In a previous post, we looked at some measures of patent attorney (or firm) success:

  • Low cost;
  • Minimal mistakes;
  • Timely actions; and
  • High legal success rate.

In this post, we will look at how we can measure these.


Legal Success 

Let’s start with legal success. For legal success rate we identified the following:

  • Case grants (with the caveat that the claims need to be of a good breadth);
  • Cases upheld on opposition (if defending);
  • Cases revoked on opposition (if opposing);
  • Oral hearings won; and
  • Court cases won.

When looking to measure these we come across the following problems:

  • It may be easy to obtain the grant of a severely limited patent claim (e.g. a long claim with many limiting features) but difficult to obtain the grant of a more valuable broader claim (e.g. a short claim with few limiting features).
  • Different technical fields may have different grant rates, e.g. a well-defined niche mechanical field may have higher grant rates than digital data processing fields (some “business method” areas have grant rates < 5 %).
  • Cases are often transferred between firms or in-house counsel. More difficult cases are normally assigned to outside counsel. A drafting attorney may not necessarily be a prosecuting attorney.
  • During opposition or an oral hearing, a claim set may be amended before the patent is maintained (e.g. based on newly cited art). Is this a “win”? Or a “loss”? If an opponent avoids infringement by forcing a limitation to a dependent claim, that may be a win. What if there are multiple opponents?
  • In court, certain claims may be held invalid, certain claims held infringed. How do you reconcile this with “wins” and “losses”?

One way to address some of the above problems is to use a heuristic that assigns a score based on a set of outcomes or outcome ranges. For example, we can categorise an outcome and assign each category of outcome a “success” score. To start this we can brainstorm possible outcomes of each legal event.

To deal with the problem of determining claim scope, we can start with crude proxies such as claim length. If claim length is measured as string length, (1 / claim_length) may be used as a scoring factor. As automated claim analysis develops this may be replaced or supplemented by claim feature or limiting phrase count.

Both these approaches could also be used together, e.g. outcomes may be categorised, assigned a score, then weighted by a measure of claim scope.

For example, in prosecution, we could have the following outcomes:

  • Application granted;
  • Application abandoned; and
  • Application refused.

Application refused is assigned the lowest or a negative score (e.g. -5). Abandoning an application is often a way to limit costs on cases that would be refused. However, applications may also be abandoned for strategic reasons. This category may be assigned the next lowest or a neutral score (e.g. 0). Getting an application granted is a “success” and so needs a positive score. It maybe weighted by claim breadth (e.g. constant / claim_length for shortest independent claim).

In opposition or contentious proceeding we need to know whether the attorney is working for, or against, the patent owner. One option maybe to set the sign of the score based on this information (e.g. a positive score for the patentee is a negative score for the opponent / challenger). Possible outcomes for opposition are:

  • Patent maintained (generally positive for patentee, and negative for opponent);
  • Patent refused (negative for patentee, positive for opponent).

A patent can be maintained with the claims as granted (a “good” result) or with amended claims (possibly good, possibly bad). As with prosecution we can capture this by weighting a score by the scope of the broadest maintained independent claim (e.g. claim_length_as_granted / claim_length_as_maintained).

Oral hearings (e.g. at the UK Intellectual Property Office or the European Patent Office) may be considered a “bonus” to a score or a separate metric, as any outcome would be taken into account by the above legal result.

For UK court cases, we again need to consider whether the attorney is working for or against the patentee. We could have the following outcomes:

  • Patent is valid (all claims or some claims);
  • Patent is invalid (all claims or some claims);
  • Patent is infringed (all claims or some claims);
  • Patent is not infringed (all claims or some claims);
  • Case is settled out of court.

Having a case that is settled out of court provides little information, it typically reflects a position that both sides have some ground. It is likely better for the patentee than having the patent found invalid but not as good as having a patent found to be valid and infringed. Similarly, it may be better for a claimant than a patent being found valid but not infringed, but worse than the patent being found invalid and not infringed.

One option to score to partial validity or infringement (e.g. some claims valid/invalid, some claims infringed/not infringed) is to determine a score for each claim individually. For example, dependent claims may be treated using the shallowest dependency – effectively considering a new independent claim comprising the features of the independent claim and the dependents. A final score may be computed by summing the individual scores.

So this could work as a framework to score legal success based on legal outcomes. Theses legal outcomes may be parsed based on patent register data, claim data and/or court reports. There is thus scope for automation.

