Big Data Requires Creative Analysts and Strategists

Big data is one of the biggest buzzwords in the recent years. Due to huge publicity by Mckinsey Company, IBM and many others, the topic had generated a lot of interest among marketers. However, not many people know how to implement big data successfully and even fewer gained competitive advantage working with big data.

Poor problem definition leads to poor insight

Without defining the problem, it is very difficult to decide what to do with the data. As a result, many analysts are just contented in plotting fanciful graphical representation of the data that does not add much value to the business. In fact, Thomas H. Davenport, a leading expert in the field of analytics had been quoted “big data often equals small math”. Visualizing data alone is not enough. It is more important to solve business problems.

Creativity is the most important trait of analysts and strategists

Many analysts and strategists would argue that their work is grounded in real science and creativity is best left to the design geeks. This concept is totally wrong. When dealing with big data, finding creative use of data for other purposes other than the intended use cases is often what that unlock values and create insights for companies. In the few examples, we can explore how can data be repurposed for other unintended usage.

Land Transport Management

Telco data can be used for many other unintended purposes and a quick illustration is using it to manage roads. The data can show the position of travellers and can be used to figure out the actual flow on roads to optimize traffic flow. Other signals such as accelerometers data in smartphones can be used to detect uneven roads for future work. Using a little bit of creativity using the same data, Telco can also form alliances with banks to inform them of changes of habits in their customers such as visiting car dealers location, changing night location (new home address) etc. to facilitate sales.

Retail data and insurance

Banks and merchants have studied retail data almost to death but they mainly do so to understand and drive conversion of retail sales. However, such data is very powerful for insurance companies as well as the purchase patterns of consumers are actually very good predictor of life span.

Search data to understand sentiments

Social sentiments are often used by analysts to understand sentiments of their customers. However, such sentiments are often skewed as only the very vocal people actually voice their opinions publicly. There are many more people who keep quiet about issues. To understand the latent sentiments, studying how people search can be useful. The results can be used to predict actual sentiments and to validate social sentiments.

Summing all up

To sum everything up, visualizing data and crunching numbers cannot replace good old thinking skills. In fact, the bigger the data get, the more thinking we should do. Only when we find creative use of data that nobody else can think of can we unlock values and gain competitive advantage.