Bias

There are many forms of bias that we must be cognizant during problem solving and decision making.

That chart can be a little daunting. I’m just going to mention three of the more common biases.

  • Attribution bias: When we do something well, we tend to think it’s because of our own merit. When we do something poorly, we tend to believe it was due to external factors (e.g. other people’s actions). When it comes to other people, we tend to think the opposite – if they did something well, we consider them lucky, and if they did something poorly, we tend to think it’s due to their personality or lack of skills.
  • Confirmation bias: The tendency to seek out evidence that supports decisions and positions we’ve already embraced – regardless of whether the information is true – and putting less weight on facts that contradict them.
  • Hindsight bias: The tendency to believe an event was predictable or preventable when looking at the sequence of events in hindsight. This can result in oversimplification of cause and effect and an exaggerated view that a person involved with an event could’ve prevented it. They didn’t know the outcome like you do now and likely couldn’t have predicted it with the information available at the time.

A few ways to address our biases include:

  • Bouncing ideas off of others, especially those not involved in the discussion or decision.
  • Surround yourself with a diverse group of people and do not be afraid to consider dissenting views. Actively listen.
  • Imagine yourself in other’s shoes.
  • Be mindful of your internal environment. If you’re struggling with a decision, take a moment to breathe. Don’t make decisions tired, hungry or stressed.
  • Consider who is impacted by your decision (or lack of decision). Sometimes, looking at how others will be impacted by a given decision will help to clarify the decision for you.

The advantage of focusing on decision quality is that we have a process that allows us to ensure we are doing the right things consistently. By building mindfulness we can strive for good decisions, reducing subjectivity and effective problem-solving.

Yes…but…and

We have all had the first rule of brainstorming, “defer judgment,” drilled into us for years. The general rule of “When a person proposes an idea, don’t say, ‘Yes, but…’ to point out flaws in the idea; instead, say, ‘Yes, and…’” which is intended to get people to add to the original idea, has become almost a norm in business settings. We have all become improv actors.

That truism is probably not a good one though. It can lend to a fairly superficial approach. Yes we need to be beyond “Yes, but”, but “Yes, and” stifles creativity. The concept of “Yes, and” gives an illusion of moving forward, avoiding conflict, but also prevents truly diving in and exploring issues.

We need to combine the best aspects of criticism and ideation, “Yes…but…and.” I propose idea A, a colleague first addresses what she perceives to be a flaw in it, provides constructive feedback (this is the “but”), and then suggests a possible way to overcome or avoid the flaw, yielding Idea B (this is the “and”). Then you do the same: You acknowledge Idea B, provide a constructive critique, and develop a new, even more improved result. Others can jump in with their critiques and proposals during the process. This kind of constructive interaction encourages a deep cycle of critical dialogues that can lead to a coherent, breakthrough idea.

Here are some things to keep in mind:

  • When you see a weakness in the idea, don’t simply say, “This does not work.” Rather, first explain the problem and then propose an improvement that would make it work.
  • When you do not understand the idea, don’t simply say, “That’s unclear to me.” Instead, first point to the specific spot that is unclear and then propose possible alternative interpretations: “Do you mean X or Y?” This helps all participants to see more detailed options
  • When you like the idea, do not just take it as it is. Instead, search for possible improvements and then push forward to make it even better.
  • When you listen to someone’s critique of your idea,try to learn from it. Listen carefully to the critique, be curious, and wonder, “Why is my colleague suggesting this contrasting view that is not in line with what I see? Perhaps there is an even more powerful idea hidden behind our two perspectives.” The critique becomes a positive force, focusing the team on overcoming its weaknesses and enhancing the original idea.

Good decisions require creativity. But flexing our practices we can drive that in our interactions.

Decision Quality helps overcome bad outcomes

We gather for a meeting, usually around a table, place our collective attention on the problem, and let, most likely let our automatic processes take over. But, all too often, this turns out to be a mistake. From this stems poor meetings, bad decisions, and a general feeling of malaise that we are wasting time.

Problem-solving has stages, it is a process, and in order for groups to collaborate effectively and avoid talking past one another, members must all be in the same problem-solving stage. In order to make this happen our meetings must be methodical.

In a methodical meeting, for each issue that needs to be discussed, members deliberately and explicitly choose just one problem-solving stage to complete.

To convert an intuitive meeting into a methodical one take your meeting agenda, and to the right of each agenda item, write down a problem-solving stage that will help move you closer to a solution, as well as the corresponding measurable outcome for that stage. Then, during that part of the meeting, focus only on achieving that outcome. Once you do, move on.

A Template for Conducting a Methodical Meeting

Pair each agenda item with a problem solving stage and a measurable outcome.

