Inquiry

Inquiry skills are crucial to developing a systems thinking mindset. The ability to interrogate a complex issue or item, and remain mindful of what we see enables real systems learning.

Critical Inquiry involves several types of actions and skills to be effective. The first crucial Inquiry skill is to be able to ask purposeful and constructive questions. This skill involves both an element of content and delivery. It is important to pursue questioning in a constructive manner as it could be perceived in a bad light.

Secondly, it is critical to gather and analyze information that is germane to the system. Developing the ability to sort key information and objectively is invaluable in systems analysis. The primary importance of inquiry in a systems thinking context, is the ability to interrogate and understand our own individual (or group) mental models and how they affect how we guide our thoughts and actions. An imperfect understanding of our own mental models will us to continue to take actions within a narrow channel, even when those actions are inadequate, inappropriate or do not yield the results we wish to obtain. In a previous post, we explored the difficulties associated with a Rational Model, or reductionist approach.

Another ability it is important to master is to balance our tendency to advocate our own perceptions and ideas, instead of inquiring to understand other perspectives and new or different information. Balancing inquiry and advocacy is a critical step in learning and understanding systemic issues. If we truly endeavor to obtain a systems perspective, it will very quickly become too complex and diverse than our own personal experience can adequately comprehend. Therefore, exercising our inquiry skills to comprehend new ideas and perspectives will be crucial in diagnosing what needs to be done, and in enlisting support to make it happen.

Simplicity vs Complexity

Simplicity versus complexity is one of the great paradoxes of modern life. Many of us are confronted with greater and greater levels of complexity as our horizons and access to knowledge expand. We are faced with questions of how we can embrace challenges without being simplistic. As we strive for more and better options, we produce proliferation and incrementalism instead of focus and wholeness. We capture more “benefits” but we don’t adequately account for the hidden costs that go undetected and unmanaged.

As we discussed in our last post about the Problems with the Rational Model , a reductionist approach will inevitably lead to more complexity, not simplicity. In many cases, complexity will lead to a loss of reliability or robustness. True systems thinking will seek to reverse this complexity by focusing an integrated whole and an umabiguous understanding of needs (priorities) and functions (outcomes). With adequate focus in these areas, we can gain much robustness in our approach to life and work. Robustness is a measure being strong and healthy in condition. When it is viewed in a system context, it refers to the ability of tolerating perturbations that might affect the system’s functional integrity.

Take a real world example from the airline industry. After deregulation of the US airlines in the late-1970’s and early-1980’s, the domestic carriers all analyzed and decided that a hub-and-spoke network would become the most efficient operating model. This was done primarily from a cost/revenue perspective, although other factors like customer access and reliability were probably analyzed, but likely not weighted heavily. This resulted in larger hubs developing around large cities. In addition several waves of domestic airline mergers have ensued in the intervening 40 years, resulting in yet fewer and larger hubs. These hubs have become extremely complex operations that are extremely sensitive to upsets that threaten a particular lines entire system (with ripple effects across the whole air travel system). Many of these hubs like Dallas-Ft. Worth, Chicago and Atlanta are subject to severe weather impacts which further reduces reliability and robustness. So now to travel from Huntsville, Alabama to Salt Lake City, one may need to be aware of the weather in Dallas or Chicago. It has also resulted in capacity issues in most major cities, and in many, single airline hegemony that is not the most effective to the traveler.

So do we just give in to complexity, or do we allow it to sneak up on us? In Overcomplicated complexity theorist Sam Arbesman gives two primary reasons of how complexity can be sneaky. “The first is accretion. We build systems, like the U.S. Constitution or the Internet, to perform a limited number of tasks. Yet to get those systems to scale, we need to build on top of them to expand their initial capabilities. As the system gets larger, it gets more complex. The second factor is interaction. We may love the simplicity of our iPhones, but we don't want to be restricted to its capabilities alone. So we increase its functionality by connecting it to millions of apps. Those apps, in turn, connect to each other as well as to other systems.” Boom! Complexity reigns and in many cases, the original purpose of these instruments is lost on the user.


So we need to find a way to reign in complexity, while focusing on what really matters. Unity in purpose has to carry more value than more and/or better. We need to shift our thinking to connecting to what really matters and managing the real “costs” of too much.

Decision Making Models

In our previous posts covering Mental Models I introduced the concept of two categories of mental models that are defaults in most people. The first was the Rational model. The rational model thinker is driven by a need to gather as much information as possible to understand their world and to make a decision. Rational thinkers are driven to gain as much information, data, insight and understanding of a situation BEFORE acting. In the most recent post I outlined some of the significant problems we can encounter in a system that is too rooted in the Rational Model. 

The second was what has been called Mixed-scanning. Those who ascribe to a mixed scanning approach willobtain enough information that they think allows them to make a good decision for the next step. They will then move forward and try to gain as much information, data, insight and understanding of a situation AS and AFTER acting. Subsequent decisions will then get made in light of these new conditions. 