We still haven’t dealt with the issues of case transfers or different technical fields. One way to do this is to normalise or further weigh scores developed based on the above framework.

For technical fields, scores could be normalised based on average legal outcomes or scores for given classification groupings. There is a question of whether this data exists (I think it does for US art units, it may be buried in an EP report somewhere, I don’t think it exists for the UK). A proxy normalisation could be used where data is not available (e.g. based on internal average firm or company grant rates) or based on other public data, such as public hearing results.

Transferred cases could be taken into account by weighting by: time case held / time since case filing.

Timely Actions

These may be measured by looking at the dates of event actions. These are often stored in patent firm record systems, or are available in patent register data.

It is worth noting that there are many factors outside the control of an individual attorney. For example, instructions may always be received near a deadline for a particular client, or a company may prefer to keep a patent pending by using all available extensions. The hope is that, as a first crude measure, these should average out over a range of applicants or cases.

For official responses, a score could be assigned based on the difference between the official due date  and the date the action was completed. This could be summed over all cases and normalised. This can be calculated from at least EP patent register data (and could possibly be scraped from UKIPO website data).

For internal timeliness, benchmarks could be set, and a negative score assigned based on deviations from these. Example benchmarks could be:

  • Acknowledgements / initial short responses sent with 1 working day of receipt;
  • Office actions reported with 5 working days of receipt;
  • Small tasks or non-substantive work (e.g. updating a document based on comments, replying to questions etc.) performed within 5 working days of receipt / instruction; and
  • Substantive office-action and drafting work (e.g. reviews / draft responses) performed within 4 weeks of instruction.

Minimal Mistakes

This could be measured, across a set of cases, as a function of:

  • a number of official communications issued to correct deviations;
  • a number of requests to correct deficiencies (for cases where no official communication was issued); and/or
  • a number of newly-raised objections (e.g. following the filing of amended claims or other documents).

This information could be obtained by parsing document management system names (to determine communication type / requests), from patent record systems, online registers and/or by parsing examination communications.

Low cost

One issue with cost is that it is often relative: a complex technology may take more time to analyse or a case with 50 claims will cost more to process than a case with 5. Also different companies may have different charging structures. Also costs of individual acts need to be taken in context – an patent office response may seem expensive in isolation, but if it allows grant of a broad claim, may be better than a series of responses charged at a lower amount.

One proxy for cost is time, especially in a billable hours system. An attorney that obtains the same result in a shorter time would be deemed a better attorney. They would either cost less (if charged by the hour) or be able to do more (if working on a fixed fee basis).

In my post on pricing patent work, we discussed methods for estimating the time needed to perform a task. This involved considering a function of claim number and length, as well as citation number and length. One option for evaluating cost is to calculate the ratio: actual_time_spent / predicted_time_spent and then sum this over all cases.

Another approach is to look at the average number of office actions issued in prosecution – a higher number would indicate a higher lifetime cost. This number could be normalised per classification grouping (e.g. to counter the fact that certain technologies tend to get more objections).

The time taken would need to be normalised by the legal success measures discussed above. Spending no time on any cases would typically lead to very high refusal rates, and so even though a time metric would be low, this would not be indicative of a good attorney. Similarly, doing twice the amount of work may lead to a (small?) increase in legal success but may not be practically affordable. It may be that metrics for legal success are divided by a time spent factor.

Patent billing or record systems often keep track of attorney time. This would be the first place to look for data extraction.

Final Thoughts

An interesting result of this delve into detail is we see that legal success and cost need to be evaluated together, but that these can be measured independently of timeliness and error, which in turn . may be measured independently of each other. Indeed, timeliness and error avoidance may be seen as baseline competences, where deviations are to be minimised.

It would also seem possible, in theory at least, to determine these measures of success automatically, some from public data sources and others from existing internal data. Those that can be determined from public data sources raise the tantalising (and scary for some?) possibility of comparing patent firm performance, measures may be grouped by firm or attorney. It is hard to think how a legal ranking based on actual legal performance (as opposed to an ability to wine and dine legal publishers) would be bad for those paying for legal services.

It is also worth raising the old caveat that measurements are not the underlying thing (in a Kantian mode). There are many reasonable arguments about the dangers of metrics, e.g. from the UK health, railways or school systems. These include:

  • the burden of measurement (e.g. added bureaucracy);
  • modifying behaviour to enhance the metrics (e.g. at the cost of that which is not measured or difficult to measure);
  • complex behaviour is difficult to measure, any measurement is a necessarily simplified snapshot of one aspect; and
  • misuse by those in power (e.g. to discriminate or as an excuse or to provide backing for a particular point of view).

