Last year there was an interesting infographic floating around the office. Created by Scott Brinker of ChiefMartec, it showed how marketing technology platforms had proliferated over the previous six or so years. In 2011, there were about 150 platforms to choose from. By 2017, a marketer’s options had exploded to over 5,000. For me, this immediately resonated with Moore’s Law (more of an observation of a trend) that processing power would double every two years*. This observation is what is driving predictions of future capabilities such as AI, and we are seeing it playing out in the marketing landscape, too.
Brinker recently updated this graphic, showing the proliferation of platforms in 2018 and 2019. The graphic, formerly known as the Martec 5000 and now known as the Martec 7000, shows the number of platforms doubling and even tripling year on year over the last few years (2017 had 37 percent more platforms than 2016, for instance). However, the number only increased by three percent from 2018 to 2019. By Brinker’s own admission, this is likely because there are so many, he is having trouble actually including all of them in a single graphic, no matter how much time and how many people he commits to the task.
Brinker’s internal resource issue echoes that of businesses everywhere: While the number of platforms available to marketers is growing exponentially, that same phenomenon isn’t exactly occurring around the internal resources needed to manage them. Brinker dubbed the conundrum ‘Martec’s Law.’ As he puts it, “Technology changes exponentially, but organisations change logarithmically.”
This can often see businesses spending years trying to reach a point where their martech stack reaches some sort of ideal state, only to find that what they have finally implemented has been surpassed by something far more sophisticated. For the marketer on the ground, simply making calls on what platform (or combination of platforms) they should use to achieve a particular business objective can feel impossible.
At krunch.co, we aim to fill some of the gap between organisational capability and martech complexity. A lot of us spend time on the ground, in our client’s businesses getting to know their real world challenges, so that we can help steer them toward the right outcomes. While it’s nice to have this expertise extension, it does still come down to the client to make the calls on what to do.
In order to help navigate the ‘what to do when you don’t know what to do next’ inevitability, I often turn to the Cynefin framework. This allows us to take a systems approach to define what kind of situation we may be in, in order to determine the best course of action.
The Cynefin framework was created in 1999 by Dave Snowden at IBM Global Services
Often referred to as a ‘sense making device’, this quadrant allows us to compartmentalise an issue in order to know how best to proceed.
Simple systems are situations that we have come across before. For example, ‘if I add these ingredients and follow the method in this recipe, I’ll have a cake at the end’. It’s the factory line – if something breaks down, the whole thing grinds to a halt (see Chaos), but we know what to do to get it back up and running.
Complicated situations may need a little more input from an expert. Sometimes consultancies like us get pulled into these situations, but for the most part a few internal stakeholders should be able to solve the situation, make a plan and set the system in motion.
As things move to the complex, we see that we may need to do some experimenting. This, to me, is where agile methodology should predominantly exist, as you would likely need to run a few short experiments (sprints) in order to prove a theory and move forward toward your goals.
Chaos, I’m sure we can all agree, is not a great place to be. If things have become so complex that they are chaotic, the goal is to act as quickly as possible in order to settle things down. Interestingly, when a simple system breaks down, we can find ourselves immediately in a chaotic situation due to the automatic nature of simple systems.
This framework’s applications for decision making and problem solving in a complex world are endless and worth exploring. One of the key takeaways for me is that it helps me know when to put my hand up and ask for help. As a consultancy, we can add a lot of value to a client when things get into that complicated or complex segment. That is the time to bring experts in to add value. When things are chaotic or overly simplistic, consultancies like krunch.co can help there too, but the value is either simply filling resource gaps or mitigating risk as opposed to adding strategic, long term value – and that’s what we’re all about, really.
One final observation which should be welcome news, is that we may have already reached ‘peak martech’. Like Moore’s Law, growth cannot continue exponentially and many predict that processing power will slow in the 2020’s. Similarly, we may already be seeing the plethora of marketing platforms on offer begin to plateau. Like many aspects of the tech industry we simply need to be prepared to adjust to change as it comes our way. This is why a decision making framework such as the one I’ve described is a really helpful tool that allows us to rationalise challenges, know when to seek out help and when to act.
*actually, it was “the number of components per integrated circuit” that he observed doubling, but this rule has been translated and applied to a range of technologies, for example microchip pricing and pixels in digital cameras.
