Talk about strategy, risk management or change and it is inevitable that the acronym VUCA — short for volatility, uncertainty, complexity, and ambiguity—will come up. VUCA is basically a catchall for “Hey, it’s crazy out there!” And like many catch-all’s it is misleading, VUCA conflates four distinct types of challenges that demand four distinct types of responses. VUCA can quickly become a crutch, a way to throw off the hard work of strategy and planning—after all, you can’t prepare for a VUCA world, right?
The mistake folks often make here is treating these four traits as a single idea, which leads to poorer decision making.
VUCA really isn’t a tool. It’s a checklist of four things that hopefully your system is paying attention to. All four represent distinct elements that make our environment and organization harder to grasp and control.
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,
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
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?
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.
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.
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:
Check for self-interest bias
Check for the affect heuristic. Has the team fallen in love with its own output?
Check for group think. Were dissenting views explored adequately?
Check for saliency bias. Is this routed in past successes?
Check for confirmation bias.
Check for availability bias
Check for anchoring bias
Check for halo effect
Check for sunk cost fallacy and endowment effect
Check for overconfidence, planning fallacy, optimistic biases, competitor neglect
Check for disaster neglect. Have the team conduct a post-mortem: Imagine that the worst has happened and develop a story about its causes.
Risk assessments have a core of the subjective to them, frequently including assumptions about the nature of the hazard, possible exposure pathways, and judgments for the likelihood that alternative risk scenarios might occur. Gaps in the data and information about hazards, uncertainty about the most likely projection of risk, and incomplete understanding of possible scenarios contribute to uncertainties in risk assessment and risk management. You can go even further and say that risk is socially constructed, and that risk is at once both objectively verifiable and what we perceive or feel it to be. Then again, the same can be said of most of science.
Risk is a future chance of loss given exposure to a hazard. Risk estimates, or qualitative ratings of risk, are necessarily projections of future consequences. Thus, the true probability of the risk event and its consequences cannot be known in advance. This creates a need for subjective judgments to fill-in information about an uncertain future. In this way risk management is rightly seen as a form of decision analysis, a form of making decisions against uncertainty.
has a mental picture of risk, but the formal mathematics of risk analysis are
inaccessible to most, relying on probability theory with two major schools of
thought: the frequency school and the subjective probability school. The frequency
school says probability is based on a count of the number of successes divided
by total number of trials. Uncertainty that is ready characterized using
frequentist probability methods is “aleatory” – due to randomness (or random
sampling in practice). Frequentist methods give an estimate of “measured” uncertainty;
however, it is arguably trapped in the past because it does not lend itself to
easily to predicting future successes.
In risk management we tend to measure uncertainty with a combination of frequentist and subjectivist probability distributions. For example, a manufacturing process risk assessment might begin with classical statistical control data and analyses. But projecting the risks from a process change might call for expert judgments of e.g. possible failure modes and the probability that failures might occur during a defined period. The risk assessor(s) bring prior expert knowledge and, if we are lucky, some prior data, and start to focus the target of the risk decision using subjective judgments of probabilities.
Some have argued that a failure to formally control subjectivity — in relation to probability judgments – is the failure of risk management. This was an argument that some made during WCQI, for example. Subjectivity cannot be eliminated nor is it an inherent limitation. Rather, the “problem with subjectivity” more precisely concerns two elements:
A failure to recognize
where and when subjectivity enters and might create problems in risk assessment
and risk-based decision making; and
A failure to
implement controls on subjectivity where it is known to occur.
is about the chance of adverse outcomes of events that are yet to occur,
subjective judgments of one form or another will always be required in both
risk assessment and risk management decision-making.
subjectivity in risk management by:
Raising awareness of where/when subjective judgments of probabilityoccur in risk assessment and risk management
Identifying heuristics and biases where they occur
Improving the understanding of probability among the team and individual experts
Risk Management is all about eliminating surprise. So to truly start to understand our risks, we need to understand uncertainty, we need to understand the unknowns. Borrowing from Andreas Schamanek’s Taxonomies of the unknown, let’s explore a few of the various taxonomies of what is not known.
I’m pretty sure Ann Kerwin first gave us the “known unknowns” and the “unknown knowns” that people still find a source of amusement about former defense secretary Rumsfield.
Risk management is then a way of teasing out the unknowns and allowing us to take action:
Risk assessments mostly easily focus on the ignorance that we are aware of, the ‘known unknowns’.
