How decision intelligence changes the way companies make decisions

Our hyperconnected world has become so complex that existing decision-making processes within organizations are no longer sufficient. In a study, about 65% of executives from Fortune 500 companies said that, as a result, decision-making in their organization has also fundamentally changed. The perception that high-quality company decisions are made is reported by just 57% of respondents.[i]

Moreover, human nature is not very efficient at making good decisions. Most of the time, whether we like it or not, our judgments are usually based on emotions and influenced by unconscious biases. People want to act rationally, but they can’t because they have natural limits to how much information they can absorb and process.

We also tend to settle for the minimum acceptable requirements we need to find a satisfying solution – a phenomenon that is known as “satisficing” (a combination of the words “suffice” and “satisfy”): It’s just a lot easier and faster to sacrifice some things to obtain satisfaction rather than considering all the necessary information to find the optimal solution to a problem.

What is Decision Intelligence?

Time for companies to rethink decision-making. The tool to make proven groundbreaking decisions for your business is Decision Intelligence (DI). It enables organizations to make future-proof decisions faster and more efficiently using advanced technologies such as AI, machine learning, or process automation.

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The great breakthrough is: Consideration is given not only to raw data but also to a multidimensional set of data that includes text, images, video, and audio. This way, cognitive technologies cannot only deeply analyze vast amounts of data but also evaluate their correlation, making it possible to derive reliable forecasts and identify decision needs that you might otherwise miss.

The term “decision intelligence” was first introduced in Lorien Pratt’s book “Link: How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World” before being adopted by market researcher Gartner, who has named DI one of the most important technology trends in 2022 and further developed as a strategic business tool.[ii]

How does Decision Intelligence improve decision-making?

By using decision intelligence, we can make better and more informed decisions, for example, by matching hazy feelings with validated data. Beyond that, AI-powered decision-making comes with five key benefits:

  • Identify complex interrelationships 

By 2025, there will be 175 zettabytes (ZB) of data worldwide, predicts the International Data Group.[iii] For humans, ingesting and processing such massive amounts of data is almost impossible. 

  • Make decisions faster 

Slow decision-making hinders progress and profitability. With the help of AI systems, companies can decisively shorten complex decision paths and respond more quickly to changing parameters, reducing the risk of unforeseen events.

  • Improve personal judgment 

External factors such as cognitive or emotional biases influence factual judgment. The truly optimal decision for business success is thus often overlooked. By using Decision Intelligence, we can rationalize our decisions because we can make factual judgments based on bias-free data analysis.

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  • Decisions become measurable 

Decision Intelligence elevates decisions to an essential strategy tool for sustainable business success. Based on concrete business goals and key figures, AI systems can be used to derive suitable optimization measures and future scenarios.

  • Decisions become scalable 

A company’s multi-layered data sets are usually scattered across different departments. AI-driven decision-making processes enable companies to correlate critical influencing factors from different sources and data perspectives.

What makes DI so impactful for businesses?

Every day, companies have to make countless decisions. Decision Intelligence enables you to leverage your data strategically and consistently to make the optimal decision for your business goals at any time and across the entire value chain. The reasons for this are self-evident: AI-supported decision-making can reduce unnecessary costs arising from slow processes and high failure rates, and decisions are made transparently and measurably. These reasons greatly increase a company’s knowledge management in the long run.

In other words: The ability to consistently and logically create value by reproducing optimal decisions, again and again, is the perfect ground to drive an effective strategy for reaching new levels of business growth. In particular,

1. Generating customer growth

With the help of DI-driven predictions and insights, companies can make reliable predictions about the effectiveness of their actions, identify cost-saving potential, and optimize internal processes.  

2. Increasing sales

Data-driven customer analytics allows you to identify high-value customers, deliver targeted marketing campaigns, and optimize the entire customer journey to attract new customers faster. 

3. Reducing costs

With Decision Intelligence, organizations can identify the factors that affect their revenue, predict how pricing, cross-selling, and upselling impact sales, and forecast when leads will convert to buyers. 

4. Maximize profit margins

AI-powered forecasts and trade-offs also will help you set prices and discounts or balance your staff capacity to maximize profit margins. 