Agenda ItemProblem Solving StageMeasurable Outcome
Select a venue for the offsiteDevelop alternativesList of potential venues
Discuss ERP usage problemsFrameProblem statement
Implement new batch record strategyPlan for ImplementationList of actions / owners / due dates
Review proposed projectsEvaluate AlternativesList of strengths and weaknesses
Choose a vendorMake DecisionWritten decision

If you don’t know which problem-solving stage to choose, consider the following:

Do you genuinely understand the problem you’re trying to solve? If you can’t clearly articulate the problem to someone else, chances are you don’t understand it as well as you might think. If that’s the case, before you start generating solutions, consider dedicating this part of the meeting to framing and ending it with a succinctly written problem statement.

Do you have an ample list of potential solutions? If the group understands the problem, but hasn’t yet produced a set of potential solutions, that’s the next order of business. Concentrate on generating as many quality options as possible (set the alternatives).

Do you know the strengths and weaknesses of the various alternatives? Suppose you have already generated potential solutions. If so, this time will be best spent letting the group evaluate them. Free attendees from the obligation of reaching a final decision—for which they may not yet be ready—and let them focus exclusively on developing a list of pros and cons for the various alternatives.

Has the group already spent time debating various alternatives? If the answer is yes, use this part of the meeting to do the often difficult work of choosing. Make sure, of course, that the final choice is in writing.

Has a decision been made? Then focus on developing an implementation plan. If you’re able to leave the conversation with a comprehensive list of actions, assigned owners, and due dates, you can celebrate a remarkably profitable outcome.

The difference between complex and complicated

We often think that complicated and complex are on a continuum, that complex is just a magnitude above complicated; or that they are synonyms. These are actually different, and one cannot address complex systems in the same way as complicated. Many improvement efforts fail by not seeing the difference and they throw resources at projects that are bound for failure because they are looking at the system the wrong way.

Complicated problems originate from causes that can be individually distinguished; they can be address­ed piece by­ piece; for each input to the system there is a proportionate output; the relevant systems can be controlled and the problems they present admit permanent solutions.

Complex problems result from networks of multiple interacting causes that cannot be individually distinguished and must be addressed as entire systems. In complex systems the same starting conditions can produce different outcomes, depending on interactions of the elements in the system. They cannot be addressed in a piecemeal way; they are such that small inputs may result in disproportionate effects; the problems they present cannot be solved once and for ever, but require to be systematically managed and typically any intervention merges into new problems as a result of the interventions dealing with them;  and the relevant systems cannot be controlled – the best one can do is to influence them, or learn to “dance with them” as Donella Meadows said.

Lets break down some ways these look and act different by looking at some of the key terminology.

Causality, the relationship between the thing that happens and the thing that causes it

Complicated Linear cause-and-effect pathways allow us to identify individual causes for observed effects.
ComplexBecause we are dealing with patterns arising from networks of multiple interacting (and interconnected) causes, there are no clearly distinguishable cause-and-effect pathways.

This challenges the usefulness of root cause analysis. Most common root cause analysis methodologies are based on cause-and-effect.

Linearity,  the relationships between elements of a process and the output

ComplicatedEvery input has a proportionate output
ComplexOutputs are not proportional or linearly related to inputs; small changes in one part of the system can cause sudden and unexpected outputs in other parts of the system or even system-wide reorganization.

Think on how many major changes, breakthroughs and transformations, fail.

Reducibility, breaking down the problem

ComplicatedWe can decompose the system into its structural parts and fully understand the functional relationships between these parts in a piecemeal way.
Complex The structural parts of the system are multi-functional — the same function can be performed by different structural parts.  These parts are also richly inter-related i.e. they change one another in unexpected ways as they interact.  We can therefore never fully understand these inter-relationships

This is the challenge for our problem solving methodologies, which mostly assume that a problem can be broken down into its constituent parts. Complex problems present as emergent patterns resulting from dynamic interactions between multiple non-linearly connected parts.  In these systems, we’re rarely able to distinguish the real problem, and even small and well-intentioned interventions may result in disproportionate and unintended consequences.

Constraint

Complicated One structure-one function due to their environments being delimited i.e. governing constraints are in place that allows the system to interact only with selected or approved types of systems.  Functions can be delimited either by closing the system (no interaction) or closing its environment (limited or constrained interactions).

Complicated systems can be fully known as a result and are mappable.
Complex Complex systems are open systems, to the extent that it is often difficult to determine where the system ends and another start.   Complex systems are also nested they are part of larger scale complex systems, e.g. an organisation within an industry within an economy.  It is therefore impossible to separate the system from its context.

This makes modeling an issue of replicating the system, it cannot be reduced. We cannot transform complex systems into complicated ones by spending more time and resources on collecting more data or developing better maps.

Some ideas for moving forward

Once you understand that you are in a complex system instead of a complicated process you can start looking for ways to deal with it. These are areas we need to increase capabilities with as quality professionals.

  • Methodologies and best practices to decouple parts of a larger system so they are not so interdependent and build in redundancy to reduce the chance of large-scale failures.
  • Use storytelling and counterfactuals. Stories can give great insight because the storyteller’s reflections are not limited by available data.
  • Ensure our decision making captures different analytical perspectives.
  • Understand our levers