In today’s data-driven world, organizations of all sizes and industries are collecting a magnificent amount of data. However, simply collecting data is not enough – it’s what you do with it that matters. 

Organizations today are focusing their attention and technology investment in their data and analytics infrastructure, in addition to uplifting their Artificial Intelligence (AI) capabilities. However, and even in this advanced era, recent studies indicates that decision-makers are yet prioritizing their Gut Feeling over Data when making decisions! 

Data by itself wouldn’t have much influence over decisions if not presented in the right organizational context & narrative. 

 

We must acknowledge that numbers alone are not meaningful to us, stories are what drives our decisions and change our perspective to the world, as Daniel Kahneman once said “No one ever made a decision because of a number. They need a story.”

Data Storytelling incorporates knowledge and skills from many disciplines where data is the center point, which includes:

  • analysis of the data
  • visualization of the analysis
  • communication of the visualization

Data Storytelling = Visualization + Narrative + Context

Data storytelling is the art of using data to tell a compelling and impactful story. Data  storytellers can create a powerful and memorable message, that enables organizations to communicate complex insights to both internal stakeholders and external audiences.

However, when organizations develop Artificial Intelligence (AI) capabilities and build an engaging data story on top of it, it can sometimes fall flat if it lacks AI transparency and understandability. This is where Explainable AI (XAI) comes in.

 

Gartner defines Explainable AI (XAI) as a set of capabilities that describes a model, highlights its strengths and weaknesses, predicts its likely behavior, and identifies any potential biases . In other words, XAI allows us to understand how AI algorithms arrive at their conclusions. This level of transparency is vital for ensuring that AI systems are making decisions that align with our values and ethics.

The combination of Data Storytelling and Explainable AI (XAI) allows businesses to create insights that are not only compelling but also ethical and trustworthy. It takes the guesswork out of decision-making, allowing businesses to make informed decisions based on data-backed insights; any organization that collects data can use these techniques to inform its decision-making processes, from healthcare to retail to telecom.

  1. In the retail industry, joining Data Storytelling and XAI can help businesses understand their customers and their buying habits. By analyzing customer data, it can identify trends and develop more personalized shopping experiences for customers. With XAI, they can ensure that they are making ethical marketing decisions, free of bias that align with their values and their customers’ needs. Some examples can be around targeted product recommendations, offer discounts, and more.
  2. Healthcare is another critical industry where AI is being leveraged to deploy efficient and precise diagnoses. As per a report by Acumen Research, The Global Artificial Intelligence in Healthcare Market Size is valued at USD 7.9 Billion in 2021 and is estimated to achieve a market size of USD 201.3 Billion by 2030; growing at a CAGR of 43.4%. Using Data Storytelling and XAI, medical professionals can develop predictive explainable models that help identify individuals who might be at risk of developing certain conditions. These models can then be used to recommend preventive care and other interventions to manage the overall health of a patient. 
  3. With XAI, telecom companies can analyze network performance data in real-time and identify congestion points and other network issues. Data storytellers can then take this information and develop compelling visualizations that illustrate the impact of those issues and the solutions that are proposed to address them.

In conclusion, Data Storytelling and Explainable AI are the keys to unlocking insight and value from data. By combining these techniques, organization can create impactful and meaningful insights that drive decision-making and improve outcomes across all industries and sectors. As we move further into the era of AI, big data and data-driven solutions, these skills will be essential for any organization that wants to stay competitive and make informed decisions based on accurate data-driven insights, like identifying new business opportunities, optimize performance, improve customer & employee experiences, and reduce costs.

https://www.gartner.com/fast-answer/tech/c710c919-9399-3c42-9f9e-e7084aa20dda?ref=panel-in-disguise&refval=369562435#

https://www.acumenresearchandconsulting.com/artificial-intelligence-market