Intrapreneurs And Patents: Lessons Learned

By Mary Juetten

The battle cry for those in the business of identifying and protecting intellectual property (IP) has long been “ You can’t protect what you don’t know you have.” This especially true for early-stage companies, who amass a lot of IP in a short period of time. Furthermore, identified and protected IP matters big time to investors or VCs come valuation time.

About year ago, I wrote a three-part series on the importance of intellectual property (IP) identification and protection for early-stage companies. But what about those entrepreneurs who invent for large companies, often called “intrapreneurs”?

Over the years, I have researched the challenges companies face when teasing out the amazing inventions from scientists, engineers, and product developers. Many organizations institute reward systems, but the invention, development, and securely garnering interest processes are still difficult.

This is where patents come into play. We have worked with outside lawyers and in-house counsel to design a process to facilitate this information gathering. But once the invention information is sent to the appropriate person to review, then what? How does the invention get patented?

Obtaining a patent from the United States Patent and Trademark Office (USPTO) is challenging, but imagine filing for thousands of patents rather than just one! For the last 23 years, IBM has won the race to outnumber all other US companies like Samsung, Apple, Qualcomm, and Microsoft and received the most patents from the USPTO. In 2015, that meant IBM received a record 7,355 patents.

I recently interviewed Sushain Pandit, IBM’s Chief Engineer and Master Inventor in the IBM Analytics department, to learn more about the patent process and provide some tips for intrapreneurs and entrepreneurs alike.  Sushain was one of IBM’s youngest master inventors, and he’s passionate about innovation, to say the least.

Mary Juetten: Tell me more about your day job?

Sushain Pandit: I work as a hands-on software architect and master inventor in IBM’s Analytics group. My day job comprises of working with a team of engineers, designers, and product managers to conceptualize and build software products for our clients. My day could go from highly fragmented to highly monolithic depending on the project and team needs. Typically, at project inception, I could be meeting with product managers or clients to analyze requirements, perform solution design, and validate technology choices to align with the strategic direction. After that, I could be working with engineers explaining the design and user stories, defining best practices, writing lots of initial code, and setting up automation. Once the project is bootstrapped, I could be mentoring new hires, performing code reviews, delving into integration with other products, advocating our product through publications, and protecting our technology and algorithms through patents.

Juetten: In an average month, how much time do you spend as a reviewer?

Pandit: As master inventors, we are expected to assist our company in development of holistic patent portfolios. We do this by volunteering as reviewers who help identify patentability of ideas submitted by other employees and support the IP legal team in pursuing patent infringement cases. I’m part of a couple of invention review boards in [the] data and analytics space, which takes 5-10% of my time on average.  

Juetten: Do you still invent on your own?

Pandit: Yes, I was an inventor on five patents that were granted in 2015 and more than 10 patent applications that were filed at USPTO. That said, of late, I’ve been more focused on helping the company develop a broad and consistent portfolio in [the] data and analytics space by volunteering my time on review boards and helping [the] IP legal team.

Juetten: Any thoughts on the next big thing in artificial intelligence (AI) or Data?

Pandit: Near term, I think cognitive technologies would continue to emerge and augment human capacity. It’d be interesting to see how they continue to aid in real-world use cases in healthcare, finance, banking, travel, and consumer space. Data about people, products, businesses, geo-spatial factors, and events would continue to be put to use through analytics, leading to new actionable insights. I’m also excited about how virtual and augmented reality (VR/AR) tech and [the] Internet of things [will] evolve in 2016.

Considering a longer-time horizon, Moore’s law, and its predicted limitations, it’d be interesting to see how nano-machines or nanobots evolve over time. If they do find their way into mainstream medical tech, impact on disease prevention could be profound. Over the years, virtually all AI research (academic or industrial) has increasingly (and very successfully) focused on individual tasks (e.g., play chess, answer questions, follow a path, recognize a face, etc.). This has been a fruitful detour from the first generation of AI researchers who thought artificial general intelligence (a.k.a. strong AI) would be possible where a machine can successfully perform non-specific intellectual tasks. It’s mostly been part of futuristic fiction since. However, if there are discernible advances in whole brain emulation and Moore’s law holds up, I’d be surprised if there isn’t a rekindled mainstream interest in strong AI.

Juetten: What advice would you give inventors on preparing to pitch their patents to a company?

Pandit: Pitching your idea as an employee to have your company pursue a patent application would be different than pitching a patent to a company as an outsider for licensing purposes. In the first scenario, one would need to demonstrate that the idea is novel and non-obvious from the prior art, has business value, and can be reduced to practice (can be implemented). It almost always helps to have a flowchart or figure(s) in your disclosure to facilitate understanding.

In the second scenario, the fact that the inventor has a patent is usually enough to prove novelty, non-obviousness, and reduction to practice. So, main focus ought to be on selling the business value of the patent and justify that it makes sense for the company to pay you to license the idea. Sometimes, when pitching to large companies, it may help to have a patent portfolio (i.e., more than just one patent) to cover a broad idea and make a case for licensing or selling the entire portfolio. Alternatively, it may be worthwhile to expand the portfolio after validating the initial interest. For instance, inventor-turned-coach Stephen Key had about 12 patents, all relating to rotating labels between 1998 and 2007.

Juetten: What is the most common mistake or pitfall that you have seen in your reviews?

Pandit: From what I’ve seen in my five years as a reviewer and inventor, I’d say that not performing a thorough prior art search (i.e., looking for similar patents) before submitting an idea tends to be the biggest pet peeve of reviewers and causes the [most] heartache to inventors after doing all the hard work to submit their idea. Then there are other considerations, like describing variations of your idea beyond the preferred embodiment, even if it’s in one to two sentences. This is extremely helpful in drawing a comprehensive set of claims and puts the company at an advantage when it comes to litigation. Reviewers usually have a mandate to not be “inventors” while they are reviewing, so it makes things easier if inventors’ take a moment to elaborate on variations.

Some business basics are the backbone to preparing a good patent application for review: create good documentation and explanations, use visuals, and make sure you do your background work. Just like looking for similar names or logos for trademarks, you can use free searches to find similar patents before investing too much time!

[This post originally appeared at Forbes / Entrepreneurs.]



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