Are nonfinancial metrics good leading indicators of future financial performance

A simple framework that plots cognitive technologies along two dimensions. (See What Today's Cognitive Technologies Can and Cant Do, p. 23.) First, it recognizes that these tools differ according to how autonomously they can apply their intelligence. On the low end, they simply respond to human queries and instructions; at the (still theoretical) high end, they formulate their own objectives. Second, it reflects the type of tasks smart machines are being used to perform, moving from conventional numerical analysis to performance of digital and physical tasks in the real world. The breadth of inputs and data types in real-world tasks makes them more complex for machines to accomplish. Depending on the type of task a manager is targeting for redesigned performance, this framework reveals the various extents to which it might be performed autonomously and by what kinds of machines. The most capable machine learning systems have the ability to learn their decisions get better with more data, and they remember previously ingested information. Mapping cognitive technologies by how autonomously they work and the tasks they perform shows the current state of smart machines and anticipates how future technologies might unfold.