These, and more, need to be borne in mind when designing the measures. However, I believe the value of relatively objective measurement in an industry that is far too subjective is worth the risk.

This is a question that has been on my mind for a while. The answer I normally get is: “well, you just kind of know don’t you?” This isn’t very useful for anyone. The alternative is: “it depends”. Again, not very useful. Can we think of any way to at least try to answer the question? (Even if the answer is not perfect.)

The question begets another: “how do we measure success?”


For a company this may be:

  • the broadest, strongest patent (or patent portfolio) obtained at the lowest cost;
  • a patent or patent portfolio that covers their current and future products, and that reduces their UK tax bill; and/or
  • a patent or patent portfolio that gets the company what it asks for in negotiations with third parties.

For an in-house attorney or patent department this may be:

  • meeting annual metrics, including coming in on budget;
  • a good reputation with the board of directors or the C-suite; and/or
  • no surprises.

For an inventor this may be:

  • minimum distruption to daily work;
  • respect from peers in the technology field; and/or
  • recognition (monetary or otherwise) for their hard work.

For a patent firm this may be:

  • a large profit;
  • high rankings in established legal publications; and/or
  • a good reputation with other patent firms and prospective or current clients.

For a partner of a patent firm this may be:

  • a large share of the profit divided by time spent in the office; and/or
  • a low blood pressure reading.

As we can see, metrics of success may vary between stakeholders. However, there do appear to be semi-universal themes:

  1. Low cost (good for a company, possibly bad for patent attorneys);
  2. Minimal mistakes (good for everyone);
  3. Timely actions (good for everyone but sometimes hard for everyone); and
  4. High legal success rate (good for everyone).

High legal success rate (4) may include high numbers of:

  • Case grants (with the caveat that the claims need to be of a good breadth);
  • Cases upheld on opposition (if defending);
  • Cases revoked on opposition (if opposing);
  • Oral hearings won; and
  • Court cases won.

I will investigate further how these can be measured in practice in a future post. I add the caveat that this is not an exhaustive list, however, rather than do nothing out of the fear of missing something, I feel it is better to do something, in full knowledge I have missed things but that these can be added on iteration.

Cost is interesting, because we see patent firms directly opposed to their clients. Their clients (i.e. companies) typically wish to minimise costs and patent firms wish to maximise profits, but patent firm profits are derived from client costs. For patent firms (as with normal companies), a client with a high profit margin is both an asset and a risk; the risk being that a patent firm of a similar caliber (e.g. with approximately equal metrics for 2-4 above) could pitch for work with a reduced (but still reasonable) profit margin. In real life there are barriers to switching firms, including the collective knowledge of the company, its products and portfolio, and social relationships and knowledge. However, everything has a price; if costs are too high and competing firms price this sunk knowledge into their charging, it is hard to reason against switching.

There is a flip side for patent firms. If they can maximise 2-4, they can rationalise higher charges; companies have a choice if they want to pay more for a firm that performs better.

On cost there is also a third option. If patent firms have comparative values for 2-4, and they wish to maintain a given profit margin, they can reduce costs through efficiencies. For most patent firms, costs are proportional to patent attorney time, reduce the time it takes to do a job and costs reduce. The question is then: how to reduce time spent on a matter while maintaining high quality, timeliness and success? This is where intelligence, automation and strategy can reap rewards.

In-house, the low cost aim still applies, wherein for a department cost may be measured in the number of patent attorneys that are needed or outside-counsel spend, as compared to a defined budget.

In private practice, and especially in the US, we often see an inverse of this measurement: a “good” patent attorney (from a patent firm perspective) is someone who maximises hourly billings, minimises write-downs, while anecdotally maintaining an adequate level for 2-4. One problem is maximising hourly billings often leads to compromise on at least 2 and 3; large volumes of work, long hours, and high stress are often not conducive to quality work. This is why I have an issue with hourly billing. A base line is that a profit per se is required, otherwise the business would not be successful. Further, a base line of profit can be set, e.g. allowing for a partner salary of X-times the most junior rate, an investment level of Y%, a bonus pool for extra work performed etc.. However, beyond that, the level of profit is a factor to maximise, subject to constraints, i.e. 1-4 above, where the constraints take priority. The best solution is to align profit with the constraints, such that maximising 1-4 maximises profit. That way everyone benefits. How we can do this will be the subject of a future post.

