Sunday, July 16, 2017


Decision-making is both art and science. It is the science only when decision-makers understand the scientific perspective of decision making.

Due to the overwhelming growth of information and unprecedented uncertainty, either at the individual or the organization level, making sound judgments and effective decisions become the core capability to differentiate the digital leaders from laggards. However, across the sectors, the high ratio of strategic decisions have been made poorly and cause the catastrophic effect. And the individual’s bias or poor judgments diminish the trust, enlarge the creativity gaps, and tarnish the corporate reputation. Ineffective decision making is, unfortunately, pervasive and caused by varying factors, here are five causes of ineffective decision-making,

Cognitive Bias: Most of what poor decisions have boiled down to lack of updated information/intelligence and decision maker bias. At the group level, the homogeneous team setting spurs groupthink and creates blind spots for making effective decisions. Poor or inaccurate judgment, illogical interpretations, lack of contextual intelligence, etc. are all root causes for making ineffective decisions which further cause a series of issues cascaded into big problems and fatal business failures. Bias or cognitive gaps come in many forms and are difficult to recognize if you are the decision maker. Therefore, team perspective is crucial for novel decisions because no individual has all the necessary expertise. Both information and intuition are important in making effective decisions, the multidimensional thinking and a clearly structured dialog and decision process can create alternatives that gain a comprehensive understanding of the issue and improve decision-making maturity.

Strategic Misrepresentation: Digital implies hyper connectivity and interdependence. It is more critical than ever to understand the interconnectivity between the parts and the whole, otherwise, you perhaps focus on making a seemly right decision for fixing a small issue, but unfortunately cause bigger issues without contextual understanding. Or put another way, such a solution is perhaps only fixing the symptom, technically right but presents strategic misrepresentation. And the deliberate misrepresentation is also caused by distorted incentives, silo thinking, and lack of system wisdom. In practice, there’s the ‘problem of defining a problem'; with its cause driven by an individual's ability to make sense out of uncertainty. The lack of clarity usually surrounds the context of the decision to be taken. Nothing is clear or concise. Therefore, effective resource allocation and utilization is an important factor for a decision making, because there are so many variables you just have to weigh in, sometimes you have to sacrifice to save and other times you need to disable one thing to enable another. Without strategic clarity and system reasoning, decision making is simply becoming the serendipity with high-rate of failures, and cause serious problems to run a high-performance business or an advanced human society.

Planning Fallacy: In fast moving competitive digital business environments, the flow and sequence of the subsidiary decision implementations all encounter a different set of context dynamics. Decision effectiveness is not only based the decision-makers' intelligence, skills, as well as tools, a dynamic decision-making scenario helps to both leverage a logical decision process as well as evolve the emergent business property. Because the planning fallacy is either caused by overly static decision process or lack of the structure - the shortcomings inherent in a current decision-making knowledge context and top-down vague strategic - 'me-tooism' - style. That means often decision-making lacks the much needed essential iterative process dynamics, or where the decision is managed as the end effect, not the beginning. Decision effectiveness relies on an agreed/ common approach to making decisions, but not a predetermined set of "one size fits all" planning.

Optimism Bias: A decision is arguably a choice between two or more options. The greater majority of these options are circumstantially provided. The other pitfall for decision effectiveness is about the systematic tendency to be overly optimistic about the outcome of actions. Even with the best systems and processes, there are no guarantees that you will always get the expected outcome. Indeed the fact that something requires a decision will mean that there will be a bunch of associated risks to manage. Hence, especially at the strategic level, the decision is not about good vs. bad decisions, more precisely, it is about making a decision that has 'less bad' outcomes. In other words, it takes the least harmful decision within a multi-complex environment. To overcome such a bias, decision making becomes more effective when decision makers understand that the best outcomes are to make a good decision in a timely manner; the second best outcome is to make a poor decision in a timely manner, and figure out that there is something wrong, and correct it and move forward; and keep in mind, the worse outcome is to make no decision or delay decision-making to the point of ineffectiveness.

Focalism: It is a sort of cognitive bias that describes the common human tendency to rely too heavily on the first piece of information provided when making decisions. The lack of updated viable information, systematic understanding, is critical to the failure of, or consequences of a bad decision. Too often, the decision makers are too much inwardly focused and lose the situational awareness and appreciation of wider context during times of stress. This is particularly risky in today’s digital new normal with “VUCA” characteristics. Without sufficient information and a holistic understanding of the problem, decision-making is often immature. It is argued that the only way to fully understand why a problem or element occurs and persists is to understand the parts in relation to the whole. In science systems, the component parts of a system can best be understood in the context of relationships with each other and with other systems, rather than in isolation. This means being very clear about both internal factors, such as decision situation, context, relevant knowledge, organizational capability & resource, etc, as well as external factors such as technology factors, political and legal conditions, and competition and consumer demands, etc.

Decision-making is both art and science. It is the science only when decision-makers understand the scientific perspective of decision making. Independent thinking is important, and collective wisdom is the gem for improving decision maturity. However, the team perspective should usually be specified probabilistically because knowledge about the past is only an imperfect guide to what the future holds. Hence, decision maturity is based on the maturity of the decision maker to overcome bias, make iterative decision processes & planning, leverage both information and intuition, to not search for perfection, but improve decision effectiveness.


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