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 simultaneously occupy the same problem-solving stage. Clear communication is critical here and it is important for the team to understand what. Our meetings need to 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

Decision Quality

The decisions we make are often complex and uncertain. Making the decision-making process better is critical to success, and yet too often we do not think of the how we make decisions, and how to confirm we are making good decisions. In order to bring quality to our decisions, we need to understand what quality looks like and how to obtain it

There is no universal best process or set of steps to follow in making good decisions. However, any good decision process needs to embed the idea of decision-quality as the measurable destination.

Decisions do not come ready to be made. You must shape them and declare what is the decision you should be making; that must be made. All decisions have one thing in common – the best choice creates the best possibility of what you truly want. To find that best choice, you need decision-quality and you must recognize it as the destination when you get there. You cannot reach a good decision, achieve decision-quality, if you are unable to visualize or describe it. Nor can you say you have accomplished it, if you cannot recognize it when it is achieved.

What makes a Good Decision?

The six requirements for a good decision are: (1) an appropriate frame, (2) creative alternatives, (3) relevant and reliable information, (4) clear values and trade-offs, (5) sound reasoning, and (6) commitment to action. To judge the quality of any decision before you act, each requirement must be met and addressed with quality. I like representing it as a chain, because a decision is no better than the weakest link.

The frame specifies the problem or opportunity you are tackling, asking what is to be decided. It has three parts:  purpose in making the decision; scope of what will be included and left out; and your perspective including your point of view, how you want to approach the decision, what conversations will be needed, and with whom. Agreement on framing is essential, especially when more than one party is involved in decision making. What is important is to find the frame that is most appropriate for the situation. If you get the frame wrong, you will be solving the wrong problem or not dealing with the opportunity in the correct way.

The next three links are: alternatives – defining what you can do; information – capturing what you know and believe (but cannot control), and values – representing what you want and hope to achieve. These are the basis of the decision and are combined using sound reasoning, which guides you to the best choice (the alternative that gets you the most of what you want and in light of what you know). With sound reasoning, you reach clarity of intention and are ready for the final element – commitment to action.

Asking: “What is the decision I should be making?” is not a simple question. Furthermore, asking the question “On what decision should I be focusing?” is particularly challenging. It is a question, however, that is important to be asked, because you must know what decision you are making. It defines the range within which you have creative and compelling alternatives. It defines constraints. It defines what is possible. Many organizations fail to create a rich set of alternatives and simply debate whether to accept or reject a proposal. The problem with this approach is that people frequently latch on to ideas that are easily accessible, familiar or aligned directly with their experiences.

Exploring alternatives is a combination of analysis, rigor, technology and judgement. This is about the past and present – requiring additional judgement to anticipate future consequences. What we know about the future is uncertain and therefore needs to be described with possibilities and probabilities. Questions like: “What might happen?” and “How likely is it to happen?” are difficult and often compound. To produce reliable judgements about future outcomes and probabilities you must gather facts, study trends and interview experts while avoiding distortions from biases and decision traps. When one alternative provides everything desired, the choice among alternatives is not difficult. Trade-offs must be made when alternatives do not provide everything desired. You must then decide how much of one value you are willing to give up to receive more of another.  

Commitment to action is reached by involving the right people in the decision efforts. The right people must include individuals who have the authority and resources to commit to the decision and to make it stick (the decision makers) and those who will be asked to execute the decided-upon actions (the implementers). Decision makers are frequently not the implementers and much of a decision’s value can be lost in the handoff to implementers. It is important to always consider the resource requirements and challenges for implementation.

These six requirements of decision-quality can be used to judge the quality of the decision at the time it is made. There is no need to wait six months or six years to assess its outcome before declaring the decision’s quality. By meeting the six requirements you know at the time of the decision you made a high-quality choice. You cannot simply say: “I did all the right steps.” You have got to be able to judge the decision itself, not just how you got to that decision. When you ask, “How good is this decision if we make it now?” the answer must be a very big part of your process. The piece missing in the process just may be in the material and the research and that is a piece that must go right.