So, let’s return to our original question: what makes a good patent attorney?

From the above, we see it is a patent attorney that at least makes minimal mistakes, operates in a timely manner, has a high legal success rate and provides this at a low cost. In private practice, it is also a patent attorney that aligns profit with these measures.

I was lucky enough to attend a session with Debra Baker of Law Leaders Lab / GrowthPlay. One of the many good points raised by Debra was that we often need to ask ourselves: “why are we doing this?”

This follows on from the talks of Simon Sinek*.

It’s the kind of question that you answer in a covering letter for a job or in an interview. You often answer it when you have no experience of the job. You tend to forget the question more than a decade later.


So: why do I work as a patent attorney?

I love technology. Growing up my favourite possessions were a box of Lego, a BBC Micro, a cheap Bush walkman and my Casio calculator watch. In conversation I get excited about  machine learning and natural language processing. Blade Runner and Terminator 2 are my favourite films. I find the Promethean ability to breath life into inert matter fascinating. Working as a patent attorney means I am immersed in technology of all kinds every day.

I like helping inventors and innovative companies. As a patent attorney you get to work with some of the smartest, most creative engineers on the planet. You also work in the real commercial world, as opposed to the more artificial confines of academia.

I enjoy diving deep into new subject matter and linking it to existing understanding. I have a “systematic” mind, I enjoy figuring out what makes things work. As a kid, I devoured Encylopedias and practically slept with a copy of the Usborne Book of Knowledge. I studied hard, partly through sheer curiosity.  I always find how we know what we know fascinating. I may be the only one of my school and University peers who uses their subject knowledge everyday. Each new invention builds upon strata of past learning in a way that is deeply satisfying.

I like an intellectual challenge (the flip-side to being easily bored by the surface of things). I like wrestling an idea into language.

And the more quotidian reasons: I like being able to pay the bills; I like working in a place with free Nespresso and apples; I like having good colleagues and leadership.


Why you need the why

You need these reasons to keep going through the day-to-day work and the ups-and-downs of commercial reality.

For example:

  • Nine out of ten small businesses fail, typically despite great inventions and people.
  • Human contact is often lost beneath the required bureaucratic machinery of large organisations.
  • Cases can be granted or refused based solely on the luck of the examiner draw.
  • The gap between the hyperbole needed to sale a product and the prosaic hardwork to get the product working.
  • The size of the body of previously-published materials.
  • Cases you work on for years are left behind as companies pivot and cost-cut.
  • There’s always a deadline or five.
  • Every other patent attorney is just as driven and smart and is competing against you.

If you align why you are doing something with what you are doing then things become a lot easier.

* Caveat: I understand that this can seem a little MBA-gimmicky, and I do share your skepticism, but the underlying question is a sound one. Reflection is also a good thing, and needed now more than ever with the iPhone buzzing and blinking. 

[This is a somewhat reflective piece that only has a tangential relation to patent work. Feel free to ignore until more patent-centric posts come along. It may be of help for others considering different working patterns while looking after young children.]

I have been working part time since May as my partner and I share the childcare for our three children. I am now coming up to the three month mark. Here are my reflections on the experience.

I currently work Monday, Tuesday and Friday. Salary, holiday and other benefits are prorated on a three-fifths basis. On a Wednesday and Thursday I am responsible for the childcare while my partner works. The older two children will be in school from September, while the youngest is under one. Working part time is temporary, we will reassess our options when the demands of the youngest tail off a little.

Benefits

Before number three came along, I worked for a period full-time with the older two children in nursery. Compared to this arrangement there are a number of advantages in working part-time.

Work

Part time works leads to better supervisory work.

For example, I work with a number of pre and post-qualified associates, supervising and guiding their work. I can set up a task at the beginning of the week and then check this at the end of the week. Not being there makes me a better teacher and manager – I have to issue clear and concise guidance, and I am prevented from micromanaging. I also feel it improves the learning and initiative of our associates – they need to work out things for themselves and prepare materials for easy review and comprehension.

Days at work pass more rapidly – “flow” is easier.

As time is limited there is always something to do and no space for procrastination. The feeling that lunch or 5:30pm has crept up on me happens more often. This is also because I have more mental energy for work tasks, and I appreciate the silence and room to think after days of childcare.

Clients get a good deal.

