The bigger the choice, the harder it is to choose. And the options are growing more and more in a connected and digitized world – but so are the possibilities to produce relief by means of data-driven systems.

I’m sitting in my car, which is on autopilot. I can confidently let go of the steering wheel. Should I spend the time on reading the newspaper or on checking my emails? Or should I, despite autonomous steering, still better keep an eye on the traffic? Anthony Jameson of Chusable gives a simple example for a decision that definitely didn’t exist 10 years ago. “Decisions have always been important, but they have gained much further significance in the era of Smart Production and they have also become more complex.” Thus, from experts’ perspective it grows more important to analyze and understand decisions and support people in making them.

„Those technologies, which have caused this increase in complex decisions, are also ideal for facilitating human decision-making.”

Knowing how to decide

When engaging in decisions, one has to understand their complexity first, Jameson emphasizes at the i-KNOW 2017. “There is extensive scientific literature dealing with this. Nevertheless, for example, someone designing a website doesn’t have the time to pore over all these scientific papers and studies.” Here the tool Chusapedia, developed by Jameson and his team, produces relief. “We have deposited the scientific know-how in an application. Therefore, a user doesn’t need to accomplish a doctorate, but can access that specific part of know-how that is relevant for the decision at hand.” One example: A shoe salesman offers his customers an online product configurator. Chusapedia provides the scientific respectively psychological insights for this, if existing: Which color do customers prefer, who decide for casual shoes? These colors should definitely be provided by the trader.

A network of network experts

Shopping is just one of many areas, where data-driven systems can facilitate decisions. In the scientific workshop on Social Network Analysis (RS-SNA) also systems for graph analysis, which are used at CERN, came up for discussion just as well as the analysis of election behavior in EU parliament. The workshop already was the second of its kind – that way Know-Center actively fosters the interconnection of experts in the area of Social Network Analysis. Elisabeth Lex, head of the Social Computing area at Know-Center, currently finds the biggest challenge in data security: “More and more data is made public and we are working on creating data marketplaces where data can also be purchased for use cases. The General Data Protection Regulation changes the circumstances significantly, quite a bit is still to come here.”