Reference no: EM133099833

Procter & Gamble (P&G), the multinational consumer goods corporation, is regarded as one of the earliest FMCGs (fast-moving consumer goods) to adopt big data and digitalisation initiatives. The company collects large volumes of different types of data from its customers, factories, production activities/sites and supply chains to facilitate quick decision making and become more productive and efficient. The company's growing data volumes in the early 2000s led to the decision to adopt Hadoop. This intervention helped the company make
quicker and more informed data-driven decisions that were utilized in different areas such as:

Devising adaptive pricing strategies, developing bespoke marketing techniques for different clusters, responding to customer feedback in a timely fashion, developing new products (and product innovations) through simulations and reducing stock by forecasting demand.

(a) Which core components of Hadoop may have benefitted P&G in its big data initiatives compared to traditional storage/processing methods and in which ways?

(b)How can P&G use IoT (the Internet of Things) to make its factories 'smarter'? Discuss and provide some practical examples of how connecting different devices/machines (or using sensors) may have tangible business benefits for P&G.