Your Company Made 10,000 Decisions Today. How Many Were Actually Good?
Every day, large organizations make thousands of decisions. Inventory is allocated across markets. Employees are scheduled. Production levels are adjusted. Capital is deployed. Customer requests are prioritized. Prices change. Resources move between facilities. Forecasts are updated, and those forecasts influence another series of decisions across the organization.
Some of these decisions involve millions of dollars and senior executives. Most are far less visible. They happen continuously across departments, facilities, systems, and management teams. Individually, many seem routine. Collectively, they determine how efficiently an organization uses its people, capital, time, and physical resources.
Companies have become extraordinarily good at measuring the results. Revenue, margins, utilization, inventory, productivity, demand, customer behavior, and thousands of other metrics can now be monitored with remarkable precision. Yet there is a more difficult question underneath those numbers: how many of the decisions that produced them were actually good?
The economics of making decisions
Research suggests that decision making consumes an enormous amount of organizational capacity. In a study of more than 1,200 business leaders, McKinsey found that managers spent approximately 37 percent of their working time making decisions. Respondents believed that 58 percent of that time was used ineffectively.
McKinsey estimated that the consequences for a typical Fortune 500 company could amount to more than 530,000 days of management time lost to ineffective decision making every year, equivalent to approximately $250 million in annual wages.
That figure measures the cost of the decision making process itself. It does not measure what happens when the resulting decision is wrong.
That distinction matters. The economic cost of a poor decision may not appear where the decision was originally made. An inventory allocation that appears efficient can eventually produce excess stock in one market and shortages in another. A production decision can affect labor requirements, supplier demand, equipment capacity, fulfillment schedules, and working capital. A staffing decision can improve one operating metric while creating an entirely different constraint elsewhere.
In a large organization, decisions rarely exist independently.
Why good decisions become difficult at scale
The problem is partly mathematical. Even relatively small decision environments can create enormous numbers of possible outcomes.
Consider a simplified situation involving ten decisions, each with ten possible choices. There are 10 billion possible combinations. Real enterprises operate with vastly more variables, and those variables interact with one another. Facilities have capacity limits. Employees have schedules. Capital is finite. Customers have requirements. Production systems have physical constraints. Regulations limit what can be done. Every decision must exist within those boundaries.
The environment also changes continuously. Demand shifts. Equipment fails. Employees become unavailable. Suppliers are delayed. Customers change their behavior. New orders arrive. Prices move. Information that was incomplete becomes available.
As a result, a decision can be rational when it is made and still produce a poor outcome. The person making it may have used the correct information, followed the correct process, and selected the strongest option visible at the time. The problem may simply be that the decision was evaluated within too narrow a window.
Gartner reported in 2024 that 72 percent of executives said bad decisions occurred about as frequently as good ones. McKinsey has found a similar tension between quality and speed. In one global survey, 57 percent of respondents said their organizations consistently made high quality decisions, while 48 percent said they made decisions quickly. Only 37 percent believed their organizations achieved both.
For an enterprise, speed and quality cannot always be separated. Waiting for more information can improve confidence, but the environment may change while an organization waits. Acting quickly can preserve an opportunity, but it can also mean making a consequential choice without understanding enough of what follows.
A decision is not an isolated event
One of the most difficult characteristics of enterprise decision making is that every meaningful decision changes the conditions for future decisions.
Suppose a company changes production at one facility. That choice alters inventory levels. The change in inventory affects distribution requirements. Distribution affects capacity elsewhere. Different capacity requirements influence labor, transportation, procurement, and potentially customer fulfillment. Each subsequent choice is now being made in an environment partly created by the original decision.
This is why the most expensive decision is not necessarily an obviously bad one.
It may be a perfectly reasonable decision that creates a series of increasingly expensive constraints somewhere else in the organization.
Large companies are divided into functions because they have to be. Finance, operations, procurement, sales, manufacturing, human resources, and supply chain teams each manage different parts of an extraordinarily complicated system. That structure makes organizations manageable, but it also means that decisions can be evaluated according to local objectives.
Reducing cost in one function can increase cost in another. Maximizing utilization can reduce flexibility. Increasing inventory can improve product availability while tying up additional capital. Minimizing inventory can free capital while increasing the risk of shortages. None of these choices is inherently right or wrong. Their value depends on what they cause elsewhere.
This creates a fundamental problem for large organizations. The best decision for one part of the company may not be the best decision for the company as a whole.
The decisions nobody remembers
Major strategic decisions receive enormous scrutiny. Acquisitions can take months to evaluate. Capital investments go through committees. New markets are studied extensively. Boards review major changes in corporate strategy.
But much of an enterprise’s performance is also determined by ordinary decisions that will never appear in an annual report.
A manager changes staffing at a facility. A planner reallocates inventory. A production schedule is modified. A customer is prioritized. A purchasing decision is accelerated. Capacity is moved from one part of the organization to another.
No single choice necessarily transforms the company. The significance emerges through accumulation.
Research from Bain & Company found a meaningful relationship between decision effectiveness and financial performance. Companies in the top quintile for decision effectiveness generated average total shareholder returns nearly six percentage points higher than other companies in its research.
The finding does not mean that decision effectiveness alone caused the difference in shareholder returns. It does reinforce a broader point. Decision making is not simply an administrative function inside an organization. It is one of the mechanisms through which resources become results.
What happens after decision number 10,000?
By the end of a day, an enterprise may be able to describe almost everything that happened inside its operations. It can calculate revenue, costs, utilization, inventory, output, delays, customer demand, and hundreds of other measures.
What is much harder to determine is whether a different sequence of decisions could have produced a better result.
That question becomes increasingly important as organizations generate more information. The modern enterprise does not suffer from a shortage of data. In many cases, the opposite is true. Organizations possess more information about their operations than any individual or management team could realistically process.
The challenge is understanding how thousands of choices interact over time, particularly when the consequence of one decision may not become visible until many decisions later.
Perhaps the most consequential decision a company made today was not the largest one. It may not have involved the CEO, appeared in a board meeting, or moved a financial metric immediately. It may have been a routine choice somewhere deep inside the organization that quietly changed the options available for everything that followed.
A company can measure the outcome at the end of the day.
Understanding whether it chose the best path to get there is much harder.