Traditional decision making is broken
Our interconnected world has become more complex than ever before and, according to 65% of senior executives in Fortune 500 companies, so have business decisions. Many organizations’ efforts with making decisions to efficiently plan ahead are falling short, because they are:
Narrow
Human nature has given us inherent limits in the way that we process information and studies prove that decision-makers use only 22 percent of available insights.
Isolated
Far too often, decisions are being made without considering all relevant variables that could effect them – which is a common result of a siloed company culture.
Untimely
If companies use data as a base for their decisions it normally happens on a periodic basis – and that only restricts their chances of capturing sustainable opportunities at the right moment.
We need to re-think our approach to decision-making by promoting a peaceful partnership between humans and machines. Decision Intelligence combines the best of both worlds – artificial intelligence recognizes complex interrelationships whilst human intellect and creativity actually do the work of interpretation – to give “superhuman” powers to decision-makers.
The best of both worlds
Decision Intelligence uses a wide range of data, analytics and AI technology to help humans evaluate complex data and predict alternative solutions.


Support
Human-centered decision-making based on experiences, reasonings, emotions and/or responsibilities backed by insights and data visualizations.
Example: Medical Diagnosis
Augment
Collaborative decision-making between humans and machines using machine-generated recommendations for human verification and further processing.
Example: Financial Investment
Automate
Autonomous decision-making based on data, machines and algorithms to generate predictions or scenario simulations leaving humans to conduct mere risk management.
Example: Dynamic Pricing
How to shift from “I feel” to “I know”
Turn your data into actionable insights
Do you find your company data a little overwhelming? We completely sympathize. There’s terabytes of data out there, but how do you derive insights that actually benefit your business?
In AI-driven decision processes, we are able to analyze and correlate combinations of historical data and a wide range of information from various sources. Based on this information, it is possible to not only identify concrete decision-making needs, but also present alternative solutions and forecasts that allow everyone to make confident decisions instead of uncoordinated choices.
Embrace the power of AI to see the unseeable
A lot of us tend to vastly underestimate the scope of possibilities that AI technology opens up, especially to businesses. But what you think you already know is just the tip of the iceberg.
AI-models alone can process the huge volumes of data that a company gathers over time. Its ability to correlate multiple factors and identify patterns unveils immense opportunities that would otherwise be missed. And these benefits will even grow as your company becomes smarter.
Supercharge your judgement knowing every possible scenario
Decision-making in a company often is a foggy affair: thought-processes are led by calculations, gut feeling, or implications, while leaving out crucial impact factors.
AI models are trained to weave together all relevant factors and variables in order to generate a series of optimized forecasts and future scenarios to help you fully understand their interdependencies and enhance your ability to make the best possible decision.
Scale Decision Intelligence across your organization
Congratulations, you laid the groundwork for making your company future-proof. Now it’s time to empower your entire organization to take the leap into the era of Decision Intelligence.
Paretos is there to help you make the shift: Our easy-to-use platform enables your teams to access and integrate analysis processes even without prior data science knowledge. Thanks to the fully automated workflow, there is also no need for manual iterations which makes the models scalable incredibly easily and quickly.