Forgetting the human element
Likely the most central thing in building data-driven digital services. While data analytics offer better guidelines for informed decision-making, humans are needed to ensure the correct course of action is taken — at least before the introduction of Broad (or at least broader) AI.
While basing decisions on conclusions drawn solely from nice, logical data sets may feel very tempting, the “soft” elements with human interaction should not be forgotten. Talking about data, there are two central elements crucial to success, from the human viewpoint.
Firstly, data visualization. As with many emerging technologies, data-driven applications can easily be too engineer-y — to put it simply. In most cases, your users are not data analysts. The core aim of data visualization is to make information accessible and easy to understand — a point that can quickly fade away when data masses grow and new dimensions are found. Developing data-driven services is no different to developing any other services — always build together with your users. Data visualization is a topic we could ramble on about endlessly (which we will, in another post dedicated solely to that). But for now, to achieve the most from your data, you want to keep information accessible, usable and limited enough to your users.
Secondly, human decision-making. While data is vital for business automation, decision-making will remain largely a human activity — by its very nature, as analytical automation tools can only make decisions based on the data they read (again, point 1: datasets rarely cover all aspects). Data and analytics are a superb tool for humans to make informed decisions, by adjoining them with emotional intelligence.
Coming back to the wedding-themed mishap of Pinterest, human oversight and data enrichment could have just prevented this communicational error from happening. Emotional intelligence and human decision-making combined with their vast user data could have been able to produce more accurate and appropriate messages. The automation, reading only data it was given, did not know these people were not necessarily going to get married — but humans would have.
To conclude, data, analytics, machine learning, and AI are all tools inevitable for modern businesses to thrive — but like any other tools, they have their limitations. By acknowledging these limitations, these tools can and will disrupt the automation capabilities of your business.