John Saaty’s “aha moment” came in the late 1990s during a meeting at Intel, the widely-respected microchip manufacturer where he worked.
“We were deciding how much to spend to launch the Pentium 3, and [Intel co-founder] Andy Grove asked how much Microsoft spent to market Windows in 1998. Someone said $300 million.”
Whew. Grove wondered aloud whether there was a better way to come up with an estimate.
Saaty realized right then that there must be a business in answering such questions for companies if a firm with the smarts and expertise of Intel sometimes lacked enough information to make the most informed decisions.
The revelation put him on the path to Decision Lens, a Ballston-based consulting firm that tries to quantify the intangible so it can be inserted into the equation of decisions.
Founded by John Saaty, 43, and his brother, Dan, the company is also a family success story that spans six decades and involves a famous mathematician.
Decision Lens applies its formula to all sorts of problems, whether it is advising the Joint Chiefs of Staff on how to spend billions, helping Kraft Foods decide which candy bar to market, or even coaching the Super Bowl XLV winner Green Bay Packers on which players to draft.
“We help answer football questions like: ‘What are good hands? Or which is more important, 40-yard-dash speed or upper body strength?’ ’” said Dan Saaty, 40, who can riff at length on the best methods for evaluating athletes.
Sounds squishy, but their numbers are anything but: Decision Lens grossed $6.7 million last year and expects to hit $9 million this year, with a 20 percent profit margin.
Perched in a sunny, 14th-floor office overlooking the Ballston Metro stop, it has around 35 employees and zero debt. The brothers earn six-figure salaries and own the firm together. They’ve had some nibbles from potential buyers, but they have no plans to sell.
The firm’s 70 customers span the United States, Brazil, the United Kingdom and Australia. Decision Lens charges from $80,000 to $500,000 to license its software, depending on the size and scope of the software’s use.
For example: aerospace giant Boeing may need help deciding what design trade-offs need to be made on the fuselage for a new plane. That would be a relatively straightforward project. Or Boeing might need a more expensive license when it is deciding where to build a new plant, which vendors to choose and how to supply it. That would be a whopper.
The Saatys’ father is Thomas Saaty, a respected mathematician and author who immigrated to the United States from Iraq in 1946. (He served as a deckhand on an iron ore ship that sailed in 28 days from Alexandria, Egypt, to Baltimore.)
Thomas Saaty, now 85 and a professor at the University of Pittsburgh, is best known for quantifying things that people didn’t think could be quantified.
“He was able to place numerical ratings on people’s likes and dislikes, or their preferences,” John said. “There is no scale for subjective intangibles like how sweet an orange tastes to you, whether a person has more risk tolerance for bungee-jumping or kayaking, and which a person fears more: jet bombers or nuclear missiles.”
The bottom line: The greater diversity of input into a decision, the more chance it has of succeeding.
John Saaty said he saw the business possibilities to his father’s work when he was a youngster growing up in Pittsburgh.
John studied liberal arts at Northwestern University and earned a master’s in business administration at the University of Pennsylvania’s Wharton School. He studied entrepreneurial management at Wharton and wrote a paper on the commercial possibilities of his father’s work.
“There was so much potential, and no one had really tried it full-fledge,” John Saaty said.
Dan studied sociology and statistics at the University of Pittsburgh and developed an expertise in multi-party decision-making.
John left Intel in 1999 and joined a couple of Washington-based start-ups before launching Decision Lens in 2002.
“I said to my brother, ‘We’ve got to take it out of academia and apply it to the real world,’ ” John said.
They began developing Decision Lens in 2002, working on it during their off-hours while they were at a local start-up. They took out second loans on their homes and maxed out their credit cards. John put up $70,000 and Dan put up $50,000, and they hired an engineer in South Africa to start writing the software because he was “the cheapest guy we could find to code Java,” a software code language.
“We took my father’s complex theory and boiled it down to a few simple software steps,” he said.
Their first offices were above an architectural firm in the attic of a Falls Church house. Their first customer was Military Health Systems, which in 2005 paid them $65,000 to use their software to improve military health care.
Decision Lens earned $400,000 that year. In 2006, that more than doubled to $1 million, providing enough of a safety net so that the brothers could quit their day jobs. It was all upside from there, with the company doing 40 percent growth year over year.
The reason? Part of it is an expert, three-person “lead generation team” that scours sites such as LinkedIn for executives to call. The team arranges more than 100 sales meetings a month, which has led to 70 clients worldwide.
About 60 percent of their client base comes from the government, the rest the private sector. Virtually the entire U.S. intelligence community is a client, as are Johnson & Johnson, Pfizer, the Oakland Athletics and Walgreens. Amtrak, Metro, Arlington County Schools, Petrobras, the National Hockey League, Siemens and eBay use their software as well.
The client names were on a colorful flat-screen TV when I visited their offices last week. They had spread out some sodas and finger food in a nearby conference room to celebrate their new 10,000-square-foot offices, which have a view of the National Cathedral and Bethesda in the distance.
I asked the Saatys whether they used their software when deciding on the look and location of their offices. Of course, they said.
Just check out the view and the proximity to the Metro.
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