In today’s evolving business landscape, digital transformation is bringing data into virtually every business decision. However, a dashboard filled with numbers can only show us what is happening; it is managers who must make decisions based on those insights. Below are five principles that managers can apply when making decisions in the age of data.
1. Define the objective before looking at the data
Without a clear objective or a well-defined question, managers can easily become “drowned in data” when looking at dashboards filled with information but still lacking the insights needed to make decisions. A system may contain hundreds of metrics, but not all of them are equally important or worth investigating in depth.
Before opening a dashboard, managers should start by asking focused questions, such as: What is changing? Why has productivity increased significantly this month? Where are we losing customers? Which stage of the process is creating a bottleneck?
Principle: Don’t let data dictate the questions. Let the questions guide the search for data.
2. Understand the context behind the numbers
It is essential to distinguish between data itself and its interpretation. Rather than simply interpreting a figure or drawing a premature conclusion, managers should examine the context behind it, including trends, underlying causes, and related metrics. Instead of asking “How much?”, they should dig deeper: Compared with what period? Why did this happen? What lies behind this number?
Principle: A number is a signal that prompts further questions, not a final answer.
3. Seek out and analyze data from multiple perspectives
People naturally tend to seek information that confirms what they already believe, and managers are no exception. If we believe a product will succeed, we may be more inclined to focus on positive figures while overlooking contradictory signals. In this case, data can inadvertently become a tool for justifying existing biases.
Therefore, when reviewing data, managers must remain objective and critically analyze the information provided. Otherwise, they risk selectively seeking out and interpreting data to support their personal biases.
Principle: Examine data from multiple perspectives rather than looking only for evidence that proves you are right.
4. Recognize the boundary between data and bias
In an era of rapid digital transformation, data and artificial intelligence (AI), experience accumulated over time remains valuable. A manager with years of industry experience may recognize an anomaly before it becomes apparent in a report. Someone who works directly with customers may sense a shift in demand before the data fully reflects it
However, intuition and experience can still lead to poor decisions when they lack supporting evidence. The key is to ask the right questions to test these hypotheses. Data provides signals, experience generates hypotheses, and the right questions help validate them.
Principle: Data and intuition do not necessarily compete with each other. They should be used to validate one another.
5. Data supports decisions, but managers remain accountable
An increasing number of tools can analyze information, make forecasts, and provide recommendations. These capabilities help managers make decisions more quickly, but they can also encourage overreliance on data-based options and recommendations. Ultimately, however, managers remain accountable for the decisions made within their organizations. This is the most important consideration when using data-driven decision-support tools.
Principle: Use data to improve the quality of decisions, not to evade responsibility for making them.
As data continues to grow in volume, analytical tools become more sophisticated, and AI generates more forecasts and recommendations, these technologies still cannot make decisions on behalf of managers. Data creates value only when the right questions are asked, the right context is considered, and insights are translated into action. In the age of data, an effective manager is not the one who knows the most about numbers, but the one who knows how to use data to make the best decisions.
