While many companies acknowledge that they should be using data-driven decision making throughout their organizations, there is a dearth of information about what data-driven organizations actually look like.
But there certain important traits that data-driven companies share, according to Thomas Redman, president of Navesink Consulting Group and author of “Data Driven: Profiting from Your Most Important Business Asset.”
First, data-driven companies work to drive decision making to the lowest possible level.
“Pushing decision making down frees up senior time for the most important decisions,” he notes. “And, just as importantly, lower-level people spend more time and take greater care when a decision falls to them. It builds the right kinds of organizational capability and, quite frankly, appears to create a work environment that is more fun.”
In addition, he notes that data-driven companies embrace variation in data analysis and they realize that it places high demand on their data and data sources.
“They know that their decisions are no better than the data on which they are based, so they invest in quality data and cultivate data sources they can trust,” according to Redman. “High-quality data makes it easier to understand variation and reduces uncertainty. Success is measured in execution, and high-quality data makes it easier for others to follow the decision maker’s logic and align to the decision.”
The data-driven organizations are also quicker than other companies to learn as they go and abandon data analysis projects if the evidence suggests certain decisions are wrong.
Data-driven companies do the following:
- Drive decision making to the lowest possible level
- Bring the most diverse data as possible to projects
- Use data analysis to understand their surroundings
- Appreciate variation
- Manage uncertainty well
- Integrate data analysis and its implications into their corporate cultures
- Invest in improving the quality of data
- Excel at experiments and research
- Recognize that decision criteria is variable
- Bring new data and new data technologies (big data, predictive analytics, metadata management, etc.) into their organizations
- Learn from their mistakes
While many companies are seeking to embrace the traits of their data-driven peers, the big data revolution is still in its infancy.
The problem resembles that created when Anton van Leeuwenhoek began building high resolution microscopes, says Erik Brynjolfsson, an MIT Sloan professor and director of the Center for Digital Business.
Although van Leeuwenhoek could see microorganisms swimming in a drop of water, nobody else could measure things the way he did because their microscopes weren’t as good.
“There will be a whole new set of tools that allow us to see what’s going on in organizations, between companies, even what’s going on inside people’s heads as they make decisions,” notes Brynjolfsson.
For example, MIT Professor Andrew Lo is using large data sets to create a map of the world’s financial system.
The system “is connected in ways we never anticipated,” Lo says. “We’re only now at the very beginnings of understanding how to map the system, how to map the network.”
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