Decision-quality is all about reducing comfort zone bias – when people do what they know how to do, rather than what is needed to make a strong, high-quality decision. You overcome the comfort zone bias by figuring out where there are gaps. Let us say the gap is with alternatives. Your process then becomes primarily a creative process to generate alternatives instead of gathering a great deal more data. Maybe we are awash in a sea of information, but we just have not done the reasoning and modelling and understanding of the consequences. This becomes more of an analytical effort. The specific gaps define where you should put your attention to improve the quality of the decision.

Leadership needs to have clearly defined decision rights and understand that the role of leadership is assembling the right people to make quality decisions. Once you know how to recognize digital quality, you need an effective and efficient process to get there and that process involves many things including structured interactions between decision maker and decision staff, remembering that productive discussions result when multiple parties are involved in the decision process and difference in judgement are present.

Beware Advocacy

The most common decision process tends to be an advocacy decision process – you are asking somebody to sell you an answer. Once you are in advocacy mode, you are no longer in a decision-quality mode and you cannot get the best choice out of an advocacy decision process. Advocacy suppresses alternatives. Advocacy forces confirming evidence bias and means selective attention to what supports your position. Once in advocacy mode, you are really in a sales mode and it becomes a people competition.

When you want quality in a decision, you want the alternatives to compete, not the people. From the decision board’s perspective, when you are making a decision, you want to have multiple alternatives in front of you and you want to figure out which of these alternatives beats the others in terms of understanding the full consequences in risk, uncertainty and return. For each of the alternatives one will show up better. If you can make this happen, then it is not the advocate selling it, it is you trying to help look at which of these things gives us the most value for our investment in some way.

The role outcomes play in the measuring of decision quality

Always think of decisions and outcomes as separate because when you make decisions in an uncertain world, you cannot fully control the outcomes. When looking back from an outcome to a decision, the only thing you can really tell is if you had a good outcome or a bad outcome. Hindsight bias is strong, and once triggered, it is hard to put yourself back into understanding what decisions should have been made with what you knew, or could have known, at the time.

In understanding how we use outcomes in terms of evaluating decisions, you need to understand the importance of documenting the decision and the decision quality at the time of the decision. Ask yourself, if you were going to look back two years from now, what about this decision file answers the questions: “Did we make a decision that was good?” and “What can we learn about the things about which we had some questions?” This kind of documentation is different from what people usually do. What is usually documented is the approval and the working process. There is usually no documentation answering the question: “If we are going to look back in the future, what would we need to know to be able to learn about making better decisions?”

The reason you want to look back is because that is the way you learn and improve the whole decision process. It is not for blaming; in the end, what you are trying to show in documentation is: “We made the best decision we could then. Here is what we thought about the uncertainties. Here is what we thought were the driving factors.” Its about having a learning culture.

When decision makers and individuals understand the importance of reaching quality in each of the six requirements, they feel meeting those requirements is a decision-making right and should be demanded as part of the decision process. To be in a position where they can make a good decision, they know they deserve a good frame and significantly different alternatives or they cannot be in a position to reach a powerful, correct conclusion and make a decision. From a decision-maker’s perspective, these are indeed needs and rights to be thought about. From a decision support perspective, these needs and rights are required to be able to position the decision maker to make a good choice.

Building decision-quality enables measurable value creation and its framework can be learned, implemented and measured. Decision-quality helps you navigate the complexity of uncertainty of significant and strategic choices, avoid mega biases and big decision traps.

Overcoming Subjectivity in Risk Management and Decision Making Requires a Culture of Quality and Excellence

Risk assessments, problem solving and making good decisions need teams, but any team has challenges in group think it must overcome. Ensuring your facilitators, team leaders and sponsors are aware and trained on these biases will help lead to deal with subjectivity, understand uncertainty and drive to better outcomes. But no matter how much work you do there, it won’t make enough of a difference until you’ve built a culture of quality and excellence.

The mindsets we are trying to build into our culture will strive to overcome a few biases in our teams that lead to subjectivity.

Bias Toward Fitting In

We have a natural desire to want to fit in. This tendency leads to two challenges:

Challenge #1: Believing we need to conform. Early in life, we realize that there are tangible benefits to be gained from following social and organizational norms and rules. As a result, we make a significant effort to learn and adhere to written and unwritten codes of behavior at work. But here’s the catch: Doing so limits what we bring to the organization.

