Decision Intelligence: Making Data Driven Supply Chain Decisions

Supply chain management is growing at exponential rates in the current world, and companies are constantly looking for ways to be a part of…

Decision Intelligence: Making Data Driven Supply Chain Decisions

Supply chain management is growing at exponential rates in the current world, and companies are constantly looking for ways to be a part of that growth. With the 2020 shakeup, decision intelligence has come into the show. How do decision intelligence blend features of decision management and decision execution with artificial intelligence to increase sustainability, efficiency, predictability, and positioning? Let’s take a look.

What is Decision Intelligence?

Decision intelligence (DI) is a specialized field used to enhance decision-making by clearly understanding and designing how decisions are made, as well as how results are assessed and improved through feedback. DI fills the gap between AI (which forecasts and classifies) and humans, who in many instances think in terms of doing actions that result in particular results.

How does Decision Intelligence benefit a business?

Decision intelligence (DI) is a good demonstration of how we may apply AI in the business setting to enhance decision making and, as a result, organizational outcomes. A decision intelligence framework assists businesses in operationalizing AI to complement human decision-making, allowing humans to make more confident and accurate decisions on which actions to take to achieve better results. In practice, this involves combining human expertise with the data, analytics, and machine learning skills required to construct a system that can propose the best action to achieve a goal and then ensure that it continues to deliver the optimal action over time as the contextual factors change.

Decision Intelligence(DI) in the Supply Chain

The decision intelligence mechanism in a supply chain scenario works by putting all accessible data into a centralized AI-powered software. The more comprehensive and diversified the data, the more precise and dependable the conclusion. So, for example, data should not only originate from all divisions, but it should also contain financial and behavioral data, and it should be obtained internally and externally wherever feasible. This obtained data is used by the decision intelligence software to examine different situations and, as a result, develop actions and alternatives within the framework of the business’s overall capabilities.

Businesses may counteract ineffective aspects in the decision-making process by constructing a higher level of decision intelligence. These aspects can be but are not limited to such as:

  • The amount of time required to carry out a choice, which can frequently be damaging and result in data expiration.
  • Lack of preparedness for the consequences of actions taken
  • Disconnect between decision-making phases of different stakeholders, resulting in conflicting outcomes.

So, how exactly does Decision Intelligence use the power of supply chain analytics to bridge AI and manual decision-making in order to optimize the supply chain? This comes in the form of supply chain predictive analytics being used by Artificial Intelligence (AI), producing informative frameworks that can be used to make better and more profitable decisions.

  • Managers will be better assisted by AI, allowing them to make better decisions with greater insights and more accurate results.
  • AI software, to an extent, is able to make logical and data-driven judgments on its own, resulting in improved timeliness

Why is Decision Intelligence (DI) important?

As the virtual age gets more linked, it becomes more unpredictable and complicated. As the business landscape becomes more complicated, supply chain management choices become more difficult, thus automating a portion of the decision-making procedure may help in a variety of ways.

Increase in efficiency:

The number of data that businesses may collect has grown to the point where using it to produce well-informed choices using traditional approaches is wasteful. Hours, days, or weeks may have elapsed by the time the material was given and reviewed by planners with demanding schedules. This is simply too long in today’s dynamic corporate climate, when keeping ahead of the curve sometimes requires making important choices in seconds or minutes. Even from the most extensive big-data sets, decision intelligence can deliver suggestions in a millisecond. This mix of power, precision, and scalability enables businesses to be responsive to market movements in real time.

Better use of analytics:

Because of the sophistication of data analytics, it can be rather incomprehensible to many people in the field, but many crucial choices are made by the same hands-on executives who are infrequently introduced to such deep technical knowledge. This is altered by decision intelligence. Low-skilled individuals no longer need to be subjected to such perplexing data by employing AI to analyze the figures and develop recommendations. They may save time-consuming conversations with analysts by having all projections and recommendations delivered to them in an easily understandable style.

Sales Improvement:

Decision intelligence may be effective in sales optimization by processing past sales data. Based on previous outcomes, deal deadlines, currency exchange rates, and even probable sales income may be forecasted. Data on customer behavior may also be used to assist in determining the most successful sales approaches for specific targets, as well as determine the most promising sales leads and perform risk assessments.

Improved Logistics:

It has never been more critical for organizations to ensure that their logistics operations are adequately optimized. Decision intelligence can foresee and make complicated judgments in planning using geological data, ensuring optimal production. It may also be utilized to enhance all elements of service delivery. For example, Streamlining warehouse operations for seamless dispatch procedures, or calculating and streamlining delivery routes, diverting trucks in real-time to minimize delays, etc.

Decision Intelligence, using aspects from supply chain management and analytics, works to push and enhance the entire decision-making framework.

Nuport’s supply chain intelligence and fleet intelligence provide backend calculated insights so that decision makers do not have to perform extensive analysis. All results and reports are delivered to users with simple insights in the form of a text message or a notification. This allows decision makers to be in the know at all times. Schedule a demo today!