Here at Ambercite we believe in the value of patent citation data to predict patent quality, but would not claim that this ability stretches to predicting Olympic medal counts.
In any case, there are a number of other analysts that are attempting to predict Olympic medal counts, see the excellent graphics found here. In this graphic, the predicted medal count for the US ranged from 82 (USA Today) to 113 (Price Waterhouse Coopers). These different groups in use a range of formulas are used, as discussed by The Economist.
But who will be the best analyst?
While avoiding the risk of trying to predict medal counts ourselves, Ambercite might go out on a limb and make one prediction - that the average of the predicted values may be better, or similar to, the best of the individual predictions. This is based on the principle of collective wisdom, where the predictive ability of experts and non-experts alike can be improved by collecting a range of independent opinions and then averaging these opinions. While each opinion may be flawed in itself, the errors in each opinion is likely to be randomly distributed and an average of these opinions may be close to the truth.
So what has this got to do with patent analysis? Network Patent Analysis (NPA) is a method of ranking patent quality based on the citations connections of the patent to other patents around it, being forward and backward citaitons (and the forward and backward citations of the connected patents, and so on and so forth). Patent citations are not randomly or computer assigned, and instead each citation is an opinion that two patents are similar in some way. While individual citation opinions can be imperfect like any other individual opinion, if we collect enough of them the result should give us a very meaningful result.
NPA can be contrasted with other approaches. These typically tend to be:
- either a count of the forward citations from individual patents, which is only accessing part of the available citation data in an area of technology and so missing a lot o potentially valuable information.
- combining these forward citation counts with what I have called 'prosecution measures' such as the number of family members for the patent, and whether the these patents have been renewed or not. This thinking behind this is is that prosecution measures reflect the value that the patent owner places on their patents.
The limitation of using prosecution measures is that they are based on the opinion of one person, namely the patent owner (or the IP manager within the patent owner). These patent owners are likely to be very careful, objective and relatively well informed in the decisions they make. On the other hand, they are just one opinion, and an opinion that may be influenced by other factors besides the quality of the patent, such as budget presssures, and imperfect information about the likely success of the protected invention. For example, consider the management of the same possibly valuable patent by a) a manager in a well-resourced and very profitable company and b) a smaller university. These two different types of owners are likely to use different management strategies, and for good reasons. These different approaches in turn would mean that a analyst using a prosecution type measure might draw very different conclusions about the same patent.
This is why we prefer network based measures such as NPA. The management of the patent will have an impact on the network, in particular the decision to filing similar family members. On other hand, NPA will look at a range of other opinions besides those of the patent owner, leading to a more rounded final assessment of the quality and influence of the patent.
Interested in a robust and independent opinion of the quality of a group of patents of commercial interest to you? Please contact us for further information.