China’s largest ecommerce company presides over a collection of online platforms – including Tmall, Taobao (similar to eBay) and the payment service Alipay – that together create one of the most sophisticated and lucrative online retail ecosystems in the world. Contributor Paul Aldrich and Andrew Pullman authors – Building an Outstanding Workforce.

Alibaba is therefore not just an online ecommerce company. It has developed a huge combination of retail links and coordinates them online into a massive data-driven network of sellers, marketers, service providers, logistics companies and manufactures. In fact, Alibaba does what Amazon, eBay, PayPal, Google, FedEx, wholesalers, and a good portion of manufacturers do, with a dash of financial services to top everything off.

Revenues in 2018 were almost US$40 billion, with a total workforce of over 65,000. The market cap is more than US$500 billion.

Business challenge
The key challenge for Alibaba has been to create a technology-centric business across many different business sectors simultaneously. This concept of a ‘Smart’ business entails harnessing machine-learning technology to leverage data; this allows companies to adapt rapidly and dynamically, as market conditions and customer preferences change.

Drivers for this business model are massive computing power and digital data. This allows sophisticated algorithms to produce powerful output. Information is produced during real time so that market decisions can be made instantly. A result is machine learning on a huge scale, which in due course replaces human decision-making.

Solutions
So, how did Alibaba create a Smart business?

First, they automated as many operating decisions as possible using live data. Then, applying a four-step process , decision-making was transformed as follows:

1.  Every customer exchange must be ‘Datified’: in order to ensure that machine learning can take place, it is essential to capture live data. This is then fed back into the loop and the process is improved.
2.  Every activity is applied to software: All activities, including management and client relations interactions, are automated. The initial step is to build models that replicate how humans make decision.
3.  Data must start flowing: This means improving and harnessing communication, typically between suppliers and customers. As data starts flowing across the network, the smarter it becomes and the more value is created.
4.  Finally, algorithms must be applies: Models and algorithms need to be created to deal with the increase in data that is produced. This is a growing requirement for data scientists and economists, in addition to the many other new skills that are required.

Learning points
Leaders of Smart companies must mobilize huge networks to realize their goals and mission. These leaders have to be inspiring as well as visible and are often outspoken. These leaders have to be inspiring as well as visible and are often outspoken. Examples of these people include Elon Musk and Steve Jobs, as well as Jack Ma, CEO of Alibaba – not many people know who the leaders of traditional firms are.

Another key skills for these leaders is to visulaize the future, but not necessarily with a set of concrete steps. More likely, they will be able to describe what the future looks like, and how their industries will evolve in response to technological and society changes. Overall, companies like Alibaba have a distinct advantage in the digital age – they have been born online and so can adapt quickly to new business models and do not find technology intimidating or restricting.

This extract from Building an Outstanding Workforce by Paul Aldrich and Andrew Pullman is ©2020 and reproduced with permission from Kogan Page Ltd.