In 2017 Google toppled Apple to become the world’s most valuable brand- an extraordinary achievement for a company that was less than twenty years old. Inspiring as the story sounds, would-be entrepreneurs need to be mindful of the fact that less than 10 percent of start-ups succeed. By common consensus, the single biggest reason for the low success rate is the lack of market demand for the product.

Admittedly, it is difficult to predict what can sell. After all, computers and mobile phones- ubiquitous in our day to day lives now- were both seen as novelties with a limited market when they were first introduced. Fortunately, data analytics can not only offer solutions to mitigate the risks inherent to entrepreneurship, but also create new opportunities in the following ways:

  • Elimination of guesswork: Data can help understand what is going on in the target market on a real-time basis. Thanks to advances in data analytics, market information can be mined to an extent of detail that was scarcely imaginable even at the beginning of this decade. Armed with in-depth analysis, entrepreneurs can avoid errors commonly made by start-ups, such as survey mistakes, erroneous demand forecasting, inaccurate cash flow planning, etc.
  • Understanding customer behaviour: Data analysis can generate insights to understand what the customers want. For instance, an e-commerce player can identify the source of web traffic, the most frequently used search terms, commonly sought products and even the point where potential customers abandoned their search, and tweak their webpage design or product offerings accordingly.
  • Identifying new possibilities: Analytics can throw up information that can help start-ups identify business opportunities or design promotional ideas that they may not have otherwise thought of. Companies can identify what potential customers are looking for, design promotional offers based on consumer preferences and track performance to identify what works best. In some cases, it can also generate ideas for cross selling. For example, a company selling alcoholic drinks online can use customer feedback to identify food products that can be added to the product portfolio to pair up with the drinks.
  • Prompt decision making: Business Intelligence tools can sift through vast quantities of data and identify opportunities, trends or challenges on a real-time basis, empowering businesses to think and act on their feet. For instance, a company management which receives a fresh order can assess working capital and inventory levels to decide whether it will be in a position to mobilise the necessary funds and meet the deadline for delivery on a real-time basis.
  • Future planning: Planning for the future is always a challenge, especially in a rapidly changing environment marked by a high degree of uncertainty. Fortunately, predictive analytics can use existing data to predict future trends and thereby reduce the degree of guesswork in future planning. For instance, a motorcycle dealership on the verge of closure recently achieved a complete turnaround, increasing the number of leads generated by nearly 3000 percent, using artificial intelligence.

A recent study indicates that adoption of data analytics is on the rise and the trend is not restricted to big businesses. Even smaller players are hopping on the bandwagon. In the context of business decision making, analytics is the future.

This article was written by the NUS community. If you would like to contribute your article, please get in touch.