Читать книгу Profit Maximization Techniques for Operating Chemical Plants - Sandip K. Lahiri - Страница 51

Data in its raw and most basic form is virtually worthless until we generate knowledge and business insights from it. The biggest challenge to confront the chemical industry today is how to generate business insights from these huge data banks sitting in their server and convert that knowledge to increase profit. Today every leading chemical industry talks about Big Data and Advanced Analytics and even machine learning and artificial intelligence (AI). Today's leading chemical industry is in a hurry to implement the advance analytics in their business and they focus too much on single technical components of the “insights value chain,” as we call it. However, the value creation of data consists of following five components and companies need to focus on all the components if they want to capture the full value (or any value at all) from relevant (smart) data (Figure 2.4):

(2.1)

It is important to understand Equation (2.1), which reveals that the insights value chain is multiplicative, meaning that if one single link in that chain is zero, your impact will be zero. In other words: the entire data ecosystem is only as good as its weakest component. The chemical industry needs to understand this critical concept and should give importance to developing all components and steps of the insights value chain – not focusing on only one piece and forgetting about the others.

The following sections briefly explain the function of each of the insights value chain's core components (see Figure 2.5) along with its upstream as well as its downstream steps and processes.

Figure 2.4 Different components of the insights value chain

Figure 2.5 Overview of the insights value chain upstream processes (A–B) and downstream activities (D–E)