Grand theories try to explain everything, and frequently fail. Simple models try to explain one thing, and usually wind up being fairly useful as a result.
Simple models are what allow us to make sense of complex situations. Models help define categories that can be meaningful and perspectives that can be useful. They provide a way of structuring what we look at, how we evaluate and interpret what is going on, and figure out implications and options for moving forward.
The problem with simple models is that there are a lot of them. Some are more relevant, some are more practical, and some provide better guidance. As a consequence, there is more work that needs to be done in finding them, understanding them, assessing their relevance and making connections between them.
As I explained last week, models often overlap. They aren’t aware of each other, were not particularly designed to work together, don’t necessarily relate, and don’t provide a seamless view. One model may reveal a partial insight into a problem, while another model may illuminate a different aspect. It’s still our job to imagine and fill in the dark space in between, and invent, deduce or otherwise speculate on what is going on behind the scenes.
The challenge becomes where to find models, and how to build a meaningful and relevant inventory of them that we might leverage and apply. Doing so can be considered the work of a lifetime. I have been progressively identifying, adopting, adapting and discarding models throughout my career. Some I learned formally. Some I actively sought in response to a specific problem. The vast majority just showed up.
Models come in many flavours, sizes, shapes and colours. Many of them are incredibly simple, and a ridiculous number of them are some form of a two-by-two matrix. There is an enduring joke about consulting that no problem is so complex that it can’t be explained by a two-by-two matrix. While humorous, there is also a certain amount of truth in that statement. It helps to understand why.
When we are trying to make sense of a difficult or complex situation, the issue we most often encounter is figuring out the information we need to look for or the questions that we need to ask in order to be able to understand what is going on. Matrices are a way of sorting and sifting and spreading out the factors associated with a problem so that we can make sense of them.
Let’s deal with an easy scenario in order to explore this in more detail. Imagine you are responsible for a project, and the problem you are trying to solve is how to respond to all the things that might go wrong. You had a meeting with your team, and they generated a long list of problems, issues, risks and bogeymen just waiting to derail your work. So which of those do you focus on first?
When all you have is a long, undifferentiated list, you have no structure and no way of making sense of it. It’s easy for it all to look like a great, big, overwhelming mess. It would also be easy to leave a meeting like that with nothing more than the primal desire to crawl under your desk, curl into a foetal ball and inhale a bag of Doritos. There needs to be some way of sifting and sorting the problems in order to figure out what you most need to focus on. You need to be able to prioritize, and identify the risks that most matter and that are most urgent or important to address.
Right there, you’ve got the basis of a model to work with. We’re back to the Eisenhower matrix (so named courtesy of US president Dwight D. Eisenhower, who in a 1954 speech apparently quoted an unknown university president. The observation he made was, “I have two kinds of problems, the urgent and the important. The urgent are not important, and the important are never urgent). Taking this framework, you can rank your risks on a structure that defines “urgent” and “not urgent” against “important” and “not important.” That gives you one means of focussing attention: deal with the urgent and important now, the not-urgent but important soon, and the rest of them in the due course of time.
Of course, that’s not the only two-by-two matrix that you might consider here. You might also look at the risks themselves, and assess what is meaningful and relevant about them. You might think of risks in terms of how likely they are to happen, for example. You might also look at risks from the perspective of how significant a problem they would be if they were to occur. From here you can launch into a second possible two-by-two matrix. You can think of problems with a high level of probability versus those that are low; you can also evaluate whether there is a high or low impact if they were to actually occur.
What two-by-two matrices essentially do is take an amorphous and formless lump of circumstances and spread them out to give them meaning and structure. You can take your list of risks, for example, and using probability and impact get a level of priority that guides where you should focus attention. High probability and high impact? You’re going to want to find ways to make those go away. Low probability but high impact? Ideally, you would like to make those someone else’s problem. High probability but low impact events will benefit from addressing in a way that reduces the probability (we call that mitigation). Everything else, you are likely to deal with as it happens.