Having more mental energy and less time for procrastination leads to high quality work for a higher proportion of the working week.

Home Life

More housework gets done.

Being home for two extra days means time for jobs such as tidying and washing. These jobs used to be relegated to the weekend when often we were too tired to spend much time doing them.

We eat better.

On the days when I am off I have time to whip up a batch of food in the slow cooker or do some baking. This saves us money and is healthier, especially compared to buying prepared food or ready meals. It means there is normally a batch of leftovers in the fridge. I also do the weekly shop on a Wednesday morning when it is relatively quiet.

I have more practice at parenting.

I am not the best parent in the world. I get angry. I have a relatively low tolerance for messing about. I do not plan amazing educational activities. However, by just being around, my bond with the children is improving. Anecdotally, I also think their behaviour, at least outside the home, is improving.

The children also benefit from having two different parents look after them. I think this makes them more robust and more open, as they are not tied to any one individual’s behavioural patterns. They also experience both a male and female perspective.

More equality, less resentment.

As we are both working (approximately) 50% of the time (60-40 for pedants), it becomes easier to share things like bills, housework and random expenses on the same basis. Hence, no one feels resentful at being the breadwinner/homemaker while the other party lives a life of Reilly as the homemaker/breadwinner. Decisions are also easier as no one plays a breadwinner/homemaker trump card.

General

More energy and motivation to live better.

Not sitting behind a desk for most of the week has health benefits. Looking after children definitely involves more physical exercise, so as a result I am healthier than I was working full time. Coupled with eating better, this results in more energy and motivation.

 
Disadvantages

Work

Career on hold.

Practically, going part-time has parked any available career progression until I return to my full-time position. This is a somewhat fair trade-off. There is not the (over) time to dedicate to career building and progression at the moment. However, I think this will become harder to bear as more of my contemporaries progress. It is noted that there are a lack of permanent options for part-time employees.

Weeks pass quickly.

When working your brain can often assume that you have a full week to get things done. This is not the case. Combined with the increased “flow” documented above, it is easy for time to fly by. This requires extra diligence and planning.

Missing seminar sessions.

For some reason, most continuing professional development sessions are scheduled for a Wednesday or Thursday. Watching a recorded session does not count as full session time.

Home Life

Constant vigilance.

Looking after young children full-time, four days a week means that attention comes in 30 second segments. Turn away for more than this and a four-year-old is balancing a totem pole on the baby’s head, or the baby is doing a stunt roll down the stairs, or someone is eating sequins. This can be mentally draining. A good couple of hours or relatively silent, contemplative time is needed to let my brain return to normal.

No time for side projects.

I have a number of web development, robotics and artificial intelligence ideas I enjoy playing around with (e.g. via Lego mindstorms, Flask projects, or Raspberry Pi GPI/O or machine vision test rigs). Although I would love to sit down and work on these during the days looking after the children, the reality is this is just not possible. Instead, discipline is needed to carve out 30mins before work or an hour before bed or on the weekend. This is hard to enact when you are tired.

Stuff That Works Both Ways

Finances

Although there is a three-fifths hit to gross income, this rather surprisingly does not equal a three-fifths hit to net income.

In the UK there is a progressive taxation of income, meaning that if you earn more you are often taxed at a higher rate. Also there are arbitrary single income cut-offs for benefits such as child benefit. Childcare costs have also risen at a much higher rate than income. For us this means that the amount we lose in income approximately equals the amount we would have to pay out in childcare. So we are about even overall.

Context

Mentally flipping between two very different environments can lead to cognitive dissonance. However, it can help in seeing more of the context both at home and at work, as neither completely takes over your life. For example, the differences between household and commercial accounts may be of orders of magnitude, but a frugal approach to home finances can help prevent profligate policies at work, and increase client value. Also the soap opera of company mergers, acquisitions and bankruptcies, and the lack of control in these situations, may be approached in the same stoic manner as a screaming toddler. In the end, the balance helps strip out some of the needless noise and concentrate on long term value.

One source of frustration with a time-based charging structure (“billable hours”) is that it is difficult to accurately estimate how long a piece of work will take. This post looks at ways we can address this. (Or at least puts down my thoughts on virtual paper .)

Many professional services are priced based on an hourly (or day) rate. This is true of private practice patent attorneys. Although there are critics, the persistence of the billable hour suggests it may be one of the least worst systems available.

