Machine-reengineering is a way to automate business processes using machine learning. Although machine-reengineering is new, companies are already seeing striking results with it, particularly in boosts to speed and efficiency. Studying 168 early adopters, we’ve seen speed improvements of two times or more for most business processes — and some organizations are reporting speed improvements of 10 times or more.
How do companies do it? Our study found that organizations are using machine-reengineering to establish new forms of human-machine collaboration that break through the bottlenecks of complex digital processes. In some cases, such as interpreting images or writing reports, machine-reengineering directly helps workers perform digital tasks. In other cases, machine-reengineering helps people uncover insights that are buried in a mountain of data. Here are some examples of how companies are using the speed and smarts enabled by machine-reengineered processes.
Scanning Images, Voice and Text
As companies implement digital strategies, they introduce new labor-intensive tasks to sort through all the data they’re collecting. This data is highly unstructured and produced in a variety of formats at an ever-larger scale, which requires people to arduously scan through it for specific items to complete a single process step. Human-machine collaboration focused on digital-data scanning can accelerate at least three kinds of routine digital tasks.