What I’ve defined above is a gross simplification (which is, if we’re honest, what models do best). Depending upon the circumstances, just dealing with high and low may not be sufficient. You could think about high, medium, and low, which would get you all the way to a three-by-three matrix (look at you being all innovative and bold). You could just score probability and impact ons a scale of one to ten, and then graph the results accordingly. The point is that you are spreading out different factors and circumstances in order to rank, order, structure and create meaning around a situation.
One of the incredibly freeing realizations in recognizing how a two-by-two matrix (or any other matrix you might apply) works is that you are not limited to using the dimensions that someone else has pre-defined. Sure, the Eisenhower matrix is well known and incredibly popular. And most people understand that thinking about risk in terms of probability and impact is a useful perspective. If those views are relevant, by all means adopt and use them. But don’t feel you have to be constrained by them.
The point of any matrix is that it is a way of sorting through and prioritizing options. If there isn’t a relevant model available to you, that is not to say that you can’t simply invent your own. Think of a situation where you are facilitating a meeting, and you are trying to guide the group through a problem solving exercise. You’ve brainstormed a list of options, but how do you make sense of them? In fact, let’s have some fun with this. Imagine you are the person walking in the room in that scene from Apollo 13, needing an air scrubber that doesn’t exist, and stating that “we need to build one of these, from all of this.”
How might you sort out the options? You might look at it from the perspective of “availability of resources” and “time to implement.” Priority is going to go to things you can do quickly with resources close to hand. You might also look at “ease of assembly” and “time to implement.” Or “robustness of solution” and “time to implement.” Or some combination of the above. What drives the evaluation is what is critical to evaluate right now.
Some two-by-two matrices have more thought behind them than others, of course. In assessing culture, for example, the Competing Values Framework developed by Kim Cameron and Robert Quinn contrasts whether the discipline of an organization veers towards control or flexibility, and whether its focus tends to be more internal or external. Combine those, and there is a great deal of nuance to be understood about how culture can be evaluated.
Similarly, if you want to understand organizational politics, there are a number of scenarios that you might work to explore. The Interest Grid developed by Joel DeLuca looks at the interests that are being served by any given political action. Where the interests of the individual are met at the expense of organizational interests, politics can be described as dysfunctional. Where the interests of the organization are served at the expense of the individual, the results are self-sacrificial. Not serving the interests of the organization or the individual is pointless and self-destructive. Only where the interests of the individual and the organization are met do you have functional politics.
That’s not the only means of assessing organizational politics, of course. A different and really interesting framework looks at the terrain of politics. It asks where political activity takes place (organizationally or individually) and what the source of power is (informal or formal). Different nuances get emphasized, and different insights emerge.
Not all models are two-by-two matrices, of course. And the world is a better place for it. Some are linear hierarchies. If you are trying to make sense of motivation, Maslow’s got your back with his hierarchy of needs. Tuckman would like to pretend that he understands team building with his forming-storming-norming-performing model. There are any number of five-level maturity models (I alone am responsible for several) that will let you make sense of your software development, project management or risk management practices (and that is a blatant simplification of the number of ways to think about maturity).
Models are everywhere. Most start as theory, sometimes formally developed and in other situations—probably more often than some would like to admit—informally conceived. We can find models in research papers and journal articles, and this is often where I initially encounter a framework. Books are another common source. Take some of the leading business books of the day, for example: The Balanced Scorecard, Blue Ocean Strategy, Business Model Generation, The Innovator’s Dilemma and Act Like A Leader, Think Like A Leader all have models lurking beneath them. Sometimes those models are obvious, and at other times they need to be teased out and given greater clarity. But underlying every single one of those books (and many, many more) is a model by which we can use to view, evaluate, analyze and make sense of the world around us.
Models show up with remarkable regularity. There’s a reason for that: they are incredibly useful in figuring out what is going on, what our available actions and options are, and how to prioritize and make sense of the moves that matter. Your challenge is to be open to models as you discover them. You need to evaluate and make sense of what they offer, decide whether and where they are relevant, and file them away in a manner that allows you to draw on them when they are required. There are no grand theories. There are lots of simple models. The game is not to collect them all, but to build a representative portfolio that makes sense for you.