Patent and IP investment can often prove to be a very complicated and multifaceted business. As a patent owner, how do you begin to put an initial price on a patent? How can you quantify and justify a patent’s monetary value when preparing a portfolio or a single patent for a potential future transaction?  

On the flip side, as a patent investor, how do you know which patents or patent portfolios are worth investing in? How do you begin to perform risk management and due diligence checks on a patent portfolio before making the leap into parting with your money and investing in something which is, when push comes to shove, an intangible asset? How cautious should you be?

As you can see, having only just scratched the surface, you can already begin to appreciate that there are many questions that both patent owners and patent investors need to ask themselves before even considering how and when to take the next step into the realm of patent investment and IP investment.

In our upcoming series of insightful white papers, we will discuss the following:

What is Patent Lifecycle Management?

Operations in Different Stages of the Patent Lifecycle

How to Use Big Data to Make Data-Driven Decisions

How to Use Big Data to Support Your Operations

Before the release of our next series of white papers, we would like to take a brief look at the traditional approach to patent investment before offering our insight into the reasoning behind why we should be rethinking patent investment strategies.

Moreover, our series of white papers will also aim to highlight why and how Artificial Intelligence and Big Data are paving the way for a more productive and effective method of preparing for and executing patent and IP investment and managing patents during the various stages of their lifecycle.

The Traditional Patent Valuation Process

First and foremost, before a patent can be sold or bought, the monetary value must be placed. The patent valuation process is typically split up into three separate stages: the diligence stage, the analysis stage, and the reporting stage.

Traditionally, each stage of the patent valuation process is performed manually. As you can imagine, manually performing due diligence checks, performing analysis and then reporting on your findings and conclusions can prove to be a highly time-consuming and arduous task.

Diligence Stage

Performing due diligence checks on a patent or portfolio of patents should be considered as one of the initial stages of the patent valuation process prior to investment or transaction. This legal exercise should be carried out with the purpose of determining the real value of the assets (in this case, patents.)

More often than not, all of the required or desired information is not always available but should include documentation which highlights the value of the patent(s) and how much value the patent(s) will hold for the remaining duration of their life. This documentation typically includes (but is not limited to) the following:

  • Limitations of the patent(s)
  • License agreements
  • Previous costs associated with the patent at issue e.g. development costs
  • Technical information
  • Legal information
  • Business information

Analysis Stage

The income-based method, cost-based method, option-based method, and the market-based method are the four most commonly used approaches used when considering patent valuation. The general consensus is that using multiple approaches is favored over a single method.

Reporting Stage

The final stage in traditional, manual patent evaluation is to report on the findings, conclusions, assumptions and the work carried out during the patent valuation process.

Mindset Shift

As you can see, manually preparing for patent and IP investment takes a lot of time and effort. AI and Big Data can support mindful and effective decision making.

As mentioned earlier, our next series of white papers will shed some light on how and why big data and AI can support and optimize patent investment and patent lifecycle management throughout all stages of the patent’s life.

When rethinking patent investment, we must consider the following:

  • Are patents assets or debts?
  • Is patent management just a continuous investment process?
  • Can the continuous accumulation of big data help to shape patent assets?
Rethinking Patent and IP Investment Statistical Chart

Patent investment flow

Patents are assets, they are “intellectual properties,” and “rights,” and they are classed as being valuable. Since patents are not tangible, in accounting, they are often referred to as “intangible assets.”

The essence of patent management is no different from a tangible asset such as a car.  One wouldn’t typically invest in a car after buying it, but would, however, pay a maintenance fee (of sorts.)

You will only maintain a patent after it has been granted (when you have the rights.) Patent management is a continuous investment process if, and only if, asset management is a continuous investment process.

For practicing entities, innovation (R&D,) asset management should be a  continuous investment process (because it is at the core of the business.)  Patent management simply transforms part of the innovation output into intangible assets and maintains them.

When it comes to managing the respective patent(s), again, it is like the car or any other tangible assets. However, the difference is that the quality and value of such intangible assets are unstable (unlike a tangible asset such as a car.)

The shaping of patent assets is similar to the idea of industry 4.0, the prosecution of a patent is just like the manufacture of a car.

So, in theory, the shaping of patent assets supported by the continuous accumulation of big data is similar to the idea of industry 4.0, which also supports the manufacture of products utilizing the accumulation of big data.

What’s Next?

The next installment in our next series of white papers will provide an in-depth insight into patent lifecycle management. In particular:

  • Uncovering technological development insights
  • Optimizing budgeting and resource allocation
  • Enhancing the quality and value of patent portfolios
  • Minimizing unnecessary patent investment
  • Maximizing the ROI of patent assets