What Is Decision Intelligence: Best Examples and Business Benefits?

Here is your guide on decision intelligence, its best examples, and business benefits.

Decision Intelligence
What Is Decision Intelligence: Best Examples and Business Benefits

If you have ever faced frustration over any activity due to indecisiveness, you are facing decision fatigue. Decision intelligence is a crucial topic that deals with choosing between alternatives. There is high unpredictability of business outcomes in today’s age. There are more options, choices, and models to choose from.

The onus on business decision-making is to be quick, precise, and mindful of the entirety of your business intelligence. Therefore, it is time to evolve in decision-making processes. This led to the emergence of decision intelligence to help take accurate, strong, and efficient decisions based on how knowledge-led actions can lead to outcomes.

In this blog, we will know more about decision intelligence, the need for decision intelligence, and the benefits of decision intelligence. Gartner puts data intelligence as a top trend in data and analytics.

What is decision intelligence? 

Decision intelligence helps make accurate decisions using various techniques. It is an emerging field that uses machine intelligence to design and align decision processes and models. Decision intelligence includes decision support and management in a descriptive and predictive manner. This data processing can improve the value and reduce the time taken to decide. Decision intelligence also reduces the risk of making a wrong choice.

The need for decision intelligence in today’s businesses? 

The decision-making process in businesses is mostly the same- you collect data, visualize it, find critical insights, and then use those insights to make decisions. It is a linear process that makes decisions after the data is collected and understood.

In traditional decision-making processes, the unpredictability and complexity of global organizations were not considered. There is exponential growth potential, and these old models become unsustainable. Decision intelligence helps your organization evolve with decision-making using advanced technologies like ML, AI, Natural language queries, intelligent apps, and more to create comprehensive platforms.

You can use data to find answers to questions like- if the decision will affect the company. You can make decisions based on past knowledge and future estimates.

Benefits of decision intelligence 

Here are the core benefits of decision intelligence solutions-

Helps in making data-driven decisions 

According to a survey, 91 percent of companies feel that data-driven decision-making can improve business growth. Harvesting the benefits of data intelligence for decision-making can be tough. To make better decisions, you need to analyze data and make predictions. AI and augmented intelligence can help find patterns, tracks anomalies in data to augment decision-making and influence outcomes.

Results in faster decisions 

As per the survey by McKinsey, very few organizations are happy with how they make decisions. Big decisions are often time-consuming. Multiple stakeholders are involved in any major business decision. Some members take a lot of time evaluating options, some waste time making the right choice, and others do not estimate all factors in mind. With AI systems, it is easy and possible to process copious amounts of data precisely.

Provides multiple problem-solving options 

Decision intelligence uses AI algorithms to make decisions. These processes can highlight how decisions alter outcomes. You can flexibly solve multiple problems. You can also see which aspect works best in the process. You can choose the best choice from a multitude of options, keeping goals and growth strategies in mind. At times, a business faces more problems than one. One problem can complement another one. This leads to multiple problems leading to the need for improved processes.

Eliminates mistakes and biases from the decision-making process 

In any decision, there is a chance for bias to influence outcomes. Since humans are involved, personal bias and mistakes can come in making decisions. Decision intelligence negates the influence of these mistakes and biases. The programmed algorithm manages all this and enhances accurate decisions.

Decision intelligence can help make better, smart decisions and avoid conflict in values and interests. These decisions are not prone to cognitive bias and hence can help shortlist the best outcomes.

What are the Types of Decision Models?

Here are the three types of decision models-

Human-based Decisions

These decisions are ones where humans make all the decisions. AI systems offer data visualization and insights for humans to make decisions. These processes do not make the final choice or pick.

Machine-made decisions

AI processes can make independent decisions in this model. AI systems make the decisions while humans are at the end of the decision-making process.

Hybrid Decisions

This is a model where AI systems and humans come together to reach an outcome. This type of model is where recommendations are made for humans. This collaboration of AI and humans offers better outputs since human cognitive intelligence is combined with the data of AI.

