done, we have in our strategic planning process something we call a strategic filter,” says Noonan. “It defines the business we are in and also defines the businesses we are not in. We use that strategic filter for all of our acquisitions, internal technologies and processes we implement.
“One of the component parts of our strategic filter is that we clearly focus on predictive analytics, but we also have another constraint, that is, we focus on people data. As we’ve looked at acquisitions, we literally found analytic applications that were profitable, growing and interesting but had nothing to do with analysis of people, understanding behaviors or changing them. So we’ve walked away from those opportunities because they were not core to what we believe our future is.
“In the entire company, all the component parts, whether it’s technology or how we go to market or how we manage the business, it’s all under the predictive analytics umbrella. If it doesn’t fit, we’ve divested it, and we have divested portions of our technology over time.”
Noonan has strung together nine acquisitions since 1992 and grown the company from $34 million to more than $224 million in annual revenue.
“If you look back over the last 13 years, about half of our growth came through acquisitions,” says Noonan. “The other half has come organically by being able to continue to grow the technology we’ve acquired. I think when we started acquisitions, because we were a single-product company, we focused on the three Ts: Technology, technology and technology.
“We were literally growing the product offerings within the same analytic space we’d always been in. We weren’t changing the business, we were broadening the (array) of like technologies and like offerings.” In 1992, SPSS was the first company to offer a Windows-based statistical software package, giving it a competitive advantage. By 1998, Noonan realized it was time to innovate again.
“There were a number of changes that was clear that needed to be made in the company,” says Noonan. “We needed to move from a desktop set of offerings to an enterprise set of offerings, which meant the technology needed to be more scalable and needed to run in a server environment and continue to support the desktop user.
“The technology we had needed to be componentized so parts could be used to build new offerings. This also would allow additional acquisitions to be integrated more easily.”
By breaking down its software into its base components, the company can respond more quickly to customer demands and create better customization features without having to reinvent every aspect of the product. This leads to more flexibility, quicker turnarounds and, ultimately, greater profitability.
“More and more, across the company, this componentization and reuse of technology is so important,” says Noonan. “If I have an analytic algorithm, I can use that same algorithm in an SPSS desktop application that I would use in a Clementine data mining product that I would use in a predictive call center application. More and more, we are trying to build technology that can be used across multiple tools and applications.”
Four years ago, Noonan changed the company focus from the three Ts to the three Cs.
“We now focus on capabilities, customers and cash,” says Noonan. “It makes sense because we have a broad enough product line now that, as we look at acquisitions, it’s important they come to SPSS with some specific market expertise and bring capabilities in that area foremost, and along with those capabilities, the real proof point is customers. Last, but not least, cash is king. You don’t want to spend a lot of money on it.”
The idea is to bring in a company with deep knowledge in a particular market, such as banking, and then apply SPSS’ expertise in analytics to get the most out of that market.
“They need to be strong on domain experience but either have weak or no analytics,” says Noonan. “We bring in the expertise and are able to integrate robust analytics with their applications.”
Noonan’s formula for acquisitions has been to fully integrate the new business into the new one.
“We typically bring the technology of the new business under the technology arm, the sales under sales, the service under service, and we roll forward vertically integrated,” says Noonan. “It’s always hard to integrate cultures. We try to make all the changes the first day. There’s typically a due-diligence process you go through, and there’s a time when the acquisition is public and a time period that it takes to finally complete the transaction of 30 to 90 days. During that period, you do all the planning, and the day the signature happens is the day you tell the staff what their new role is, and you align the combined entity around the combined strategy.
“All the organizational changes are made simultaneously. Everyone on Day Two knows what their job is and can focus on their new role.”
Future indicators
SPSS now commands a customer list that includes 95 percent of the Fortune 1000 and all 50 state governments, and has a suite of 40 products. It’s come a long way, but Noonan is still defining the niche at the same time SPSS defines new products.
“I believe the application of predictive analytics is in its infancy,” says Noonan. “The collection of data is also in its infancy. The amount of data about the operation of a corporation is growing exponentially. The opportunity to turn that into useful business information or knowledge or having decisions made automatically by software is in its infancy.”
The software enables analysis of human behavior and can automatically apply ways to change it. For example, if someone calls the call center of a telecom company, the software can immediately analyze the buying habits of the person, calculate how likely he or she is to leave the calling plan and deliver a personalized script to the employee to decrease the chances of the person canceling the company’s service.
“Our technology is used for many, many things,” says Noonan. “It does everything from prioritizing collections for the finance department to improving the recruiting process for students at academic institutions, identifying the best customers and finding new ones.”
But even with all the potential, it’s still difficult to sell because the ultimate end result is out of SPSS’ control.
“It is a tough sell because when you think about the application of this technology, it’s not just plugging it in and seeing a return on the investment,” says Noonan. “You use this technology to change your business processes, so not only do you have to be willing to make a change, you have to proactively make change in your organization. You’d be surprised at how many people talk about change but are unwilling to proactively make it.”
The potential for the niche SPSS has defined has plenty of room for growth. Market research firm IDC predicts that the market for predictive analytics will be $3 billion by 2008, and states that ROI for this type of software is 145 percent, much higher than for other business analytical software. SPSS reported an increase in diluted earnings per share of 18 percent in its first quarter, and is recognized as the industry leader by analysts. The news coming from the Sears Tower headquarters is almost all good these days, and the potential to keep it that way is high.
“I have a smile on my face these days,” says Noonan with a laugh. “The one thing I will say as I look at where SPSS has come from and what the future is, is that the opportunity for the application of this kind of technology has barely broken the surface of the places where the technology should and could be applied to increase the effectiveness of almost everything we do.”
How to reach: SPSS, http://www.spss.com
