Fluitec Wind: Improving Sustainability Through Predictive Analytics

The chief executive officer of Fluitec Wind needs to devise a strategy for using predictive analytics to provide gearbox services to wind turbines operated by energy companies. As gearboxes have a 10 per cent chance of failure each year and replacements are costly, predicting and preventing such failure is a constant source of stress for wind farm owners. Fluitec Wind has access to a wealth of untapped data resources that could be used to diagnose gearbox health using existing wind turbine data without the need of additional monitoring and sensor hardware. However, the company faces many technical challenges in improving the accuracy of the predictive analytics and thereby commercializing the product.

The case exposes students to the interaction between data science and business strategy. It addresses a high-level perspective of transforming data analytic capabilities into sustainable strategic advantages and choosing the appropriate challenges to be solved with data science. The learning objectives include the following:<br><br><br><ul><li>To examine how to build a business around an analysis capability, how to profit from accumulated data, how to sell predictive analytics as a product and how to identify viable big data business models.</li><li>To understand how to acquire and sustain competitive advantage from data analytic capabilities and data assets.</li><li>To analyze and evaluate data-driven business strategies.</li><li>To develop a convincing business case for predictive analytics and selling it as a product to external customers.</li></ul>The case is intended for use in Business Analytics courses, either in an MBA or MS program, and can be used both in an in-classroom setting and in an online/hybrid delivery model.

• Data analysis
• energy
• information technology
• big data
• United States