Use cases of Decision Intelligence
Decision intelligence / July, 06 2022

Benefits and Use cases of Decision Intelligence

In the DI series, here is the third blog. In the previous blogs, we discussed why businesses need Decision Intelligence and the differences between BI and DI. Let’s look at some industry-specific use cases and the benefits of DI here. We recommend reading the blogs mentioned above to comprehend Decision Intelligence fully. Let’s get into the specifics.

Businesses now recognize the need to make high-quality decisions to maintain a presence in this competitive market. A single wrong decision can have a significant impact on a business. These are the crucial variables that lead to companies making poor decisions. They are,

  • Inadequate data
  • Inefficient data processing
  • Bad decision-making

To avoid insufficient data, organizations must strengthen the data collection infrastructure and utilize all sorts of structured and unstructured data. Enterprises must adopt technological innovations and strategically build their workforce to improve data processing. 

To make high-quality decisions, you must follow the above two processes and have an intelligent system to assist you. Decision intelligence can act as that intelligent genie all organizations aspire to have, to assist them in making the right decisions and helping to gain a competitive advantage in a fast-changing market.

Benefits of Decision Intelligence

Decision intelligence gives you the superpower to make impactful business decisions, combining multiple decision-making techniques and models. Gartner predicts that by 2023, 33% of the organizations will exercise DI. By incorporating decision intelligence in your decision model, you will experience the following benefits,

High quality and less time – Big decisions take time to make and involves many stakeholders. Some might spend much time studying possibilities, some invest time making the appropriate choice, while others fail to consider all aspects.

DI provides access to all the necessary information and tools that you need to make more informed decisions based on sophisticated data rather than hunches or gut reactions. Furthermore, decisions made using decision intelligence technologies take less time to complete since they do not need hours of study or many stakeholder meetings as the essential information is already available easily.

Enhanced accuracy – When people are involved, personal prejudice and inaccuracies might occur while making decisions. Decision intelligence mitigates the impact of these errors and biases. The programmed algorithm takes care of all this, improving decision accuracy. Decision intelligence can assist in making better, more informed decisions and avoiding conflicts of values and interests. These decisions are not subject to cognitive bias and can thus aid in narrowing down the best outcomes.

When you adopt decision intelligence tools to support your decisions, you can alleviate much of the trial-and-error process and spend less time on things that don’t work out. It will enable you to concentrate on possibilities that will impact your company more.

Bias recognition – We make choices driven by emotions, prior experiences, or other factors that aren’t always logical. While these biases can help us make quick decisions in some contexts, they can also lead to huge blunders when we aren’t aware of them. Decision intelligence can help you detect your biases, so you can account for them when making crucial decisions.

Reduces Dependency – It cuts off the need to depend on analysts to create reports and dashboards and provide insights to the stakeholder. This method limits the performance of the data by answering only a few business questions. With DI, the stakeholder himself can get the insights and recommendations that provide limitless opportunities to make high-quality decisions.

Monitoring and scalability – The continuous monitoring capability of DI makes it proactive, outlier detection and provides a personalized experience to the user. DI considers billions of data points to decide. Organizations need a scalable system as the data is growing exponentially. For this reason, DI has a scalable, robust, high-speed analytics engine, compute framework and security/access controls.

Where should organizations use decision intelligence?

Organizations make a wide array of tactical, operational, and strategic decisions. The degree of machines involved determines if DI will support, augment, or automate a decision concerning speed, complexity, and scale. While we know of DI’s three-level assistance, the DI support is provided by analytics/BI for tactical and strategic decisions with low speed, complexity, and scale.

Data science for decision automation for tactical and operational decisions with medium to high speed, complexity, and scale.

Decision Intelligence for decision augmentation, for organizations, to take tactical, strategic, and operational decisions with low to high speed, complexity, and scale. It assists people in analyzing millions of data points and discovering hidden relationships that would not be discovered otherwise or delivering predictions and patterns that humans cannot discover.

Industry-agnostic use cases of DI

Decision intelligence transforms organizations by ensuring optimal performance in critical areas such as sales, marketing, store management, talent management, and much more.

Marketing – A strong brand results from meticulous planning and analysis across various touchpoints. Marketers can quickly discover high-performing initiatives across multiple channels from social media to email and optimize ROI for each campaign by employing decision intelligence tools.

Sales – It would be best to have real-time insight into your prospects’ preferences and how they want to get information about your products or services to create leads for your organization. You may get valuable insights from consumer data with decision intelligence technologies and utilize them to adapt messages, enhance conversion rates, and raise revenue.

Store management – Making accurate inventory levels and pricing decisions is crucial to ensuring retail profitability. Retailers may use decision intelligence tools to optimize pricing strategies and inventory levels based on demand patterns, ensuring they satisfy consumers’ demands while optimizing profit margins.

Talent management – Today, organizations receive a pool of resumes when posting a job opening. Recruiting talented people can be one of the most difficult tasks for your organization if you have limited resources. However, you can use decision intelligence software to examine candidates’ data and provide suggestions based on their profile and previous accomplishments. DI enables recruiters to concentrate their efforts on individuals more likely to succeed inside their firms.

Supply chain – Supply chain is one of the essential areas of an organization as it maintains the continuity of processes. DI can do wonders like

  • Automated Root Cause Analysis of Defects or Delays
  • Inventory Optimization
  • Demand Forecasting
  • Supplier Performance
  • Monitoring
  • Quality Analytics

HR – DI can assist with ad hoc analysis metrics like headcount, attrition, compensation, incentives, etc., making it easier for the HR department to perform the tasks.

Industry-specific use cases of Decision Intelligence

Healthcare sector – It is feasible to improve medical results with DI. You can gain much insight into the next step of the treatment, better predict prognosis, and produce better results, giving doctors a superpower.

Environmental sector – Decision intelligence can forecast and detect vulnerabilities based on historical and present data. We can predict climatic conditions with better accuracy with DI. It helps you avoid any disaster and arm yourself.

Banking and Financial sector – Decision intelligence can study consumer behavior, demands, and pain spots and helps organizations customize customer solutions. Customers can benefit from DI’s outstanding investing techniques. Human specialists then validate these strategies before recommending them to the customer.

Energy sector – DI assists users in better managing their energy resources and ensuring automated energy and spending decisions. DI can anticipate solar energy and adjust the battery capacity accordingly.

Insurance – DI can perform policy underwriting, risk modeling, and fraud detection, helping organizations process genuine requests and maintain maximum security.

Decision Intelligence has an ocean of benefits and use cases. Every organization can incorporate DI in their decision model and start their journey toward being a successful organization.

To get started with decision intelligence, contact us here.

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