How does AI-based decision-making work?

For routine business tasks, production and customer operations, an end-to-end automation is the fastest and most profitable solution. Using programmed processes, repetitive tasks and actions can be executed flawlessly and without interruption. But beyond these predefined processes there are innumerable choices to be made which require intuition, flexibility and coordination between all personnel involved.

Just like us, machine-learning systems learn from experience and independently find solutions to new and unexpected problems as they prepare the entire process from data analysis to decision recommendation. Decision makers can make the right decisions by choosing from all proposed alternatives. In other words, using Decision Intelligence never involves leaving critical decisions to machines but rather combines human experience and intuition with automation to take decision-making to a whole new level.

How can I implement DI in the company?

The number of DI users is still relatively small. Analyst Dr. Pieter J. den Hamer predicts that 33% of large companies will begin implementing Decision Intelligence by 2023.[iv] A good starting position if you want to put your company ahead of the competition.

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However, the use of AI technology in itself is not enough to outpace the competition. It usually involves rethinking your company’s culture and removing from focusing purely on IT. According to Gartner’s analysts, a company that wants to fully exploit the benefits of Decision Intelligence should make its decisions as follows:[v] 


Decisions have a mutual impact on individual personnel of an organization so the process must be much more connected at all levels. Sharing data and insights is the bread and butter of this process.


Any alternative decision being considered must be evaluated beyond the constraints of a single event or transaction.


Companies must respond to both opportunities and disruptions as quickly as possible. Decision-making is increasingly becoming a continuous process.

Companies set their starting point for using DI by analyzing the current state of their decision-making processes. At what point are the decision-making processes so complicated that they become unmanageable? At what point is there a huge amount of data but little insight? Where is the opportunity to merge multiple decision silos? Meetings, where decisions are made, should be monitored along with organizing interviews with decision-makers and asking them to explain some examples of how decisions are being made. This allows decision-making principles to be defined and decision-making habits to be identified.

Scale your business with Decision Intelligence tools

Following this and selecting customized technologies and tools will make it possible to review important use cases step-by-step before scaling the DI approach for the entire company.

This is where paretos steps in, Germany’s leading Decision Intelligence platform. The Heidelberg-based tech start-up makes analysis processes for companies as easily accessible and integrable as an email programme. With the help of AI-based software as a service tool, innovative SMEs, dynamic start-ups, and large corporations can carry out extensive data analyses without prior knowledge or the expertise of data science specialists.

Based on existing company data, paretos analyzes optimization potentials and visualizes correlations in a user-friendly dashboard so everyone can obtain in-depth insights without data expertise. Thanks to a modern user interface, all information can be managed quickly and easily. The automated optimization approach identifies new solutions faster and more efficiently than familiar analysis tools or manually calculated scenarios. This allows logistics companies, for example, to evaluate how CO2 consumption, delivery speed, and costs should be balanced to increase profit margins. To be able to do this, paretos takes on the task of combining all of the dynamic factors that make many digital organizational processes so complex today.

Among other things, the underlying software is capable of fully automating the most complex challenges in the business and marketing context today:

  • Targeting customers using personalized product recommendations, cross-selling options, and impact analysis (Customer Recommendations).
  • Dynamic pricing of products and services in response to market changes (Dynamic Pricing).
  • Efficient inventory management to optimize logistics processes in real-time (Warehouse Optimization).

Using paretos, the German e-commerce retailer SNOCKS, for example, established an intelligent price management system quickly. This allows the company to control its discount prices in a data-driven manner and adjust them according to demand. Also, one of Europe’s largest parcel delivery companies achieved a prediction accuracy of up to 95% on its expected parcel volumes after just five months of using paretos’ software. The increasing volume of available analyses and automated forecasts allows companies to create more precise deployment plans and, thus, sustainably save on operating costs while incorporating CO balance targets into their decisions. 

And this is just the beginning. Altogether, the opportunities to leverage Decision Intelligence to improve the profitability of your business are endless. Now is the time to reconsider your decision-making processes.



[iii] i



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