Asian companies need an efficient supply chain ecosystem, exec says
A recent survey that NTT Communications conducted has revealed how Asian retailers, manufacturers and wholesalers are investing in disruptive technologies.
The survey, "The Digital Silk Road to Success", found that nearly 80% of business and IT decision-makers at large corporations based in China, Hong Kong and Singapore are generally positive about the business outlook in the next 12 months.
This is all in spite of current challenges including talent shortages, rising wages, price pressure, increasing costs and competition.
To overcome business challenges, 94% of organisations surveyed say that plans are already in place to deploy two or more disruptive technologies, accelerating digital transformation.
Raymond Ng, vice president of Vertical Solutions at NTT Com Asia, says the success of retail, manufacturing and wholesale industries relies heavily on an efficient supply chain ecosystem.
"Asian companies have extensively applied IoT and big data to capture real-time business intelligence from all the touchpoints, and overcome business blind spots in the ecosystem," explains Ng.
"Though combining IoT and big data is far from new, it is the recent extensive application of these disruptive technologies that is proving to be a game changer for the supply chain.
Out of the organisations surveyed, 50% rated stringent data security and compliance regulations, legacy IT and the complexity involved in sourcing suitable technologies and supplier for the job are the top three road blocks.
And, to accelerate business transformation, over 60% of respondents would choose to outsource transformation projects to reduce deployment time and cost, and tap cross domain expertise from suppliers.
"Strategically selecting a mix of disruptive technologies to overhaul the supply chain is only the first step of a successful digital transformation journey," adds Ng.
"It all comes down to three important determining factors – the readiness of infrastructure, connected technology and people to make sense of data to derive actionable business intelligence.
