Traditional decision-making techniques are excellent at assisting firms in analyzing historical data and forecasting the future. Questions such as "What time of year do we sell the most items, and how can we improve marketing and the supply chain to support and expand those sales and our business?" are common in such procedures.

However, today's businesses require more effective decision-making procedures. Decisions nowadays have a broader impact on the business. And data may drive choices in ways they've never been fuelled before.

Organizations may improve their decision-making abilities by using decision intelligence (DI). And there are many of them. Such firms aren't wondering what the data is showing them. And thanks in large part to their data leaders - people who can support a data-centric culture and empower workers to use data in their regular job. They're asking questions like, "What will my consumers want to purchase next year?" and "What will my customers want to buy next year?"

These firms may utilize their decision intelligence models to figure out what data they need to collect and implement tools for evaluating that data. They also make educated choices fast and track the effect of those actions across the organization by asking such questions.

Decision Intelligence does not have "a single umbrella procedure", as Pam Baker recently noted for PCMag.com. You can build totally your data and decision architecture around your business and the questions you want to answer, the data you're collecting, and the technologies you're using (or will utilize).

Regardless of how you implement decision intelligence, you'll continue to collaborate with your team to ask future-oriented questions. And more importantly, determine what data is the requirement to support those choices.

Decision intelligence best practices for data leaders

Adopting the following principles in different areas of your company can help you evolve your decision-making processes with greater intelligence:

• The main pillars will be relevance, openness, and robustness. You must deploy decision intelligence in such a way that it will have a long-term influence. Gartner advises using models that are more intelligible rather than entirely correct all of the time. Transparency is essential. Concentrate on the long-term viability of cross-organizational choices by developing models based on concepts. It helps to improve traceability, replicability, pertinence, and trustworthiness.
• Having a global perspective. The worldwide implications of both macro- and micro-decisions should be the major focus of choice intelligence at your firm. Launching a new product, for example, is a macro-decision that will inevitably touch numerous departments. A micro-decision, such as updating an essential message on a website page, must, nonetheless, be assessable for its overall impact. As soon as new analytical habits emerge, you may keep track of them and adopt them. To understand how dependencies and assumptions perform over time, you'll need to keep track of them.
• Using a cutting-edge intelligence technology stack. Reduce the number of tools you need and make sure they all operate together. It's critical that your tools have two-way communication so you can deliver data feedback regularly and automatically, as well as enhance automated models.

How business leaders can share the vision of Decision Intelligence

Business vision leaders—those driving the overall direction of the business—are instrumental in getting cross-organization support for decision architecture. Here’s how to ensure that the intelligence is applied across decisions and that the effectiveness of decisions for the organization is measured:

• Keep an eye on the decision-making frameworks. Track how your new choice frameworks affect your business if we define decision intelligence as "the discipline of translating knowledge into improved actions at any size. "Celebrate achievements and collaborate with colleagues throughout the business to enhance procedures as required.
• Lead with a big picture in mind. Business executives should "ensure that peers and direct reports look at the 'big picture,' the 'Global Outcome,' while constructing a decision model," according to Gartner in a 2020 research titled “Improve Decision Making Using Decision Intelligence Models. ” Even extremely localized decision models should always contribute to the wider picture and be incorporated into an existing decision-making architecture, according to the concept of providing a global outcome."
• Early on, enlist the help of stakeholders. Include the stakeholders who will be directly impacted by new decision models from the outset, have business executives give input and teach them about the models' transparency, and make sure your models prioritize explainability above aggressive correctness. Because business executives who understand the models are better able to secure buy-in from the rest of the organization.

Dataflake as a source of decision intelligence

Here are some examples of how Dataflake may assist your organization to drive decision intelligence:

• No-code tools. Transforming highly technical functionalities into visual tools, Dataflake allows users regardless of technical skills to quickly dive into data visualization without the high learning curve when working with SQL and data visualization
• Advanced data visualization configurations. Convey the details of your data report better by designing your charts and report elements to the details needed. Each element in Dataflake has been designed to solve all complications when detailing a chart to visualize the message you are trying to project through data. 
• Speed up the time between report development and data evaluation. With faster completion time thanks to Dataflake no-code tools, your teams will be able to eliminate all frictions in the data report process to speed up the delivery time. 
• Make better data-driven decisions.  Dataflake exceptional data visualization customization helps your organization to quickly understand the bigger picture of the data they’re working with while still being able to analyze into details of all data. Your organization's management will confidently arrive at more accurate decisions without taking up too much time dissecting the report.