Best examples of decision intelligence in different industries 

Decision intelligence is used in multiple industries to drive resilient, sustainable, and cost-effective solutions for businesses.

Finance & Banking 

Businesses like Morgan Stanley help clients invest more smartly with intelligent decision-making. Their platform uses decision intelligence to suggest winning investment strategies for customers. Human experts then verify these plans before being suggested to the customer. Another banking group uses decision intelligence to analyze customer behavior, predict their needs, assess pain points, and customize personalized products.

Energy sector 

Athena AI is a decision intelligence application use case firm in the energy sector.  The technology helps users manage their energy resources better and ensure automatic energy and expenditure decisions. The software, through decision intelligence, forecasts solar energy and alters the capacity of the battery accordingly.

Environmental sector 

Global issues like ecological destruction, natural disasters, and environmental degradation threaten firms at all levels. Decision intelligence can predict and identify hazards keeping past and current data as the locus point. You can look at risk management solutions and mitigate disasters to an extent. Another use case is with improving decisions based on climate.

Retail 

Decision intelligence also predicts better processes for goods based on customer demand, sentiments, and trends. This is the simplest use case of decision intelligence. Many companies also create software that helps retain businesses enhance their pricing decisions and optimize their policy as per customer expectations. This helps increase revenue and align supply chain processes.

Healthcare 

Many companies use data analysis and decision-making to diagnose, examine, and assist doctors with patients. Enhancing medical outcomes is possible with decision intelligence. You can get a lot of insights on the next move of the treatment, determine prognosis better, and create better results.

How to Get Started with Decision Intelligence?

In a report by Gartner, it came to light that decision intelligence is a top strategic technology trend for 2022. You need to go beyond undefined data reports to get started with decision intelligence. Decision intelligence allows you to make informed decisions based on data. You can process this data with machine learning and augmented intelligence to come up with improved reports and analyses. This decision intelligence allows you to process better decisions and improve outcomes.

A. Commence with a process that is well-defined with minimal risk involved

Decision intelligence can help you meet market needs in an automated fashion. You need to kickstart a process that is less risky and well-defined. Companies need to be integrated with top opportunities so that they don’t miss out on what can scope of growth. You need to know why competitors are doing better and how you can replicate the same. Feedback can help improve the process.

B. Amplify complex processes involving data collection

When making any decision, you must keep data in mind. This decision can become simpler when data collection is simpler. You need to involve the right data to get the right decisions. If the risks are big, there is a chance the outcome is also tough.

If you simplify the process, the chances of better decision-making increases. This can take place with automation. You can revamp how data collection processes take place and create a defined, automated process around it.

C. Look out for biased data

If data collection is an issue like the previous point, factually correct data is another. If a company has wrong data, their entire decision set will be faulty too. The decision may be based on incorrect or faulty data making it wrong. Biased data can lead to improper results. This needs to take internal human bias into mind. You must remember that you cannot predict the future with the wrong data.

D. Have a keen interest in AI

Data-driven decisions are always augmented with technology. Technology must interact with the product to get the desired impact. A keen interest in AI will help measure risks appropriately. For example- If a clothing company wants to produce clothes in a vertical, they need to use AI to see how many users might want a specific size. AI will involve fewer people and augment with better results. You can get qualitative results with AI predictions.

E. Take baby steps to learn

It is not easy to get the best results with a single shot. You need to start with small things and learn accordingly. Many companies may be using data-driven decision intelligence without even knowing it. Though it may not be clear, it is data that is usually driving the solution. Utilizing data intelligence is possible when one learns about the process. Invest in data intelligence and create improved opportunities.

Final Words 

Using business intelligence powered by AI is a blessing for businesses and is crucial to improving business outcomes. It results in quicker and better decisions for companies. Decision intelligence processes ensure that businesses take the benefits of being data-driven.35

Companies can also drive better action by taking into account a wide array of information before deciding on the next step. Decision intelligence is the cement for a better future in any business. It helps augment the decision-making process. You can look at augmented intelligence to enhance customer outcomes and drive customer success.

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