Most day-to-day patent work in private practice consists of relatively small items of work. Here “small” means around £1k to £10k, as compared to the £1m cases or transactions of large law firms. These small items of work typically stretch over a few weeks or months.

When performing patent work an unforeseen issue or a overly long publication can easily derail a cost estimate. For example, it is relatively easy to find that a few more hours are needed after looking into an examiner objection or piece of prior art in more detail. This often presents a lose-lose situation for both attorney and client – the work needs to be done, so either the attorney has to cap their charges in line with an estimate or the client needs to pay above an estimate to complete the job. This is not just an issue for patent attorneys – try comparing any quote from a builder or plumber with the actual cost of the work.

This got me thinking about taxis. They have been around for a while, and recent services like Uber offer you a price on your phone that you then accept. This is a nice system for both customer and driver – the customer gets a set price and likewise the driver gets a fare proportional to her time. Could something like that work for patent work?

For taxi services, the underlying variable is miles (or kilometres depending on your Brexit stance). A cost is calculated by adding a mile-based rate to a basic charge, with minimum and cancellation charges.

For patent work, one underlying variable is words. Take an examination report (or “office action”). The amount of time it takes to respond to novelty and inventive step objections is typically proportional to the length of the patent specification in question, the number of claims and the number of prior art citations.

Now, we can use EPO OPS to retrieve the full text of a patent application, including  description and claims. We can also retrieve details of citations and their relevance to the patent application (e.g. category ‘X’, ‘Y’ or ‘A’). I am working on parsing PDF documents such as examination reports to extract the text therein. In any case, this information can be quickly entered from a 5 minute parse of an examination report.

Wikipedia also tells me that an average reading rate for learning or comprehension is around 150-200 words per minute.

This suggests that we can automate a time estimate based on:

  • Words in the description of a published patent application – WPA (based on a need to read the patent application);
  • Number of claims – NCPA (applications with 100s of claims take a lot longer to work on);
  • Words in the claims – WCPA (claims with more words are likely to take more time to understand);
  • For each relevant citations (category ‘X’ or ‘Y’ – this could be a long sparse vector) :
    • Words in the description of the citation – WCITx (as you need to read these to deal with novelty or inventive step objections); and
  • A base time estimate multiplied by the number of objections raised – BTo (possibly weighted by type):
    • E.g. x amount of time per clarity objection, y amount of time per novelty objection.

Even better we need not work out the relationship ourselves. We can create a numeric feature vector with the above information and let a machine learning system figure it out. This would work based on a database of stored invoicing data (where an actual time spent or time billed amount may be extracted to associate with the feature vector).

The result would be an automated system for pricing an examination report response based on publically available data. We could host this on Heroku. By doing this we have just created a marketplace for patent responses – a single weight could be used by patent firms to set their pricing.

Similar pricing models could also be applied to patent drafting. The cost of a draft may be estimated based on a set length, number of drawings, number of claims, number of independent claims, length of invention disclosure and length of known prior art. The variables for a response are similar for a European opposition or an appeal, just with different weights and expanded feature vectors to cover multiple parties.

This would yield a compromise between billable hours and fixed fees. For example, a variable yet fair fixed fee estimate may be generated automatically before the work is performed. The client gets predictability and consistency in pricing. The attorney gets paid in proportion to her efforts.

 

 

 

The European Patent Office has now published a case law summary for 2014 as Official Journal supplementary publication 4/2015. Sections I-C-4.1, I-C-5.1, II-A-1, and II-E-1.4 discuss case law that relates to computer-related inventions. The relevant passages are extracted and commented on below.

Skilled Person

T 407/11 held that the relevant skilled person in the context of providing computer-system users with operating assistance via a user interface (e.g. error messages or warnings) was an expert in software ergonomics concerned with the userfriendliness of human-machine interfaces rather than an expert in software programming or in computer technology in the strict sense.

The objective problem to be solved by that skilled person was to prevent a situation whereby the user’s action caused an electronic data-processing system to execute a called function differently from intended (or even to fail to execute it at all).

In the board’s view, however, the technical effect claimed in the application (simpler operation of an object-oriented user interface, facilitating initial use and subsequent familiarisation, especially for beginners or upgrading users, and so making the resulting method easier and more intuitive to learn) could not be considered a directly derivable consequence of the distinguishing features, because attributes such as “simpler operation” or “easy and intuitive familiarisation” were generally subjective, i.e. depended on the user’s individual preferences and experience or intellectual capabilities, while the classification of users as “beginners”, “upgraders” or “advanced” was generally based on a variety of criteria which were not clearly defined.

