Data's payoff in the patent department

In the 2011 biographical movie, Brad Pitt starred as the guy who employed the assistance of a number-crunching economist to put together a competitive team despite having less money than most other major league teams.

Data's payoff in the patent department
In the 2011 biographical movie about Oakland Athletics’ general manager Billy Beane’s efforts to assemble a winning team from a small budget, Brad Pitt starred as the guy who employed the assistance of a number-crunching economist to use data and analytics to put together a competitive team despite having less money than most other major league teams — about one third that of the New York Yankees.

The movie was based on Michael Lewis’s best-selling book: Moneyball: The Art of Winning an Unfair Game, which has since been applied to various professions to show how if you take data already available to you and apply it strategically, you can produce better results without spending more.

But can that same theory be applied to managing the complexity and perceived uncertainty of managing in-house patent departments? Apparently, yes. During a session at the Corporate Legal Operations Consortium annual conference in Las Vegas in May, David Ishimaru, senior director of patent asset development at Yahoo, Inc. presented on the subject of “Moneyball Patent Asset Management.” Ishimaru says the Moneyball approach is “synonymous with the intelligent use of data.”

Ishimaru wanted to see how he could apply Moneyball methodology to patent management on a day-to-day basis.

In 12 years, Ishimaru has helped build and manage the company’s global patent portfolio from the ground up. He has developed and implemented many of the department’s processes, vendor management, financial modeling and patent analytics capabilities. He’s also involved in the company’s open-source, standards-setting and patent-monetization efforts.

He grew up in Silicon Valley surrounded by technology and companies innovating first with computers and then eventually the World Wide Web. He talked about how his internships in law firms revealed that work wasn’t being handled smartly. An electrical engineer and Stanford grad, he came from a background where technology played a role in many aspects of work only to enter the legal field where the idea of high tech was using Microsoft Excel.

The patent group at Yahoo hadn’t been formed yet when Ishimaru joined it in 2004. “I was very frustrated by the fact there was very little technology being brought to bear,” he said. But over the years, one of the ideas he has come to embrace at the patent group is “if you can’t measure it, you can’t improve it.”

In-house groups retain outside counsel to help maintain patent assets, but unlike other matters in a legal department that receive direct oversight, such as litigation, with patents there are thousands of things in the pipeline without direct supervision by in-house lawyers.

“It’s common to use multiple law firms and, therefore, we’re probably very annoying to our legal operations people,” he said.

Every morning when he arrived at work, a paralegal he worked with would have two stacks of mail to go through containing critical activities related to the company’s patents. “We had a very primitive homemade docketing system just starting to be populated. They would open the envelopes and see that we missed a filing deadline so we would call outside counsel.”

Ishimaru pointed out that much like the Oakland A’s, he decided the in-house department in charge of patent assets needed to get creative and efficient in how it was using its external counsel payroll.  

“They [Oakland] had a lot of opportunities to say ‘we can’t compete on money, we have to use our money more efficiently and challenge traditional inefficiencies,’” he said.

The Oakland A’s started measuring what contributed to a win and using data to measure a player’s contribution to a win and where a market was undervaluing players so they could more efficiently use their money and optimize where their money was spent.

So what do Moneyball and patents have in common? “There’s a lot of data and strong incentive to improve and everyone likes to win,” said Ishimaru.

Some lessons he has taken from the Moneyball book around gathering the right data include:

• What are the right questions to ask? Make sure you’re asking the proper questions.

• Look at whom you are paying money to.

• Ask tough questions and ones you can use data to support.

“If you don’t have data to back it up, you can’t measure if you’re wrong or right in your assumptions,” he said.

• Know what your data’s strengths and weaknesses are — is it good for projections or trends? Maybe, but it’s not what may actually be happening two years from now.

• Past performance is not always an indication of future success, but it can be. There are a number of things statistics don’t measure.

They also tackled the issue of budget — just how much was the department spending on patent asset work and what would be demanded for the future?

“When we first started, if you had asked us what we were spending, we would have said ‘let’s go talk to the law firms and try and get an answer.’ If you said what will we be spending a year from now, we’d say ‘let’s go talk to the law firms and ask them,’” said Ishimaru. “At the time, we had 30 different law firms working on patent prosecutions — many of them were not working on very many cases and so, in order to get their attention and get them to give us information, it took a long time.”

He saw it as an opportunity to start from scratch and figure out what the legal department needed to do to answer those budget questions.

“Anyone else in Silicon Valley could answer these questions and the fact we can’t is really quite sad. We needed a plan to stay on budget and track progress towards that — ask how are we doing right now and estimate the next year, two years, four years and five years down the line. What’s our budget going to be like? What’s the impact of decision-making today in the long term? Did our spending reflect priorities? How can we use data to project the cost?”

The other important factor Ishimaru knew was that any time you provide a budget, management is likely to say take 10 to 20 per cent off of that. In a situation like that, you have to look at things you can control, what is optional and what can be pushed off.

He realized they needed cost and docketing data — what actions are happening now and what will be happening in the near future.

“At the beginning, we didn’t have much data, but we were in a position to use data. We could go to the law firms and say if you want to do work with us you have to give us cost savings but also have to give us data in a certain way, so not only were we thinking about how to use the data but also make sure the law firms complied with what we were asking. It was about how will we review all the invoices and how can we control them?

Yahoo had caps and fixed fees for certain things and still some hourly rates. It told its law firms they could only bill for completed work.

“We needed to be on the same page as our law firms and make sure we were talking about the same things. For example, in RFPs, comparing apples to apples,” he said, noting that CLOC is bringing together different groups to try and come up with industry guidelines for a common vocabulary in this area.

Eventually, it did a budget and narrowed down its external law firm roster to one third of the law firms it was using.

“We were able to look at trend lines and say if we have 800 cases every year they will sit at the patent office for two years and then we will hit a period of activity and so then we will start to see where our costs would increase 20 to 30 per cent,” said Ishimaru.

 Looking at that kind of trend line will help the department prepare finance for the cycle and how much money it will need to spend.

“Now we’re preparing well in advance of the consequences,” he said. “We also started providing feedback on the patent group internally so we could look at are we doing what we want given the strategy we have.”

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