According to various estimates, every person makes dozens to hundreds of decisions daily, most of them automatically and without reflection. Most of the time, no specific competencies or sacrifice are required and no serious risks are involved. The decisions made in organizations are also typically routine and practically automatic. And yet, there are hardly leaders who have never in their careers been forced to make choices that they felt would immensely affect their organization. Such pivotal moments test a leader’s ability to handle complex problems and multiple critical factors. The most crucial decisions by managers are affected by stress, prior experience and competencies, analytical skills, and the abilities to control one’s emotions, rapidly process large amounts of information, and think ahead. While each of these factors plays a role, it is impossible to measure their sum accurately. Therefore, the way I see it, the making of key decisions is a balancing act between knowledge and ignorance, intuition and reason, certainty and uncertainty. This point is well illustrated by Aaron Wildavsky, an American theoretician of management, who did the bulk of his work in the 1980s. In his well-known quote, Wildavsky shows that, paradoxically, no leader of any organization will ever have all the information they need, as some of it gets lost on “entering” the organization while its other bits get filtered out once they circulate in it. If they seek original sources, they are easily overwhelmed. If they rely on what they get, they are easily misled. Either way, the pickle they are in is not enviable. Whichever way they go, error is endemic.
The going is tough – therefore things are going well
All theoretical models that describe decision-making, and there are scores of them out there, share numerous elements. The most basic of them describe a sequence of steps, starting with problem identification, followed by problem analysis, the development of viable solutions and the selection of the solution that best matches one’s priorities and/or resources. Among such simple descriptive models, the ones that appeal to me the most are based on the belief that decision-making boils down to choosing from among the available options. It is always essential to weigh the costs and benefits of a given choice. Even this simple approach has a readily identifiable critical point. After all, the costs and benefits of the options we are pondering may be comparable. And then nothing really matters except an intuition that relies on experience. Even here though I can see a promising solution that has been well summarized by Peter Drucker. He said that you simply cannot wait too long. “On an important decision one rarely has 100% of the information needed for a good decision no matter how much one spends or how long one waits. And, if one waits too long, he has a different problem and has to start all over. This is the terrible dilemma of the hesitant decision maker.” In other words, delaying and evading decisions tops the list of a leader’s no-nos. My experience tells me that a failure to make any decision at all is often the worst possible option.
A few simple measures
Even at times when, as a leader, I am confronted with the most knotty of problems, I do not operate in a vacuum or start from scratch. As long as my leadership is open and based on dialogue with people on a partnership basis, I can always count on feedback from those around me. Others can help me verify misguided presumptions, warn me or support me. Provided my leadership model is not authoritarian, drawing on collective knowledge greatly improves my chances of avoiding mistakes. Furthermore, in a modern organization, I can access all kinds of data, including historical studies that allow me to assess my decisions and the likelihood that their results will be positive.
It seems sensible to me that any leaders who face complex decisions draw up a handy list of rules that will guide them through critical moments. For example, when making a decision, I pick, as my first choice, an action which I expect to provide the best results, based on the knowledge I have right there and then. In this way, I keep myself from multiplying data ad infinitum. Secondly, I beware of falling into the pitfalls of misguided views and flawed reasoning. I make sure not to confuse causes with effects. Thirdly, as a rule, I never stop broadening my perspectives and listening attentively to other people’s opinions. Fourthly, I make sure that all of the relevant critical information is at my fingertips at a given time and that all the analytical tools that are available have been acquired. And, importantly, I do not make rash heat-of-the-moment decisions by yielding to emotions, which should never influence the decisions whose consequences are long-lasting. And, most critically, I make decisions based on experience (of my own, my associates or the organization as a whole). I also muster the courage to admit my mistakes once I realize I have made them. This list of behaviors is neither exhaustive nor universal and may not make sense to everyone. However, I think that every leader can make their own, useful list of effective practices that work for them.
My discussion of decision-making would not be complete without at least a sketchy reference to decision automation. That is because advances in automation have also extended to this area. The rise of artificial intelligence has added a new dimension to decision-making. This vast and fascinating topic actually deserves a whole separate article. For now, however, I would like to signal a few related points. Today’s tools that rely on machine learning and deep learning algorithms and technologies enable machines and algorithms to make ever more key decisions. Their immediate beneficiaries may be leaders, entire organizations and customers. The immense data sets available to organizations today allow them to create many analytical and operational models that become useful and indispensible as tools for managers and experts in areas ranging from sales to marketing to logistics to production and finance. We live in a world of global digital ecosystems that consist of products, services and the constant exchange of information at the interface between man, organizations and algorithms. Such ecosystems represent the business environment of modern organizations, whose market success depends largely on effective information processing. The concept of real-time analytics rests on the assumption that modern leaders will have access to ever more algorithm-based tools to support their decisions. Traditional analytical methods required data to be grouped before it could be interpreted. Today’s tools enable one to collect and structure data instantly, providing experts and/or leaders with accurate real-time information on markets. The leaders who are aware of the potential of modern technology will be able to use it to solve current decision-making problems.
Client and leader
One of today’s primary beneficiaries of technological advances is the customer. As technologies provide customers with mobile devices that offer unlimited access to the web, they can comfortably delay their purchasing decisions. Hand-held devices allow customers to shop around and compare prices. Customers can freely explore any products they find appealing. Their decisions become increasingly rational and ever less emotional. Knowing this, the modern leader is becoming more aware of the importance of constantly monitoring customer movements in the digital space. I think that this precisely creates a whole new quality and will increasingly influence executive decision-making. Today’s risky decisions are those that account for all customer behaviors identifiable from every possible source, including social networks, geolocation data, movie viewership and IoT devices at customers’ homes. This puts the traditional intuitions of leaders, their experience and decision-making temperaments in a whole new light. Leaders can verify their decisions by referring to instant reports on the behaviors of the customers who have made their choices using mobile devices. I can get instantaneous feedback from customers based on their purchase decisions and smartphone data. As a leader, I should use such data to improve the next decision I make.