Our approach to building a data exploitation strategy delivers two main areas of work. An understanding of what data you should be collecting, and an understanding of how this data can be leveraged.
We start by clarifying your business goals and strategies, so that we can map out where your greatest areas of impact are found across your processes, data, and decisions.
With that understanding we investigate with your business people what is (or what could be) observed and recorded as information and data, which we then audit and characterise. Once we know what your data assets are, we can identify areas of opportunity where machine learning and decision automation can add the greatest value to your strategic objectives.
The result is a targeted list of data to collect, or data gaps to address, and a qualified list of hypothesis to be tested. If the tests prove valuable, then the strategy is to industrialise them.