Challenge #2: Failure to use one’s strengths. When employees conform to what they think the organization wants, they are less likely to be themselves and to draw on their strengths. When people feel free to stand apart from the crowd, they can exercise their signature strengths (such as curiosity, love for learning, and perseverance), identify opportunities for improvement, and suggest ways to exploit them. But all too often, individuals are afraid of rocking the boat.

We need to use several methods to combat the bias toward fitting in. These need to start at the cultural level. Risk management, problem solving and decision making only overcome biases when embedded in a wider, effective culture.

Encourage people to cultivate their strengths. To motivate and support employees, some companies allow them to spend a certain portion of their time doing work of their own choosing. Although this is a great idea, we need to build our organization to help individuals apply their strengths every day as a normal part of their jobs.

Managers need to help individuals identify and develop their fortes—and not just by discussing them in annual performance reviews. Annual performance reviews are horribly ineffective. Just by using “appreciation jolt”, positive feedback., can start to improve the culture. It’s particularly potent when friends, family, mentors, and coworkers share stories about how the person excels. These stories trigger positive emotions, cause us to realize the impact that we have on others, and make us more likely to continue capitalizing on our signature strengths rather than just trying to fit in.

Managers should ask themselves the following questions: Do I know what my employees’ talents and passions are? Am I talking to them about what they do well and where they can improve? Do our goals and objectives include making maximum use of employees’ strengths?

Increase awareness and engage workers. If people don’t see an issue, you can’t expect them to speak up about it.  

Model good behavior. Employees take their cues from the managers who lead them.

Bias Toward Experts

This is going to sound counter-intuitive, especially since expertise is so critical. Yet our biases about experts can cause a few challenges.

Challenge #1: An overly narrow view of expertise. Organizations tend to define “expert” too narrowly, relying on indicators such as titles, degrees, and years of experience. However, experience is a multidimensional construct. Different types of experience—including time spent on the front line, with a customer or working with particular people—contribute to understanding a problem in detail and creating a solution.

A bias toward experts can also lead people to misunderstand the potential drawbacks that come with increased time and practice in the job. Though experience improves efficiency and effectiveness, it can also make people more resistant to change and more likely to dismiss information that conflicts with their views.

Challenge #2: Inadequate frontline involvement. Frontline employees—the people directly involved in creating, selling, delivering, and servicing offerings and interacting with customers—are frequently in the best position to spot and solve problems. Too often, though, they aren’t empowered to do so.

The following tactics can help organizations overcome weaknesses of the expert bias.

Encourage workers to own problems that affect them. Make sure that your organization is adhering to the principle that the person who experiences a problem should fix it when and where it occurs. This prevents workers from relying too heavily on experts and helps them avoid making the same mistakes again. Tackling the problem immediately, when the relevant information is still fresh, increases the chances that it will be successfully resolved. Build a culture rich with problem-solving and risk management skills and behaviors.

Give workers different kinds of experience. Recognize that both doing the same task repeatedly (“specialized experience”) and switching between different tasks (“varied experience”) have benefits. Yes, Over the course of a single day, a specialized approach is usually fastest. But over time, switching activities across days promotes learning and kept workers more engaged. Both specialization and variety are important to continuous learning.

Empower employees to use their experience. Organizations should aggressively seek to identify and remove barriers that prevent individuals from using their expertise. Solving the customer’s problems in innovative, value-creating ways—not navigating organizational impediments— should be the challenging part of one’s job.

In short we need to build the capability to leverage all level of experts, and not just a few in their ivory tower.

These two biases can be overcome and through that we can start building the mindsets to deal effectively with subjectivity and uncertainty. Going further, build the following as part of our team activities as sort of a quality control checklist:

  1. Check for self-interest bias
  2. Check for the affect heuristic. Has the team fallen in love with its own output?
  3. Check for group think. Were dissenting views explored adequately?
  4. Check for saliency bias. Is this routed in past successes?
  5. Check for confirmation bias.
  6. Check for availability bias
  7. Check for anchoring bias
  8. Check for halo effect
  9. Check for sunk cost fallacy and endowment effect
  10. Check for overconfidence, planning fallacy, optimistic biases, competitor neglect
  11. Check for disaster neglect. Have the team conduct a post-mortem: Imagine that the worst has happened and develop a story about its causes.
  12. Check for loss aversion