Risk assessments can also serve as a tool of teasing out the ‘unknown knowns’. This is why participation of subject matter experts is so critical. Through the formal methodology of the risk assessment we expose and explore tacit knowledge.
The third kind of ignorance is what we do now know we do not know, the ‘unknown unknowns’. We generally become aware of unknown unknowns in two ways: hindsight (deviations) and by purposefully expanding our horizons. This expansion includes diversity and also good experimentation. It is the hardest, but perhaps, most valuable part of risk management.
Taxonomy of Ignorance
Smithson distinguishes between passive and active ignorance. Passive ignorance involves areas that we are ignorant of, whereas active ignorance refers to areas we ignore. He uses the term ‘error’ for the unknowns encompassed by passive ignorance and ‘irrelevance’ for active ignorance.
Taboo is fascinating because it gets to the heart of our cultural blindness, those parts of our organization that are closed to scrutiny.
Smithson can help us understand why risk assessments are both a qualitative and a quantitative endeavor. While dealing with the unknown is the bread and butter of statistics, only a small part of the terrain of uncertainty is covered. Under Smithson’s typology, statistics primarily operates in the area of incompleteness, across probability and some kinds of vagueness. In terms of its considerations of sampling bias, statistics also has some overlap with inaccuracy. But, as the typology shows, there is much more to unknowns than the areas statistics deals with. This is another reason that subject matter experts, and different ways of thinking is a must.
Ensuring wide and appropriate expert participation gives additional perspectives on unknowns. There is also synergies by finding unrecognized similarities between disciplines and stakeholders in the unknowns they deal with and there may be great benefit from combining forces. It is important to use these concerns to enrich thinking about unknowns, rather than ruling them out as irrelevant.
Sources of Surprise
Risk management is all about managing surprise. It helps to break surprise down to three types: risk, uncertainty and ignorance.
Risk: The condition in which the event, process, or outcomes and the probability that each will occur is known.
Issue: In reality, complete knowledge of probabilities and range of potential outcomes or consequences is not usually known and is sometimes unknowable.
Uncertainty: The condition in which the event, process, or outcome is known (factually or hypothetically) but the probabilities that it will occur are not known.
Issue: The probabilities assigned, if any, are subjective, and ways to establish reliability for different subjective probability estimates are debatable.
Ignorance: The condition in which the event, process, or outcome is not known or expected.
Issue: How can we anticipate the unknown, improve the chances of anticipating, and, therefore, improve the chances of reducing vulnerability?
Effective use of the methodology moves ideally from ignorance to eventually risk.
Methods of Mitigation
Information is available but SMEs are unwilling or unable to consider that some outcomes are unknown to them.
Self-audit process, regular third-party audits, and open and transparent system with global participation
Information is available and SMEs are willing to recognize and consider that some outcomes are unknown.
Surprise occurs because an individual SME lacks knowledge or awareness of the available information.
effective teams xxplore multiple perspectives by including a diverse set of individuals and data sources for data gathering and analysis.
Transparency in process.
Surprise occurs because a group of SMEs has only similar viewpoints represented or may be less willing to consider views outside the community.
Diversity of viewpoints and sue of tools to overcome group-think and “tribal” knowledge
Surprise occurs because the SMEs are unable to anticipate and prepare for external shocks or internal changes in preferences, technologies, and institutions.
Simulating impacts and gaming alternative outcomes of various potentials under different conditions (Blue Team/Read Team exercises)
Surprise occurs when inadequate forecasting tools are used to analyze the available data, resulting in inter-relationships, hidden dependencies, feedback loops, and other negative factors that lead to inadequate or incomplete understanding of the data.
Track changes and interrelationships of various systems to discover potential macro-effect force changes 12-Levers
Risk Management is all about understanding surprise and working to reduce uncertainty and ignorance in order to reduce, eliminate and sometimes accept. As a methodology it is effective at avoiding surrender and denial. With innovation we can even contemplate exploitation. As organizations mature, it is important to understand these concepts and utilize them.
House, Robert J., Paul J. Hanges, Mansour Javidan, Peter Dorfman, and Vipin Gupta, eds. 2004. Culture, Leadership, andOrganizations: The GLOBE Study of 62 Societies. Thousand Oaks, Calif.: Sage Publications.