This suggests that providing objective definitions of technical effects (e.g. millisecond time savings) may help to support an inventive step under European practice. It also further indicates a need to avoid reference to “user”-based advantages.

Applications of Algorithms

In T 2035/11 the application mainly related to navigation systems that could be tailored to a user’s particular wishes. The focus of the application was on the route-planning functionality of a navigation system.

The board held that the subject-matter of claim 1 lacked an inventive step within the meaning of Art. 52(1) and 56 EPC. It noted that mathematical algorithms may contribute to the technical character of an invention only in so far as they serve a technical purpose (see e.g. decision T 1784/06). The purpose of the algorithm was the mere display of an optimal path to the user for cognitive processing. The user could act on the information, but did not need to.

As stated in decision T 1670/07, a technical effect may arise from either the provision of data about a technical process, regardless of the presence of the user or its subsequent use, or from the provision of data (including data that on its own is excluded, e.g. produced by means of an algorithm) that is applied directly in a technical process.

In the case at issue, the data was produced by means of an algorithm and was not applied directly in a technical process, so neither possibility applied.

Warning on Generalisation

In T 2231/09 the patent in suit concerned a method of representing and analysing images. Claim 1 of the main request set out that “… at least one said descriptor element is derived using only a subset of pixels in said image.”

The board considered the expression “subset of pixels” to be problematic under Art. 84 EPC 1973 and stressed that, while a certain degree of generalisation may be permitted, features as claimed should make it possible to clearly identify features of embodiments that are covered by the terms of a claim. Moreover, the generalised subject-matter as claimed should make it possible to understand the technical problem to be solved.

When amending claim 1, the applicant had put forward a new interpretation according to which a “region” could mean the whole image, and a “subset” could correspond to all pixels of the region. The board considered this interpretation to be inconsistent with essential parts of the described embodiments, according to which a subset corresponded to only some of the pixels of a region. The subject-matter of claim 1 was thus unclear when interpreted in the light of the description.

The board also stated that the requirements of clarity and support by the description in Art. 84 EPC 1973 were designed to reflect the principle that the terms of a claim should be commensurate with the invention’s technical contribution to the art. Taking into account the description, the board regarded the division of the image into regions and subsets as essential for achieving the technical effect underlying the invention. Therefore, the subject-matter of claim 1 was not supported by the description. The board concluded that claim 1 did not comply with Art. 84 EPC 1973.

This indicates the need, when drafting claims for computer-related inventions, to provide clear and unambiguous definitions of terms used within the claims. This is especially important when features of the claims relate to abstract entities, e.g. data within a data processing system.

Added Subject Matter and Features without Technical Contribution

In T 1779/09 the board considered that the appellant had found itself exactly in the situation envisaged in decision G 1/93 (OJ 1994, 451). As emphasised in Headnote II of G 1/93, “a feature which has not been disclosed in the application as filed but which has been added to the application during examination and which, without providing a technical contribution to the subject-matter of the claimed invention, merely limits the protection conferred by the patent as granted by excluding protection for part of the subject-matter of the claimed invention as covered by the application as filed, is not to be considered as subject-matter which extends beyond the content of the application as filed within the meaning of Art. 123(2) EPC.” These principles were confirmed in G 2/98 (OJ 2001, 413) and G 2/10 (OJ 2012, 376). The board in the case at issue concluded that a limiting feature which generally would not be allowable under Art. 123(2) EPC could, under certain conditions, nevertheless be maintained in the claim of an opposed patent in the particular situation addressed in decision G 1/93. It then complied with Art. 123(2) EPC by way of a legal fiction. In the case at issue, the term “only” was introduced during the examination proceedings and successfully objected to under Art. 100(c) EPC in proceedings before the opposition division by the former respondent. Since the board considered the term to be truly limiting, its deletion would extend the protection conferred and thereby infringe Art. 123(3) EPC. However, the board held that the exclusive limitation did not influence the solution of the technical problem as understood from the application as originally filed, and hence provided no technical contribution to the claimed invention (see also decision T 384/91, Headnote II). It merely excluded protection of part of the invention described in the application, thus not giving any unwarranted advantage to the applicant. Claim 1 of the appellant’s sole request was therefore deemed to comply with Art. 123(2) EPC.

The USPTO issued updated guidance on Patent Subject Matter Eligibility (i.e. things you can get a patent for in the US) at the end of July.

