Читать книгу Profit Maximization Techniques for Operating Chemical Plants - Sandip K. Lahiri - Страница 57

Once we have extracted important insights from the models, the next crucial step starts: turning these insights into action in order to generate a business impact. An example would be when a predictive maintenance model gives you warning as to when a compressor or some asset might break down, but maintenance is still required. It is very crucial to understand that just knowing the probability of a breakdown is not sufficient; prevention, not prediction, is the key to business impact. Turning insights into action thus requires two things: first, to understand the insights coming from the data analytics and to know what to do. Second, even once it becomes clear what action needs to be taken, success will depend on when and how that action is taken. This step is very crucial. Knowledge generation by data analytics software is not sufficient; taking corrective and preventive actions from these insights is the key driver for business impact.