In 2006 I was proud to be appointed to my first global role leading an Information Management team to market. The trouble was that in a crowded field, and regardless of budget, it was hard to apply enough funds to differentiate our capability.
Like so many businesses, we were convinced that our intellectual property (IP) was uniquely valuable. Unfortunately, a few client interviews revealed the reality that the world saw all IP in our field as being roughly equivalent. To differentiate we needed to do something disruptive, so we donated a large volume of material to “open source” via a Creative Commons licence. The story of the success of this initiative was subsequently told by Josh Bernoff and Charlene Li in their 2008 book Groundswell.
The body of work was called “MIKE2.0” and received numerous accolades before ultimately becoming part of DAMA’s respected DMBOK. By putting it into the open domain, we garnered a community, credibility and we levelled the playing field.
Behavioural economists have extensively researched why open business models sometimes work well whereas at other times exclusivity reigns supreme. One of the pioneers of the field is Dan Ariely whose highly regarded book, Predictably Irrational, explains that we tend to value things that we own more highly than the worth seen by those that we seek as buyers. This is particularly true when they have a “next best” alternative.
Ariely describes an experiment where he asked people to put a price on sporting tickets according to whether they were a buyer or a seller. The subjects of his experiment were college students who had all gone to some effort to procure seats to a particular basketball game. Given the limited stadium capacity many students missed out. All students equally wanted the tickets but after the final allocation, he tested the market and found an order of magnitude difference between the price those who wanted the tickets would pay and the price that those that had the tickets would sell. On questioning, the potential buyers had all moved onto their next best alternative (watching the game on television).
This is analogous to the way we generally value the IP that we’ve worked hard to create and are surprised when potential buyers don’t assign the same worth. In the case of methods, tools or software, if they are functional and not well understood by customers then they are unlikely to be seen as differentiated. The challenge becomes one of reducing friction to adopt the IP and finding other ways to monetise the relationship.
In another experiment, Ariely offers people two types of chocolates, a premium chocolate for fifteen cents or an ordinary chocolate for one cent. Given the trivial amount of money involved, most people opted for the premium chocolate. However, when he dropped the price of the ordinary chocolate by just one more cent to “free”, while also dropping the premium by the same amount, the vast majority went for the lower quality but free chocolate. This is because of the alure of “no regrets” – something I’ve written about before.
The entertainment industry knows all about this phenomenon. It’s why television in the twentieth century followed a “free to air” (or “no regrets”) model supported by advertising. But in later decades, they also discovered subscription models through cable TV.
Subscriptions add a little friction to the purchasing decision which can be mitigated by a free trial period and other incentives. It’s taken years for the software industry to catch-up to where television executives and studios have been since the introduction of cable. Now that they are there, there are more options than ever for their IP.
Most organisations and individual professionals spend a lot of effort promoting their expertise. Opening-up IP does this in spades by allowing contributors to “show rather than tell”. Rather than talk about what they’ve done, it is often better to provide evidence through contributions to their profession’s body of knowledge, software or other assets in shared IP.
At an organisational level this creates the opportunity to free-up IP to change a competitive dynamic. As the world absorbs the impact of Generative AI, there is a battle between the incumbent tech giants and an open source community. Unusually, the open source advocates sensed the opportunity to recruit one of the incumbents, Meta (the owner of Facebook), to their cause by asking them to release their “Llama” large language model to an open source license. The campaign was given the catchy title “Free the Llama”!
As much as Meta’s large language model is highly sought-after by developers, to the general public there is no understanding of the distinction of each model from its competitors. Arguably Meta is behind OpenAI after their unexpected release of ChatGPT, and with Google fast catching them with Bard, opening-up access to Llama is a highly disruptive move that, at the time of writing, is still to play out.
We may soon see the same battle in the automotive sector with many regarding Tesla’s data and AI capability as being as much a differentiator as their cars and batteries. With Tesla now having collected many years of data in an “automotive data cloud”, traditional and smaller new entrants might well see an open approach as levelling the field against Elon Musk.
Similarly, Amazon’s greatest strength is its data and IP managing the integration, speed and cost of end-to-end retail. As a mixture of traditional retailers and smaller digital rivals work to catch-up, they are likely to ask whether an open business model could help them beat the now well-established global behemoth.
In industry after industry, the same decision is playing out. Smart executives will be sure to seriously consider non-traditional, open, approaches to reposition against successful incumbents. The question for each business is whether each part of their organisation is established in their market with differentiated IP or a challenger who needs to shake things up.