Patent landscaping is becoming an increasingly important tool to extracting the wealth of information from the 80 odd million patent publications, with it potential to show the leading areas of activity, patent owners and patents. However when talking to clients, it is becoming clear that these clients want to know more than what is hot - they also want to know what is not - not yet, that is. In other words, clients want to know where the white spaces are that will give them an opportunity to create new IP ahead of their competitors.
Or in the words of an experienced US patent analyst we are in contact with:
One KEY disadvantage, and in fact limitation that I see in landscapes is the fact that other than providing visual cues where “hot spots” or islands of research are located (and by extension researchers themselves) there is very little insight as to the connections between those hot spots or islands.
…a map showing every contour line does not tell you the entire story, or the best route to a destination. This is true if you are trying to find new paths between two locations on the map.
Luckily, our long standing tool for patent landscaping, Network Patent Analysis (NPA) can help with white space analysis as we will show below with a case study in the smartphone space.
Long terms readers of our blogs will know that NPA differs from other available patent landscaping tools. One of the most important parts of patent landscaping is 'clustering' or grouping patents similar patents together. Other patent landscaping tools tend to do this in one of two ways
- By grouping patents based on keywords. However experienced searchers will quickly recognise that a given keyword (for example 'phone') can cover a broad range of patents, and yet highly relevant patents can easily be missed: 'A handheld computer device'
- By grouping patents based on patent codes. Again a given patent code, whether the older US patent or IPC patent, or the new CPC patent codes can both include a lot of irrelevant patents while missing highly relevant patents.
At Ambercite, we believe that humans are much better at recognizing similarity between patents than computers. More specifically, we rely on the tens of millions of available patent citations, each of which is a record of similarity. But we do more than than that, we then apply advanced algorithms to weight these citation links so that we can tell the most similar patents. This provides a very precise means of grouping patents, more more precise than available with keywords or patent codes (think of how precisely patent examiner can review what can be hundreds of candidate prior art patents to identify the closest X citation prior art patents)
Other algorithms then allow more just grouping patents, as we can also rank individual patents, which in turn allows us to rank patent owners, not just overall but on a technology by technology basis. For these reason, it is not surprising that this combination of:
- much greater precision than available with other patent landscaping methods.
- an ability to group and rank patents at the some time
has attracted worldwide interest in the NPA. But moving back to the main topic of this blog, how can NPA identify the white spaces in an area of technology?
To answer, we will return to a very popular earlier published NPA patent landscape study on the smartphone 'patent wars', originally published in 2011. Although over two years old, this publication and its accompanying patent landscape map (the zoom function in your pdf reader can provide extra detail of this patent landscape map) provide an excellent example of what is possible using NPA, for example showing that:
- the major areas of smartphone patent litigation were in the areas of mobile data access, touch screen technology, and mobile data transmission, as shown below (with 13 other clusters also identified).
- Apple had a very strong position in touchscreen patents, while Interdigital and Qualcomm had strong position in mobile data transmission:
- Research In Motion (now Blackberry) is the leading patent owner in the mobile data cluster, ahead of Microsoft and Palm (now HP), as shown below.
What should also be obvious from these maps is that there is a lot of 'white space' between these clusters. When we consider the mobile data access' cluster shown above, it appears that this cluster could be also regarded as two sub-clusters (consider the question: 'Is Wall Street in Manhattan or New York?' Of course 'both' is the answer).
For the rest of this blog, we will regard the 'mobile data access' cluster as comprising two sub-clusters (in the same way New York includes the suburbs Manhattan and Brooklyn), even if these two sub-clusters are well connected. The common subject matter of these two sub-clusters can be surmised by a review of some of the leading patents in the left hand and right hand clusters:
So, not surprisingly, the subject matter of the two sub-clusters were different, but both fell under the general theme of 'mobile data access'. It should be noted that the three patents in the right hand cluster were not targeted toward hand held devices, instead being targeted toward general computer networks, for example as disclosed by US6023708:
This invention relates generally to computer networks, and more particularly to a system and method for using a global translator to synchronize workspace elements such as files across a computer network.
But what about the patents in the middle of these two sub-clusters? Many would regard this spaces between these two clusters as white space. But if you consider some of the maps shown above (in particular the last map) you will see that even in the white spaces between the major clusters, there are almost always patents found. In other words, just like vacuums even in space, white spaces are never truly empty.
We tend to regard the patents found in these white space patents as 'broker patents' because they help to connect technology clusters. But regardless of what you call them, these patents can be very valuable as they provide information about just what the white space opportunities might be - and how a company wanting to file patents in these white spaces could exploit these opportunities.
So what are these white space patents sitting between the two sub-clusters? If we look at the space again, I have selected a couple of the larger patents that sit within this white space.
So why do these patents act to broker these clusters together?
A) US5974238 (1996) - Automatic data synchronization between a handheld and a host computer using pseudo cache including tags and logical data elements - was originally filed by Compaq, discloses:
An apparatus ... for performing dynamic synchronization between data stored in a handheld computer and a host computer,
Which you would expect to fit about midway between the left and right sub-clusters shown above.
B) US6101531 (1998) - System for communicating user-selected criteria filter prepared at wireless client to communication server for filtering data transferred from host to said wireless client - was originally filed by Motorola, and discloses:
prestage filtering is applied via user-definable filter parameters (e.g., reject, pass, or granularity filters) on data being transferred between a communication unit (201) and communication server (220) ..This system is configured to support one or more user devices such as wireless subscriber units
Again, this patent appears to be sitting in about the right position in the patent network. While being predominately linked to data synchronisation, it also refers to handheld devices and so is positioned a little away from the 'data synchronisation to remote platforms' sub-cluster and towards the 'smartphone data entry' cluster.
Applications of white space analysis
This case study has shown what is possible with white space analysis using NPA, once we accept that white space is not in fact as empty as we might think. Applications for white space analysis include product development, IP strategic planning, and targeting of patent acquisitions. NPA is particularly suited for white space analysis because grouping by citation analysis gives greater precision than it possible when grouping patents by keywords or patent codes.
To discuss how white space analysis can be applied in your area of business, please contact us to discuss our NPA service offering.
How do other analysts do it?
It should be noted that this approach differs from the approach used by other patent analyts. These analysts tend to:
- Build a patent landscape using a grouping method other than the very precise citation based grouping that NPA uses
- Try to identify white space by the absence of patents in certain spaces, i.e. in relation to specific keywords or patent codes
In contrast, our NPA approach tends to positively identifies white space technologies by identifying broker (white space) patents siting between patent clusters - hence the title of this blog Positively identifying white space opportunities
PS - what if there are few white space (broker) patents?
Back in April 2012 we reported on an NPA study on patents for Alzheimer's treatments, and in particular how this patent landscape seemed to contain fewer broker patents than normal. At the same time, clinical results from a then highly rated prospect for the treatment of Alzheimer's disease was suggesting that the clear gaps between the various patent clusters may not be justified in practice - in other words treatments for Alzheimer's may show more potential cross-over between these clusters than patent applicants realized. Or as we wrote at the time:
The take home lesson from this is that such clear white space in an NPA landscape should raise the question - what opportunities for new technologies that cross over this white space are going begging?
This is another reason for reviewing your patent landscape of interest carefully for broker patents - because a relative lack of broker patents between dense clusters of patents may signal a commercial opportunity.