5 Steps for Extracting IP-Driven Market Intelligence
At London’s Roundhouse venue in Camden, BMW is celebrating 100 years of the BMW brand with an immersive event, ‘BMW Group Future Exhibition.’ At this event, the company is displaying its vision for mobility for the next 100 years. And the Next 100 (pictured above) is one of the concept cars on display - a car that promotes some of BMW’s near-term, as well as long-term, future plans.
So, in our most recent white paper, we decided to take a look at innovation in one of the most exciting and rapidly evolving areas of future driving - the self-driving car - and to find out what market intelligence can be derived from looking at a range of IP in this space.
While the car sector is a high-octane area, with huge stakes and intense competition, we are all in a world of ever-accelerating innovation. It means we all need to get more detailed information about our markets by using every data point available, to help us build the best picture of the market landscape and competitive environment. Which leads us to the question – what can we learn from the automotive market about how to stay ahead in our own race? Here are five data points that we consider:
1. The lead car is absolutely unique, except for the one behind it, which is identical
One of motorsport commentator Murray Walker’s unforgettable lines! However, it is a phrase that rings true in the patent world. Often we find exactly the same technologies often being described in many different ways – and in ways that are commonly different from marketing terminology. Luckily, the first data point we take a look at - text clustering – is a perfect tool for helping us find the terms that are most relevant to the industry area we’re interested in. Text clusters look at the most frequent words that occur within a specific group of patents. So, starting with ‘self-drive,’ we find overlap with the term autonomous vehicle, which itself leads us to autonomous driving and, from there, on to driver assistance system – all terms that allow us to track down all of the usual suspects in the space. And, through this process, we also unearth some potentially surprising extras.
It’s worth making a note of each of the manufacturers found, their main technology focuses and how they refer to these technologies in a competitive matrix that helps to keep track of them.
2. Auto racing began 5 minutes after the second car was built
A quotation now from Henry Ford. Of course, competition in all walks of life is inevitable; it’s what we do about it that counts. One patent on its own can only really tell us about a single invention – but when you collect all the patents together, aggregate the information from those patents, and apply some interpretation, it’s then that you uncover huge amounts of market intelligence. You can find out, for example, which are the fastest growing technology areas. And, you can also see who has been quickest to react to new and emerging trends. As Jeremy Clarkson once said, ‘speed has never killed anyone, suddenly becoming stationary… that’s what gets you.’ Cue our second data point, volume of patents matching certain technology terms.
3. “He ran out of talent about halfway through the corner”
A classic comment here from Buddy Baker, the American NASCAR driver and sports commentator. And the sentiment translates into the area of innovation, a place where staying ahead of competitors means having exactly the right know-how, at all times. And if you don’t have it, then you need to consider how to get it. Fortunately, aggregated IP information can help with this aspect. We mentioned using text clustering to find market players in specific industry segments. Once we’ve identified the main players - and uncovered the lesser known suspects – it’s now possible to compare each manufacturer and the number of patents they have in various technology sectors (as designated by IPC code, for example). This information gives rise to our third data point – measuring technological footprints – and determining the tech areas in which R&D teams from different organizations have the biggest focus. As we find in the white paper, this analysis quickly reveals potential partners that are worth considering in terms of forming strong partnerships.
4. Born to perform
A strong partnership, of course, will be based upon a chosen partner’s ability to perform. Working out a score for ‘ability to perform,’ is a great way to benchmark both partners and the competition. Again, trends in IP provide an empirical method for measuring a potential partner’s performance against different criteria. Here are some examples of criteria that can be used: • Rate of innovation: This can be measured by looking at the total number of patents being filed. Are they in phase of speeding up or slowing down, from a growth perspective? • Quality of innovation: Are they filing patents that are being cited by others? A much-cited patent means it’s one that is influential. This is very difficult to measure from individual patents, but it becomes clear when all the patents in an area (such as autonomous cars) are taken together. • Diversification: how many patents sit in multi-technology classifications? • Openness to partnership: for example, how many co-patenting activities is an organization engaged in?
5. If everything seems under control, you’re not going fast enough
The final quotation is from Mario Andretti, former Italian American racing driver of the late-sixties and seventies. As far as innovation is concerned, this equates to venturing outside the comfort zone. Again, a couple of patents on their own will not necessarily reveal overlapping technologies. However, by finding and analysing all of the patents relating to technologies, then many other new avenues that are worth exploring will begin to emerge.
Circle charts, for example, use semantic indexing to provide a view of which terms are closely interrelated to each other within a group of patents. In the chart here, for example, we evaluated all the terms related to ‘connected cars.’ Some of these patents relate to connected cars in terms of train carriages, but the term is also used for cars that have WiFi connectivity – and it’s here that we can see how emerging 5G technology is playing an important role in terms of the overall ‘connected car’ landscape. 5G, of course, will be an important component of the smart city, within which the self-driving car will be one part of a much wider system based on the Internet of Things – a point which demonstrates that a high level of collaboration will be needed for future success in the automotive sector.
Winning is everything
So that’s our pick of five data points that use analysis from IP to show how to get ahead of the competition. To get more insight into how we evaluated the automotive market area, as well as a range of other ideas - and a comparison of how different auto vendors are approaching the market, the full white paper is available for download here.