One of the biggest frustrations of most companies is, in an age with so much information at hand, to continue to make decisions based on intuitions, past experiences or considerations. After all, shouldn’t data provide more assertive paths?
Data-Driven Management has emerged to address this problem and have ensured remarkable advances in team management. Find out a little more about it:
What is Data-Driven Management?
Data Driven Culture, or Data Driven Culture, exists when a company organizes its processes and metrics based on the intelligence extracted from its database.
Data-Driven Management is one in which decisions are driven by data, statistics, metrics and numbers. This means that the judgment of actions becomes less subjective, gaining the objective basis of the data.
How is Data-Driven Management?
Not all people are prepared to manage data-driven teams. There is a basic scope of activities that managers need to bring together to do it. Some of the main activities that should be put into practice are:
- Raise the correct metrics
“There is a difference between numbers and numbers that matter”
Jeff Bladt and Bob Filbin in a column published in the Harvard Business Review.
One of the most important steps to start making data-driven decisions is to define which metrics are important. Good metrics are those consistent, easy to collect, and that decisively influence business results.
Data may come from different sources and it is necessary to define which one is best suited to nourish a base. Satisfaction surveys, reports commissioned for specialized companies and software like Zoox Smart WiFi are some of the most common data sources.
- Ask the right questions
While the analysis of quantitative statistics is done by data analysts, it is up to the managers to ask the correct questions in order to find the answers necessary for the business. In an article published in 2013, Thomas Davenport lists six questions that must be asked through data analysis:
- What was the source of this data?
- How well do these data represent the population?
- Does this data include exceptions? How do they affect results?
- What are the premises behind these data? Could some conditions invalidate this data and assumptions?
- Why did you decide on this specific approach? What alternatives did you consider?
- What is the probability that independent variables influence this result?
- Know the basics about Data Visualization
Not everyone needs to be trained in Statistics, but basic data visualization is required to work with Data-Driven. Interpreting charts, knowing how to do them, dealing with variables, distributions, exceptions, comparisons, all enrich analysis and help transform the database into a management friend’s best friend.