Have you heard of data-driven decision-making? This topic has grown in popularity in recent years and is here to stay—mainly due to its importance and the wide range of benefits it delivers.
However, to understand just how strategic the use of data in decision-making truly is, we need to reflect on how this process is currently carried out and how to select the right data for each type of decision.
Current Context of Decision-Making
Decision-making is essentially the process in which leaders or similar roles must choose one option among several alternatives to solve a problem or achieve a specific goal.
Countless decisions are made throughout daily routines, and they may vary in both complexity and subject matter. For example, they may involve people, actions, investments, strategies, and more.
However, the recurring question is: how can I know if I am making the best decision?
There are numerous types of decision-making, but the most common include:
- Intuitive: based on the decision-maker’s instinct or gut feeling.
- Values-based: guided by the individual’s personal values and beliefs.
- Rational: uses logic to select the best alternative, typically yielding better results in corporate environments.
- Collaborative: involves consulting a team and considering different perspectives on the same issue.
- Data-driven: uses company data and information, including historical records, bringing greater precision, objectivity, and accuracy.
Benefits of Data-Driven Decision-Making
Making decisions based solely on intuition or personal values can be a risky practice for organizations. However, we understand that if this has been part of the company’s culture for a long time, promoting change in this area may be more challenging.
In this case, our suggestion is to combine the use of information and data with the types of decision-making your organization is already accustomed to in its daily routine.
By doing so, you will:
- Ensure greater accuracy and objectivity, as decisions are based on facts and metrics.
- Gain a holistic view of the business, since analyzing historical data makes it easier to outline possible scenarios and identify opportunities.
- Anticipate future problems and act proactively to mitigate risks.
- Optimize processes and resources with a focus on continuous improvement, positively impacting team performance.
- Achieve a competitive advantage by making decisions grounded in behavioral patterns—whether from the market or your own organization.
- Improve the customer experience by enabling personalized deliveries aligned with the customer journey.
- Generate new insights, not only for current challenges but also for issues that have not yet been analyzed, fostering an innovation culture and promoting sustainable business growth.
This type of decision-making encourages the use of available data and information to make more assertive and reliable choices. These data may include consumer behavior, customer feedback, market analysis, investment history in a particular area, financial data, among many others.
How It Works:
1) Identify the problem or situation to be analyzed.
2) Choose which data will be considered, taking into account the decision that needs to be made and its level of complexity.
3) Collect the necessary information using a management tool or with the support of the responsible department.
4) Analyze the collected material and the available alternatives, considering the problem, possible scenarios and opportunities revealed by the data, the company’s planning and objectives, and other related processes.
5) Make the decision, preferably data-driven, since you have already analyzed the information.
6) Finally, implement the necessary actions based on the decision and conduct ongoing evaluations until the action is completed, ensuring that its results also become essential information for future decision-making.
Technology as a Support for Data-Driven Decision-Making
Technology and digital tools are essential for collecting, processing, and analyzing large volumes of data, also making visualization and analysis much easier.
Analytics Manager, an Interact solution, is a fundamental tool for monitoring corporate performance, enabling scenario anticipation and guiding decision-making more efficiently through data-driven insights.
Although it integrates with ERP and CRM systems, it can also be used alongside other solutions such as Governance Manager — for corporate governance and strategic planning; Process Manager — for process management; Project Manager — integrating project management; and Risk Manager — which encompasses risk management, among others. In this way, you centralize all data in a single place.
The solution offers customizable analyses, allowing the selection of logos, colors, and display formats, as well as intuitive, visually driven data analysis.
Explore additional benefits and features:
• Dashboards that consolidate and cross-reference data
• Improved prediction of critical decisions
• Drill-anywhere functionality: strategic, tactical, and operational
• Generate reports, scorecards, and dashboards
• Dynamic tables and interactive filters
• Graphical analysis and visualization of performance evolution
• Real-time data analysis tools
• And much more
