Noted business author Tom Davenport has an article, “Make Better Decisions,” in the November issue of Harvard Business Review . He describes the prevalence, in the business world, of what he calls “decision-making disorder,” but this also has real applicability to government.
He says decisions have “generally been viewed as the prerogative of individuals – usually senior executives. The process employed, the information used, the logic relied on, have been left up to them, in something of a black box.” He notes that, unlike other business processes, “decision making has rarely been the focus of systematic analysis inside the firm.” But, he notes, there are many opportunities to improve decision making, just as there are opportunities to improve other business processes.
He lists a series of useful books that are being widely read on ways to improve decisions, but concludes “few companies have actually adopted their recommendations.” Still, he confidently lays out four “I”steps that he believes can improve decision making:
• Identification of key decisions to be made. Without some prioritization, all decisions will be treated as equal. This probably means important decisions won’t be analyzed sufficiently before they are made.
• Inventory of factors that need to go into making key decisions. What the are roles, processes, systems, and behaviors your organization should be using to make effective decisions? It is important to establish a common language in your organization around how decisions are made.
• Intervention by top leaders. Leaders need to look not only at the decisions being made but also at how they would be implemented.
• Institutionalization of a decision making process. Organizations serious about making effective decisions invest in defining a process, developing the tools, and training their executives on how to use it effectively.
Davenport concludes: “Analytics and decision automation are among the most powerful tools for improving decision making,” yet he cautions that “multiple perspectives yield better results” and that managers should not “build into their businesses analytical models they don’t understand.”