The good news about how data can benefit businesses and how crucial it is to include data in the decision-making process is disseminated by today’s data evangelists. That’s excellent, but what exactly does that mean and how does it work in practise? What is decision-making based on data? What should a corporation do if it wants to become a data-driven organisation?

The topic of data-driven decision-making is explored in this article, along with ideas like design thinking, data sharing, best practises, and advice for starting a successful data-driven business.

Although data is informative, how can this help managers make better decisions?
On a personal level, we are aware that the more knowledge we have when making a decision, the better that decision will be. This also holds true for bigger-picture circumstances like business strategies and plans. Numerous companies have found that their chances of developing effective programmes and making the right decisions increase with increased access to trustworthy, pertinent data. Managers can reduce risks and obtain the ROI they are seeking to achieve by using data that has been well vetted.

So how can we integrate the crucial data analytics tools with the soft talents listed above? One approach is computational leadership science (CLS). The logical progression from computational social science, which examines data about people and relationships using data processing and data science methods, is CLS.

Through network analysis, simulations, AI, and other digital methods, CLS leverages these computational social science techniques to enhance leadership. Managers and other company leaders must first lead by example by adopting technology, integrating it into routine tasks, and promoting the new data culture.

Many soft talents are best characterised as instincts, gut sensations, and innate tendencies. Leaders may strengthen and give more weight to such soft talents by using the actionable information obtained from data analytics. For instance, a manager with strong communication abilities would be invaluable in getting the right teams or people the information they need.

Additionally, a manager who excels at problem-solving can use the trustworthy, carefully selected information that analytics offers to gain a deeper understanding of the problem and the resources they can use to solve it.

However, this is not simply a problem for managers and leaders. By praising and rewarding team members who utilise data effectively, managers can encourage a stronger relationship between soft skills and data. This collaboration boosts team morale and productivity and demonstrates the importance of data and analytics in today’s cutthroat corporate environment.

Managers can also start projects to teach individuals how to combine data analytics and soft skills to form teams with greater market-building capabilities (e.g., open houses, forums, and educational initiatives). Speaking of teams, competent managers should create cross-functional groups that include individuals from many fields (business, data analytics, computer science), in order to foster variety and encourage creative thinking.

Must-Read Advice for Becoming a Successful Data-Driven Manager
Following our discussion of the best practises for decision-makers, we will discuss some advice for leaders who want to develop into data-driven managers.

Encourage, facilitate, and support your staff’s attempts to upskill: Unfortunately, not every employee in the company is equally data literate. By providing employees with the time to take advantage of upskilling possibilities, generating learning opportunities, and democratising data access, leaders may foster a more learning-friendly atmosphere.
Make sure data is incorporated into all decision-making processes: Good data-oriented managers must demonstrate how they use data throughout the firm, not just talk the talk. A strong leader makes clear the goals and objectives of the firm as well as how the data culture fosters success.