What if you could learn from your mistakes without ever actually having to make them?

The science is clear.  The decisions that humans make are never linear.  It is multidimensional and directional, is full of biases and shortcuts and it is rarely fully rational.  The process, when visualized, looks nothing like the well-recognized ‘decision tree’.  Using linear tools and statistical or ‘finite state’ models  (LLM) to augment decision making yields rapidly diminishing returns-as many have experienced using recommendation engines or current AI enabled services.

Relying on n-dimensional graph structures which emulate the human mind’s process of information organization and dissemination, DecisionArts enables brands to engage with a greater degree of hyper-personalization, utility and relevance at scale. 

 Decision science is an interdisciplinary field that relies on a broad range of quantitative and qualitative disciplines and tools to effectively evaluate and understand how decisions are made.

 This discipline combines tools from statistics, economics, psychology, neuroscience, physics, and data science.  Decision scientists help organizations to identify, prioritize, and act upon opportunities and challenges, often using data-driven techniques to predict outcomes and measure the risks which accompany those possible outcomes. 

 In essence, decision science aims to understand the often-opaque process of decision making and improve that process through the betterment of outcomes.

 Whether for an individual or within a corporate or governmental context, decision science attempts to provide a structured framework to assist in balancing judgment, experience, and evidence inputs while removing often hidden biases.

 It's about making informed and rational choices based on the analysis of complex data and the application of sophisticated models which can simulate potential outcomes.

 This is DecisionArts’ focus.  Our GNN (hybrid Graph Neural Network) knowledge graph, called FELIX, follows many tested and emerging decision science concepts and structures.

 DecisionArts is a Decision Science middleware application company focused on improving the quality and outcomes of end-user decisions across a variety of industry categories. 

 Our focus is helping commercial brands win in marketplaces where differentiation is difficult,  substitution is rampant, friction is high and customer acquisition and retention is expensive.

 DecisionArts identifies where optimal, yet hidden linkages between brands and consumers exist and the intelligence on what action to take.

 The field of decision science is particularly valuable in areas where stakes are high, and the consequences of decisions are significant.  We understand this and coined this phrase, which represents the value provided by DecisionArts and our knowledge engine, FELIX:

“What if you could learn from your mistakes without making them?”

In the upcoming series of articles here as well as , here on LinkedIn, the DecisionArts team will break down in bite-sized chunks how decision science intersects with artificial intelligence and outline DecisionArts enhanced approach to solving commercial problems, beginning in the CPG space using FELIX, DecisionArts’ Knowledge Engine, FELIX.