How a new era of metrics is amplifying IP value

As AI empowers us to track more and better KPIs, the IP industry is finally being equipped with the data and capacity it needs to provide tangible indicators of return on IP investment, says Marcia Chang of Tradespace. 

Performance is measured everywhere—from sales and marketing teams’ quarterly targets, to the number of pupils achieving certain grades, to average patient wait times in healthcare settings.

But proving the ‘success’ of intangible assets such as IP is less straightforward. Quantity, an often used indicator of success, is misleading when it comes to innovation or IP value, with lengthy processes involved in prosecuting IP rights and complexity around judging their worth.

Over the last decade, there has been recognition that a focus on quality, rather than quantity, is more appropriate for measuring IP. More sophisticated key performance indicators (KPIs) such as claim quality and product alignment have been touted as better ways to measure IP. However, a lack of data and lack of common definitions across industries—and capacity—have sometimes hindered their implementation.

These difficulties have led to a “persuasion gap” when it comes to conveying the role of IP to company leadership. Compared to sales and marketing teams, it has been harder for IP departments to show the C-suite and board members how their budgets translate to company profits. Further complicating matters is the fact that the true value of a patent - its ability to deter competitors and protect profits - is either never conclusively demonstrated, or comes years later after successful litigation. Contrast with fields - like sales - where an unambiguous, universally agreed binary metric works - did you hit your revenue target?

This lack of clarity is apparent in a trend towards reduced investment in IP. In a report by Tradespace published in January, IP leaders reported budget cuts and hiring freezes, with some in-house counsel saying that IP teams were the first from the legal department to be diminished.

In parallel to this, the rate of technological innovation has been soaring, with patent volumes increasing and defending rights becoming ever more complex.

An AI-powered shift

Despite the historical difficulties in defining them, metrics have the potential to close the ‘persuasion gap’ and provide tangible evidence of IP’s worth. Armed with the right KPIs, IP practitioners can communicate the importance of their work to the C-suite, and secure the funding they really need to do their job.

On the operational side, KPIs can inform better business decisions, enabling IP leaders to ensure each step in an asset’s lifecycle, from disclosure review to maintenance payments, supports overall business goals.

Furthermore, KPIs can track employee engagement, such as the number of employees participating in IP training sessions, or provide insights into diversity, equity and inclusion across the inventor base.

These tools to communicate the value of IP are set to become more available than ever before with a new era of AI-powered KPIs for the industry.

AI is changing the way KPIs are tracked and reported on, unlocking new methods for companies to identify the purpose of their ideas. It can provide the data that has been lacking from KPIs for IP, allowing IP practitioners to be surer of their decisions, for example, by suggesting products or technologies to map new and existing patents against.

This real-time mapping of IP to products, technologies and competitors is already happening. AI also has the potential to be used in tracking claim quality, litigation risk, licensing scope and other metrics.

However, there will always be a human aspect to measuring and interpreting KPIs—for example, ‘claim quality’ is subjective. But AI can give IP teams more time to focus on these issues by helping automate other day-to-day administrative tasks such as docket management or disclosure intake—and therefore expanding their capacity.

Tracking performance throughout the lifecycle

With more capacity, and data, from AI tools, IP teams can incorporate KPIs at every stage of an IP asset’s lifecycle. From the seed of an idea, to multi-stakeholder licensing agreements, metrics can ensure every step is purposeful, and grounded in a company’s overall strategy.

However, not all KPIs will be relevant to a business and different companies will be focused on particular stages of this lifecycle, and may only care about certain categories of metrics—efficiency, engagement, or quality.

The following graphic outlines the four stages in the IP lifecycle and the different KPIs that could be used in each.

For example, at the ‘create’ stage—when ideas are formed—a company can use KPIs to measure how effectively it has fostered the conditions for innovation. It can also look at how much inventive activity there is per dollar spent on R&D.

The next stage in the lifecycle is the protection of the idea. At this point, a company could implement KPIs for tracking prosecution costs, allowance rate and claim survival. Another KPI is that of how engaged the inventor community is with the process of taking their ideas to patenting, useful for both measuring the output of innovation and the effectiveness of the IP team at soliciting inventor participation in the IP process.

Other businesses with well-established portfolios may be more focused on IP management. Within this category, KPIs can offer insights into the number of granted patents per technology, product, or revenue, how this aligns with what competitors are doing, and how aware employees are of the various assets.

The final stage of the IP lifecycle is commercialisation—which for some patent owners, will mean how to maximise licensing revenue. KPIs at this point can tell the board what the licensing process time is, the size of the licensing pipeline, and the number of inventor hours billed against the lifetime value of an asset and many other metrics that will resonate with business leaders.

Linking to strategy

By using these metrics, IP teams have a way of demonstrating the value of their work that goes far beyond ‘number of patents filed’. These KPIs can help distinguish the assets in a portfolio that are tuned in to a company’s business goals—rather than those that are just making up the numbers.

Investing in a new technology always has an element of risk. KPIs can assist with the decision-making process, providing insights into competitor activity, current IP landscape—and the red flags that suggest an innovation is doomed to fail. For example, according to recent reports, Apple axed its secretive ‘Titan’ electric car project after a decade of work and billions of dollars of investment, presumably after a number of factors indicated it was not going to succeed.

Continually mapping IP to overall strategy, and questioning the reason behind each asset, will result in a portfolio that is easier to manage and clearly adds value. AI will enable this process, by measuring KPIs and providing the data to make informed decisions, and also by automating day-to-day tasks to free up IP practitioners to focus on strategy.

Assessing the quality of IP doesn’t need to be done with an extensive, sophisticated set of metrics, and not all will be relevant to an individual company. Simply keeping track of which patents and disclosures map to which products or R&D initiatives is a great start on the path to making better decisions and convincing leadership to champion IP.

Marcia Chang is the Vice President of Client Success at Tradespace. She can be contacted at marcia@tradespace.io, or via a coffee virtual chat here.

Read the free to download Tradespace report IP Strategies for a New Era.