In the Paradox of Choice, Barry Schwartz introduces the concept of two types of decision makers: maximizers and satisficers. Maximizers are rational model types who will agonize over every detail in fear that they will miss some ideal choice. Satisficers will figure out the minimum they feel they need to make a decision. Interestingly Schwartz’s research shows that satisfiers tend to be happier. I will note that there has been some backlash among the intellectual community to some of Schwartz’s findings. Some saying less is more, some saying more is more, some saying it depends. I think the key is in the level of uncertainty that one feels around the choices. If uncertainty of options is very low (e.g. if rational info gathering is “complete”), then the number of options is immaterial. However, if large uncertainty exists around choices, and sufficient information gathering is time consuming, impractical or impossible (or all three!) then the number of choices needs to be small. I contend that this how mixed-scanning works best. Understand enough to move forward with a critical next step (Observe and Orient from our OODA-loop example in Post Number 1), take that step (Decide and Act from OODA-loop) and then check, and redo it moving forward.

So to understand how we make crucial decisions to integrate our life and work, we need to get clear on our comfort zone for making those decisions. Then we need to be clear on the context of the decision, and realize we may need to act in the one that is outside our “normal” comfort zone. Ultimately if we’re going to focus and integrate the “system” of our lives, decision making will need to occur all the time, and at every level. The challenge is on us to decide and move forward. In fact, we may need to only decide on a few key critical next actions and then have the discipline to stop and think about where we go next.

Problems With the Rational Model

In our previous discussion of mental models, we talked about two types of models. In this post I want to divert and discuss some problems and limitations that come from applying the Rational Model approach. Many people, especially those with technical backgrounds, will equate systems thinking with a rational approach. 

In the seminal management book, In Search of Excellence,Thomas J. Peters and Robert H. Waterman Jr., found issues with the Rational Model when they studied the excellent companies. This was a particularly interesting part of the book to me (In Search of Excellence, Chapter 2). It was obviously important to them to devote an entire chapter to it’s limitations and fallacies. They uncovered what they summarized were several significant issues, all of which the excellent companies had learn to overcome; 

1. The numerate, analytical component has an in-built conservative bias. Cost reduction becomes priority number one and revenue enhancement takes a back seat.

2. The exclusively analytic approach leads to an abstract, heartless philosophy.

3. To be narrowly rational is often to be negative.

4. Rationality does not value experimentation and abhors mistakes.

5. Anti-experimentation leads inevidently to overcomplexity and inflexibility.

6. The rationalist approach does not celebrate informality.

I believe that there is a prevalence of this mentality afflicting our society today. The reductionist approach of the Rational Model leads to complexity by attempting to continue to break down issues into their constituent parts. This is meant to simplify, yet indeed it tends to introduce complexity. This has been driven in large part by our rapid march toward technological "progress". Our minds tend to want see the world as “fixed”, and want to reject randomness that exists in nature. We automatically want to place data "in it’s place”. Technology only feeds this feeling, or instinct, of a rational fixed pattern or product. As Peters and Waterman rightly observed, this can lead to complexity and inflexibility in our lives. It is also dangerous in that it can cause us to adopt a “heartless philosophy” toward the randomness (read messiness) that is real life. 

Another real danger of this is the loss of beauty. Complexity that is simply described is beauty. The celebration of form over style, function over utility, or more over enough, can lead us to crowd out our appreciation for the simple beauty of our messy world. In 2007, Gene Weingarten published an article in The Washington Postabout an accomplished violinist playing six classical pieces in the L’Enfant Metro station in Washington, DC during rush hour. Approximately 1,097 people passed by Joshua Bell, one of the finest classical musicians in the world while he played some masterpieces that have endured for centuries. This was a free performance of pure art, but very little was noticed or acknowledged by the passing crowd. Weingarten writes, “In the three-quarters of an hour that Joshua Bell played, seven people stopped what they were doing to hang around and take in the performance, at least for a minute. Twenty-seven gave money, most of them on the run -- for a total of $32 and change. That leaves the 1,070 people who hurried by, oblivious, many only three feet away, few even turning to look.” Many, if not most, of those passing by are well-educated, well-paid professionals associated in some way with the Federal Government. Yet, they did not bother to appreciate what they were passing by. Does this mean that beauty is not appreciated? Is it too hard to understand or is not relevant to our busy lives? If so, then indeed our priorities have been flipped on end, and how Rational is that really?

So if we can integrate our priorities around our life and work, we may depart from a Rational model view. A paradox is by being a little “irrational”, we can be whole.

Mental Models

Mental models are the way we see the world. Our brains develop models to make sense of the environment. Our mental models are a compilation of assumptions, our understanding of data and information and a way for us to take action. Mental models literally become neural pathways in our brain that shape how we naturally think, and form the foundation of our habits and actions. Over time, several big-picture concepts of models have been developed.

The first concept is the Rational model. The rational model thinker is driven by a need to gather as much information as possible to understand their world and to make a decision. Rational thinkers are driven to gain as much information, data, insight and understanding of a situation BEFORE acting. 

Some refer to a second model called by various terms such as muddling through or winging it. In my mind these are not really models, but more the absence of a model, or a lack of awareness. I really won't spend anymore time discussing this, as it is really not useful. 

The third way is what has been called Mixed-scanning. Those who ascribe to a mixed scanning approach will obtain enough information, context, advice, etc., that they think allows them to make a good decision for the next step. They will then move forward and try to gain as much information, data, insight and understanding of a situation AS and AFTER acting. Subsequent decisions will then get made in light of new conditions. 

If we want to obtain an integrated life, we need to learn to apply this third way thinking to our system. This model’s beauty and power comes in two forms. First it allows one to plan sufficiently and start taking action sooner. Second it allows us to be simultaneously deliberate and flexible. These are important qualities in making our life and work whole, to really use the Power in One.