Machine learning is powerful, and the results we see from deep-learning papers are typically impressive. But can we be confident enough in them to make business decisions that have real, monetary outcomes? For any type of isolated tasks, such as learning to detect a face in an image, or classify a credit card transaction as fraudulent or not, or classify a frequently rebooting device as defective, we can usually construct the relevant low-level features (e.g., pixels, filters, zip codes, vendors, reboots, URLs) and solve the problem using conventional machine learning techniques.

It's 6:30pm, and you’re about to leave for the day. But messages start coming in, and Customer Support is scrambling with a sudden surge of end-user complaints. You come to know your flagship product has been failing to connect users and their applications to the Internet. 

Is it sufficient to digitize business operations for higher efficiency? Or does the real – and much larger – business opportunity come with digitizing products, and with creating entirely new value propositions? Read on to find out why we recommend businesses shape their digital transformation by reinventing what they make.