Guest post: Improving patent analysis with big data
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Guest post: Improving patent analysis with big data

By Tyron Stading, senior vice president IP analytics and information solutions at CPA Global

Tyron Stading

Insight gained from big data analytics is driving business strategy in a range of global industries – from professional sports to the stock market. The internet has globalised every company and the IP landscape is becoming increasingly competitive. Organisations that create IP have a smaller window to ensure it is protected and exploited internationally. Big data tools and techniques can play an important role in this. IP departments can apply larger data sets and smarter analytics to drive value in the creation and protection of IP.

In January 2016, the Economist Intelligence Unit reported that 60% of the professionals surveyed believed that insight gained from big data was generating revenue within their organisation; 83% felt it was making existing products and services more profitable.

For organisations that create IP, big data analytics is enabled by three key factors: the availability of large and complex data sets, on-demand cloud computing power and artificial intelligence and machine learning, enabling organisations to process in minutes what would previously have taken months.

Combined, these technologies offer organisations predictive capability over the huge amount of data available to them, empowering deeper insight to be gained into both internal and external patent data.

Companies now have access to more than 100 million patents across 100 jurisdictions as well as 5 billion websites. This data can be fed in real time through powerful cloud computing technologies to offer actionable insight for businesses.

International IP portfolio management

During the patent lifecycle, organisations are faced with a number of business – rather than legal – patent decisions that can be improved with access to insight from big data. Questions over which patents to invest in, how much to invest, where future investment returns might occur, which areas are high or low risk or how to optimise an entire patent portfolio with limited resources can all be answered with far more internal and external visibility.

This can be particularly useful when faced with business constraints, whether it is time, headcount or financial resources. Analytics can be used to prioritise resources – showing which patents to review in detail – reducing overall review efforts and timeframe by more than 60%.  

By combining internal data on its most profitable patents with external data on new markets, an organisation can identify new opportunities for additional IP monetisation. Decisions about R&D investment, new patent filing, third party legal support and litigation strategy, as well as decisions about purchasing, licensing, renewing or selling patents, can also be enhanced.

Even if each individual decision is only slightly influenced by the analysis, the cumulative effect over time can significantly improve the investment value to an organisation of its overall patent portfolio.

Behavioural analysis

Eighty percent of IP budgets go to filing and prosecution, so the ability to minimise low profitability filing and increase higher probabilities can significantly maximise available resources. Predictive analysis has been used by retail businesses to predict shopper behaviour for some time, but the same principles can also be deployed within IP portfolios.

Data covering patent filers, litigants, legal agents, patent examiners and inventors can all be analysed and compared to provide a more accurate prediction of behaviour.

Behavioural analysis can reveal the likelihood of patent issuance during prosecution using factors such as the number of office actions, the identity of the examiner reviewing the application and the agent behind the application.

If the likelihood of issuance is low for a non-critical patent application after a certain point, this information could be used by the filer to abandon the application rather than continuing to invest. The aim is not to gain concrete answers, but to gain additional insight to enable better, more informed decision making.

It is called big data for a reason

Central to big data analysis is the size of the data sets being analysed. Analysing patents in aggregate and comparing them via big data algorithms and analytics requires all of the available information – and the computing power to process it.

While many organisations have a management system that tracks their own filings, few can offer insight into portfolio strength relative to competitor patents, or which patents will be most profitable to sell.

Big data analyses of patents in aggregate provides an additional layer of insight and guidance that is not possible to achieve through manual patent-by-patent analysis.

The huge data sets are available today, but gaining insight from its analysis may require new tools and skillsets for IP managers. Practitioners that are widening their own skill sets and utilising IP tools are harnessing new capabilities with the proprietary information and context their own organisation holds. This – above all else – will be essential to correctly interpreting the analysis results.

By selecting a partner that can provide optimised patent data, skills training and a collaborative approach, IP managers can provide successful portfolio analytics to significantly improve business decision making. 

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