Decision Intelligence – how businesses can leverage decision analysis techs to scale up and increase profits

While Artificial Intelligence (AI) has long been hailed as the next evolutionary step in working with business data, people use it as a buzzword so often that it loses its meaning. However, actually it is a technology that, beyond human capabilities, can process and analyze huge amounts of information, creating models for future predictions. The core element that people lack in recent years is understanding how artificial intelligence affects business decision making and business growth. This is where the term Decision intelligence is brought into play.

Decision intelligence is the commercial application of artificial intelligence to stimulate profit and business growth. It enables businesses to make faster, more precise and consistent decisions.

Let’s see a few points below to understand what any business should look out for if it sees decision analytics as a promising tool.

Understanding the ultimate goal

Intelligent decision-making combines complicated and disparate data and makes forecasts built on it at a such pace and accuracy that exceeds human capabilities. As its name implies, it is used to find solutions to complex business problems in a more efficient way. However, as with any other kind of business transformation project, having a clear idea of what needs to be attained with decision analytics is vital prior to implementation.

The key is to determine what the ultimate goal is: to make the marketing campaign more affective, to ensure that the right goods are delivered to the store, or to increase the efficiency of logistics processes. These are all understandable options related to decision analytics, but to truly experience the advantages of technology, the focus must be on business results that can be measured.

Data is the North Star

Companies normally understand what they need to do with their data, the idea of using AI is of interest to them as they can imagine what benefits AI can bring. Nevertheless, being processed for a long period of time in quite disparate systems, data tends to be messy and fragmented. Because of this, many are convinced that it is necessary to spend a lot of time getting them in order first before using AI. This is often not the case. Fear of data health shouldn’t become an obstacle to start using AI.

Intelligent decision-making allows companies to work with data from anywhere, no matter what state they are in, and at the same time unite all the disparate storages within your business. When AI is applied to new and improved data sources, a holistic and predictive view of products, customers, and the supply chain can be created. This is a big task in itself, and it is important to combine data skills with the relevant platforms to assist you in building and testing AI models. Done correctly, however, it implies more than just examining past data, opening a window to the future instead.

With the help of Decision intelligence, businesses get the possibility to decide quicker on questions regarding complex data and its transforming throughout the company.

A decision analytics system must also be able to manage technology throughout the value chain without replacing elements such as existing marketing automation tools, ERP, CRM, and logistics systems. AI must create a centralized system that integrates with other business systems, uses standard data models and solutions that can be adapted to the purposes of the business.

How is Decision intelligence different from AI?

In some cases companies are not very sure about applying AI to their business procedures as they are not entirely aware of the technology capacity. Or they think that this is too big a black hole to begin to delve into it. In this case, AI serves a more important goal of achieving results. Many artificial intelligence projects are never used everyday operations. The clear ultimate goal is to help companies be among the winners by driving growth, profit and efficiency, not just getting a little smarter.

Decision intelligence also aims to be “explainable” with a clear focus on easy understanding and affordable value for every business. As the name suggests, decision analytics is highly action-oriented and goes beyond data analysis to provide suggestions and guidance on what should be done next. This is the essence of a long-standing human dream of the ability of technology to finally “make decisions with us.”

Companies no longer need to be tech giants to take advantage of data-driven decision making. Accurate, successful, and most importantly, data-driven business solutions are now available to every company.

Empowering Teams

The more data points are considered when making decisions, the more correct the decision is. Time is a priceless commodity, and time spent on the analyzes of decision-making processes can be spent better. AI frees teams from time-consuming data-intensive tasks and helps them to stay focused on strategy and development instead.

The essence of Decision intelligence is that it provides teams with the possibility to work on the results of a solution, rather than digging through tables trying to make the best on their own.

With all that said and done, the business case for adopting Decision intelligence is that everyone gets advantages from it. The commercial application of the technology is often hampered by the company: the financial side is concerned about costs, business leaders are worried about the return on investment, and team members do not understand how it works. By putting company success at the center as AI technology does, the business will see the impact Decision intelligence can have across its entire business.

Many companies from different industries are already using the new technology. Here are just a few of them:

Banking and finance

Morgan Stanley is a firm that specializes in financial advisory services and assists its clients in investments with its own financial advisors and smart decision models. Their money management platform is built with the help of smart solutions.

Based on the client’s goal, the artificial intelligence system offers winning strategies that are tested by consultants before they are offered to the client.

Lloyds Banking Group also applies Decision intelligence to make decisions in most of its business procedures. They use it to analyze the behavior of their customers, foresee their needs and problems, and make their goods and services customized.


The ability to predict more accurate prices for particular product categories based on externalities, current demand, trends and client sentiment is one of the most common but most effective use cases for analytics solutions for retailers and sellers.

For instance, Remi AI, software that helps retailers make informed pricing decisions, adapt their price policies to their clients’ purchasing power and expectations, and thus optimize their supply chain and get the possibility to predict volumes of revenue more precisely.

Health care

Enlitic Cure is a data analysis and decision-making platform built to combine the power of AI and doctors. Decision intelligence allows clinicians to analyze medical imaging reports quickly, propose a diagnosis, and assist clinicians in prioritizing treatment success.


When talking about the use of smart solutions in the energy sector, Athena AI software should be mentioned. The system provides users with the possibility to manage their energy resources better and automatically make energy and cost saving decisions. It also predicts solar energy production and optimizes battery capacity respectively.

Infopulse has created AI decision making software for Ellevio, one of Sweden’s leading operators within electricity distribution domain. With its decision engine, Ellevio can collect, structure and analyze business data from seven different sources, make detailed reports and more streamlined decisions.


Environmental issues, climate change and natural disasters caused by them are global concerns, but at the micro level they impose serious risks on a business. Among the advantages of decision analytics is the ability to predict potential risks based on historical and actual data and propose AI-assisted risk control, response, and mitigation strategies.

One Concern is an AI-powered decision-making platform that enables businesses to examine and understand the potential risks of ecological catastrophes. Through accurate analysis of climate data, they can also make better decisions about their business strategies. For instance, the hospitality industry may choose more secure place to build a new hotel, considering not only weather conditions, but also the market state, COVID-19 situation and customer demand.

The main players in the market for Decision intelligence solutions are now:

  • Busigence
  • Google cloud platform
  • IBM Hybrid Cloud
  • Oracle Business Intelligence
  • Quantellia
  • Urbint
  • Xylem



Decision intelligence is sure to become a critical tool in the business intelligence sector of the future. The advancement of human and artificial intelligence will provide organizations with more opportunities to use data intelligently, so why don’t you take a deeper look at DI possibilities and consider scaling up your business this way?

Altabel Group IT specialists will be happy to support you in this process. Let’s scale up your business together!

Julia Govor

Senior Business Development Manager