The materials are fairly dense and help address some of the criticisms raised by applicants. Further explanations of the approach are provided as well as an expanded list of examples.

Reading between the lines, it appears the USPTO is moving towards a position that is harmonised with European, Chinese and UK approaches on excluded subject matter.

Having a relatively simple mind, I found the following page from the guidance summary useful.

Stuff What You Can't Patent

One thing I have been trying to do recently is to connect together a variety of information sources. This has inevitably involved Python.

Estonian Snake Pipe by Diego Delso, Wikimedia Commons, License CC-BY-SA 3.0

Estonian Snake Pipe by Diego Delso, Wikimedia Commons, License CC-BY-SA 3.0

Due to the Windows-centric nature of business software, I have also needed to setup Python on a Windows machine. Although setting up Python is easy on a Linux machine it is a little more involved for Windows (understatement). Here is how I did it.

  • First, download and install one of the Python Windows installers from here. As I am using several older modules I like to work with version 2.7 (the latest release is 2.7.8).
  • Second, if connecting to a Microsoft SQL database, install the Python ODBC module. I downloaded the 32-bit version for Python 2.7 from here.
  • Third, I want to install IPython as I find a notebook is the best way to experiment. This is a little long-winded. Download the ez_install.py script as described and found here. I downloaded into my Python directory. Next run the script from the directory (e.g. python ez_setup.py). Then add the Python scripts directory to your Environmental Variables as per here. Then install IPython using the command: easy_install ipython[all].
  • Fourth, download a Windows installer for Numpy and Pandas from here. I downloaded the 32-bit versions for Python 2.7. Run the installers.

Doing this I can now run a iPython notebook (via the command: ipython notebook – this will open a browser window for your default browser). I found Pandas gave me an error on the initial import as dateutil was missing – this was fixed by running the command: easy_install python-dateutil.

Now the aim is to connect the European Patent Office’s databases of patent and legal information to internal SQL databases and possibly external web-services such as the DueDil API

 

 

If you are looking for some data to help with marketing efforts Google Trends can be useful.

http://www.google.co.uk/trends/explore

For example, you can play with terms to work out areas of rising interest and direct blog posts and tweets in that direction. It can also provide a guide to the terms non-professionals use.

For example, I work in intellectual property. In this field talking about “protecting ideas” would likely get you more interest/exposure than talking about protecting “innovations” or “inventions” or “patents” specifically.

IMG_0179.PNG

Similarly, talking about “Brands” would likely get you more interest/exposure than talking about “Trademarks”.

IMG_0178.PNG

Have a play and let me know if you come up with any interesting insights.

Case:

O/174/14

Claimed Subject Matter:

The alleged invention relates to a computer system and method for executing a point of sale transaction. In particular, the invention provides a point of sale terminal which is capable of receiving first price data from at least one item purchased by a customer and a server which receives both transaction data from the point of sale terminal and second price data pertaining to comparable competitor items from an update server so that the first and second price data can be compared and a voucher issued based on the comparison.

[This appears to be a patent application directed to Sainsbury’s Brand Match feature.]

Comments:

The Hearing Officer found that the actual contribution of the invention related entirely to a method of doing business which, as it was brought about by a computer program, also related to a computer program, as such. The invention was therefore excluded by section 1(2) and the application was refused.

Section 22 shows the risk of using an argument that is not present in the specification; the Hearing Office was sceptical of an argument based around quality control / self-checking that appeared to have little basis in the application as filed. As we have seen with many Europe cases, basing an argument on advantages not described in the patent application rarely succeed.

The Applicant attempted to argue that a technical contribution lay in “the overall architecture of  the computer system with technical components which in themselves are known but connected in a different way” . However, on applying step 3 of the Aerotel/Macrossan test the Hearing Officer was firmly of the view that “the actual contribution relates entirely to a way of conducting business” (see 27). This is because the actual contribution was deemed to be “about: (i) comparing prices, which manifestly is a business issue, and (ii) issuing a voucher with “value” information on it, which is also wholly a business issue”.

Section 29 has useful comments on whether the computer program exclusion is avoided. It was argued that “it is the connectivity of the components of hardware that creates the overall architecture of the invention” and that the computer program “lies in the middle of the system” but does not make up the whole system. This was found to be initially persuasive. However, the Hearing Officer concluded that the ” connectivity is necessarily brought about by a computer program” and that therefore lies “entirely in the programming itself”.

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