Big Data Adoption In Hong Kong Lags Behind Mainland China By At Least 18 Months

I was invited to speak at the Big Data and Business Analytics Forum in Hong Kong last week, and introduced our latest research on big data in Asia Pacific for both marketing and technology management professionals in the age of the customer. Listening to other speakers at the event who discussed Hadoop and explained the 4Vs of big data — volume, velocity, variety, and value — it dawned on me that there may be a significant gap in big data development between mainland China and Hong Kong. While Hong Kong is perceived as more technologically advanced, these terms were already buzzwords on the mainland 18 months ago. There are several constraints could have hindered big data adoption in Hong Kong:

  • Demographic limitations. With a total population of 7 million, Hong Kong doesn’t generate data volumes as gigantic as mainland China’s. This raises the unit cost of big data for Hong Kong businesses.
  • Budget to invest in new technologies. Hong Kong businesses are still struggling to recover from the 2008 financial crisis and maintain hiring freezes. It’s difficult for tech management to convince business leaders to invest over HK$1 million in a big data project and hire data scientists.
  • There are few local practices in unstructured data like social, location, and mobile. Hong Kong is open to global social platforms like Facebook or Twitter, meaning that multinationals can use global big data solutions to cover social in Hong Kong and keeping local adoption of big data technology for SoLoMo low.
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Service Differentiation Kicks JD.com’s Business Growth Into Top Gear

Contributed by Bryan Wang, Di Jin, and Vanessa Zeng

JD.com, the second largest online retailer in China, went public on May 22, listing itself on Nasdaq after merely 11 years of existence. At the time of IPO, JD had a market value of nearly $30 billion. Despite its size however, JD still managed to increase its customer base by 62% in 2013. How did JD manage to continually achieve business growth? I believe this is due to three key factors that differentiate JD:

■  Comprehensive logistics network for online retail in China. JD.com invested heavily in a last-mile strategy to ensure that customers receive products as quickly as possible, establishing 82 local warehouses with 1,620 delivery and 214 pickup stations across nearly 500 cities in China. This has made same-day delivery available in 43 cities — far ahead of the capabilities of Google Shopping Express in San Francisco. To better reach customers in lower-tier cities, JD is also collaborating with local convenience store chains in provinces like Shanxi and Guangdong to further strengthen its last-mile delivery capability.

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Cisco Extends Its Data And Analytics Capabilities At Its Annual Cisco Live Event

At the Cisco Live Event 2014 in San Francisco last week, we heard about plenty of updates, extensions, and new acquisitions to expand the business. The major technologies highlighted were InterCloud, Application Centric Infrastructure (ACI), and the Internet of Everything (IoE). Among these new offerings, I reveal that Cisco’s extended big data and analytics capabilities excited me the most. Why? Because its data virtualization techniques can help customers easily analyze large volumes of virtual data, no matter where it physically resides; enhanced video analytics technology could improve the customer experience when checking out in retail stores or waiting for a train; while IoE analytics and digital intelligence increase customer engagement.

  • Data virtualization supports big data analytics. End user organizations realize the importance of quickly and carefully making decisions; to do this, they plan to centralize data from different branch offices or departments. Consolidating data that resides in multiple systems and in global locations — or that is locked away in spreadsheets — is expensive. For example, telecom operators in China have hundreds of millions subscribers and need to consolidate and analyze this customer data — but it resides in 31 provincial companies. Data consolidation will be a huge and expensive project, but data virtualization technology can help solve this problem. Customers could consider adding Cisco to their data virtualization vendor shortlist, especially given Cisco’s acquisition of Composite Software last July.
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