New business strategy in the age of large data

Deloitte, in its latest http://www.aliyun.com/zixun/aggregation/14294.html "> 's Big Data Report, a new business strategy for the Big Data 2.0," points out: in the face of big data opportunities, Business leaders should take the initiative before the crisis arrives, rather than coldly wait and see, missed fighters. Deloitte believes that business managers should be aware of the three types of application and business value of large data when weighing the pros and cons of large data:

1. Answer known questions about existing business and focus on improving performance and operational efficiency.

2. Answer new questions in existing business and focus on business growth opportunities.

3. To answer new business questions, the goal is to rewrite the competitive landscape.

At present, large data applications in most enterprises still stay in the first phase of the application: answer the existing business known problems, improve performance and operational efficiency, that is, the so-called large data 1.0. But Deloitte believes companies should begin to pay more attention to the second type of application of Big data: answer new questions from existing businesses and focus on growth opportunities.

Deloitte, which recently surveyed more than 100 CIOs from more than one industry, found that knowledge discovery based on large data applications would be one of the three most disruptive enterprise-class technologies of the 2013, just after cloud computing was deployed and moved.

In a 2010 survey by The Economist magazine, when asked about new opportunities for big data, 51% of respondents first mentioned "improving operational efficiency", while the number of people choosing "Service and Product innovation" ranked only fourth (24%).

Deloitte's ComfortDelGro, a Singapore taxi operator, describes how companies evolve from large data 1.0 strategies to large Data 2.0. (Editor's note: How to use large data to solve urban road congestion and the problem of taxi, may be an extension of the discussion topic,

Big Data 1.0: new technologies to support business expansion

Initially ComfortDelGro's booking service was manually completed by telephone, and then, as the number of customers exploded and the artificial telephone service was blown up, the company began investing in large data technology, investing 60 million of dollars to develop a taxi booking system made up of automatic dialing systems and smartphone applications. The backstage data infrastructure supports a number of 100,000-meter trips, 15,000 taxi operating data, and 1 billion real-time GPS location information.

New business strategy in the age of large data 2.0

Reinventing customer Behavior:

With the continued growth of population and Tourism in Singapore, the peak of the number of car rental bookings per day or per week has continued to increase, in order to ease the peak period of taxi, ComfortDelGro collected many years of taxi operating data, adjusted the pricing strategy, Through the price lever (increase) to adjust the specific period and region of booking requirements, but also to the company's service quality and service experience can maintain a relatively stable state.

Create new products and services:

By analyzing the large number of taxi operation data, we recommend the best route forecast service to avoid congested sections at different time and place, this service can not only help ComfortDelGro taxi drivers to forecast business volume and traffic condition, but also can sell to other company's taxi drivers as third party value-added service.

Data Ecosystem Integration:

From the point of view of the large data ecosystem, the best route service is a large data ecosystem consisting of multiple data sources, and entities such as taxi operators, traffic management, land and environmental protection departments can provide complementary data in the field of transportation intelligence. The data include Street View images, real-time weather and road conditions, taxi-run data, etc. The parties that provide data also benefit from large data ecosystems. The regulators want to reduce congestion, which means more revenue for taxi companies and less carbon and haze for the environmental protection sector.

(Responsible editor: The good of the Legacy)