Date
12 December 2018
Companies that set out to build an overly comprehensive data platform could end up wasting a lot of resources as they don’t know what sort of data they really need. Photo: Bloomberg/Facebook
Companies that set out to build an overly comprehensive data platform could end up wasting a lot of resources as they don’t know what sort of data they really need. Photo: Bloomberg/Facebook

Some misconceptions about digitalization

With a digitalization roadmap, companies can strengthen their data capability for a more scientific decision-making process.

As different companies target different customer groups, they should also have different roadmaps.

Based on my experience, there are a few common misconceptions.

Companies that set out to build an overly comprehensive platform could end up wasting a lot of resources as they don’t know what sort of data they really need.

The right design for data infrastructure can’t be achieved overnight; it is a process of incremental optimization.

A better way is to constantly improve the data platform based on actual use.

Another common mistake is not being able to appreciate the importance of external data, which could play a supplementary but crucial role.

Regular review of data assets would help the management understand things like the relationship between data and their applications, what sort of data is often used and what sort of data is most scarce.

Meanwhile, the importance of a specialized system and automation cannot be overstated.

Without that, it would be hard to ensure the quality, practicality and security of data.

If you believe data economy is the future, data strategy should form part of the overall management strategy.

This article appeared in the Hong Kong Economic Journal on Nov 27

Translation by Julie Zhu

[Chinese version 中文版]

– Contact us at [email protected]

RT/CG

Venture Partner of Sequoia Capital China, former head of the data committee and vice president at Alibaba Group.

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