As we continue to unpack the 6 traits of Adaptive Organizations, let’s take a closer look at Trait #2: How Decisions Are Made.
Adaptive Organizations are aware that the world is ever-changing. To make more dynamic, effective adjustments, they make investments to validate assumptions both internally and externally to ensure that they capture and synthesize the best data. Distributed points of decision-making enable them to capture relevant context.
If 2020 taught us anything, it’s that the world can change overnight. But even before this year, change was constant on both the micro and macro levels. While the House of Resiliency places the trait of change under Systems, it impacts all House of Resiliency characteristics—Culture, Customers AND Systems—and understanding the inevitability of change is the foundation of how Adaptive Organizations make decisions.
Let’s look at some decision-making characteristics of decision-making Systems in the House of Resiliency.
The House of Resiliency organizes traits at three levels: Rigid, Flexible and Resilient. Organizations with traits at the Resilient level have achieved full business agility and adaptability, are typically able to weather threats, and can often turn threats into opportunities.
However, it’s not always feasible to be agile and Resilient in all traits—especially for some verticals (such as manufacturing) or highly-regulated businesses (such as pharmaceutical). But does that mean these organizations can’t be Adaptive? Not at all. While the Rigid and Flexible levels aren’t necessarily inappropriate, they do have consequences for organizations. Understanding these consequences and preparing for them helps organizations work within the constraints of their business model—and still achieve agility and adaptability.
What follows are some decision-making characteristics of non-Resilient organizations. As you read them, I recommend that you ask yourself, “Do I recognize any of these symptoms in my own environment?”
If your organization is based on decisions made at the top, it’s likely you’re in the Rigid level of the House of Resiliency.
Expectation that the system is predictable, and that we just need to find the proper “laws” to be able to foresee the future. Limited point of decision-making (who knows “the law”). Organizations that are Rigid in their decision-making Systems have a single point of decision-making, which manifests itself in negative ways. One such manifestation is increased time for making critical decisions because the boss is flooded with decisions to make.
Another negative manifestation of top-down decision-making is that change and disruption are more likely to result in pushback (likely passive) from those lower in the organization. Due to a lack of advanced consensus, large initiatives seldom live up to their potential.
Another negative manifestation of top-down decision-making is that change and disruption are more likely to result in pushback (likely passive) from those lower in the organization.
However, one benefit is that the organization has a single expert, and if you’re in a highly regulated environment, having an expert as a gatekeeper is a good way to protect your organization.
If your organization is Rigid for a valid reason, you can move up to Flexible and still maintain needed checkpoints for regulation and/or process optimization. For instance, letting someone other than the boss make less sensitive decisions can alleviate the consequences of being Rigid and move your organization into the Flexible level of decision-making Systems.
An organization with Flexible decision-making Systems has the expectation that the world is a mix of static and flexible rules. Organizations in this level of the House of Resiliency make investments in improving collaboration as well as gathering and understanding data to make better decisions. They may have a single point of decision-making (which still poses risks), but that single point has access to more feedback and data.
Expectations of How the World Works
Organizations with a Rigid outlook on the world believe that the system is predictable and they simply need to figure out the appropriate “laws” to succeed. To picture this, think about how we work our way through a jigsaw puzzle—looking for pieces that fit the gaps. This belief typically manifests itself in decisions made by a single point that knows and understands the “laws.”
One of the biggest risks of this kind of decision-making is that there are rarely static laws for anything— especially in business. Even in manufacturing, where we typically find this Rigid way of decision-making— change is constantly happening, and not being able to take advantage of changes and opportunities makes it more difficult to compete.
One of the biggest risks of this kind of decision-making is that there are rarely static laws for anything— especially in business.
An example of this is computer scientist Carlos Gershenson’s solution for Mexico City’s traffic problems. Check out the interview here, but here is a brief excerpt:
Q: Tell me about this project you’ve had with traffic lights in Mexico City to speed up commutes and reduce emissions.
A: Traffic-light systems are normally timed and programmed in a way that’s supposed to be efficient, but then the precise number of cars stopped by each traffic light varies constantly. Even if you’re basing it on a traffic measurement that it’s around 13 cars per minute on average, one minute there will be 20, and another there will be zero, and another there will be six.
Coordinating all these programmed traffic lights to keep vehicles moving is a problem. It gets more and more computationally demanding as you have more intersections to coordinate, and it changes as you add and subtract cars. It’s impossible to predict.
Q: And you want to optimize the flow of traffic.
A: Yes, but since optimization is so computationally demanding, you need to use adaptation.
Self-organizing traffic lights have sensors that let them respond to incoming traffic by modifying the timing of the signals. They are not trying to predict; they are constantly adapting to the changing traffic flow. But if you can adapt to the precise demand, then there is no idling. The only reason for cars to wait is because other cars are crossing.
The traffic light tells the cars what to do. But because of the sensors, the cars tell the traffic lights what to do, too. There’s this feedback that promotes the formation of platoons, because it’s easier to coordinate ten 10-car platoons than 100 cars, each with its own trajectory.
By being flexible and understanding that the rules are going to change, Mexico City solved problems that had troubled its drivers for decades.
Adaptive Organizations, which are agile and Resilient in decision-making Systems, understand that the world is ever-changing. To make more dynamic, effective adjustments, they make investments to validate assumptions both internally and externally to ensure that they capture and synthesize the best data.
Rather than a single point of decision-making, Resilient organizations have distributed points of decision-making that enable capturing the relevant context for all decisions that need to be made. This results in the best decisions possible at the time based on the information they have—but with the understanding that things may need to shift to accommodate new information at a later date.
Does this mean clear decisions are impossible for a Resilient decision-making System? Hardly. Over time Adaptive Organizations use data, feedback and their decision-making environments to not only drive awareness of changes, but also to know whether to adjust decisions based on incoming changes.
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