Many businesses are investing significant resources in big data and need to maximise the value of their investments. Big data in Chinese businesses explores how accountants can make a significant contribution to that success, if they can adapt to changing business needs and develop the right skills, based on real experience in China.
There is no single meaning for ‘big data’ but broadly speaking, it is used to refer to data with the following characteristics:
Different uses of data highlight different aspects of these characteristics. The ability to process large volumes of data enables analysis of entire datasets, rather than samples, or examination of more granular data. Linking together data from different systems, or data from third parties, can provide fresh insights.
While there are many waves of new technology, big data (and associated analytics) is particularly important for accountants. Big data enables radical new business models and ways of working across and between organisations. It enables different ways of making decisions, which are more evidence-based, quicker and more automated. It can improve the value offered to customers and other stakeholders.
The most transformational way for big data to create value is through new business models, enabling entirely new products and services, or the extension of services into previously underserved markets. In China, these possibilities are greatly enhanced by extensive use of mobile payment systems, with Chinese consumers largely bypassing the card generation of technology. Mobile payment platforms provide a further source of data as well as easy integration for many O2O (online to offline) services.
Another way to generate direct value is to monetise big data, whether by selling the data, selling access to it or selling analysis related to it. Some of the companies studied in this research project featured in the report were considering this avenue, where they had data about consumer locations, preferences or activities that could be used by other companies in their planning and decision making.
In most of the companies studied, marketing and sales functions were at the forefront of using big data. Marketing departments have access to new sources of data, particularly through the internet, which provide very specific insights into customer behaviour and preferences and translate into measurable benefits, such as increased sales, increased customer engagement and higher success rate of marketing campaigns. There is also a strong competitive imperative for marketing functions to be actively engaged in data-driven techniques.
In some companies, big data was helping to optimise operations and logistics. For instance, one company described warehouse management as increasingly like science, due to the way that data and algorithms could enable extremely precise planning and processes. This allowed for optimised stock taking and organisations in the warehouse.
Big data can enable a shift from supply-led planning to demand-led planning. It becomes possible to get a much better understanding into the specific demands of the market and thereby take a more strategic and evidence based approach to business planning. This represents a significant change to decision-making approaches in some of the companies studied, but they perceived it as a big area of potential value.
This research project examines how finance functions are approaching big data in the specific context of China. While the research highlighted many universal themes, the Chinese business environment presents a particularly unique setting for studying the impact of big data.
The research project built on the experience and knowledge of the three research parties (ICAEW, SNAI and Inspur), publicly available information about China, and interviews with other experts in the field.
Eight companies were selected to study in more detail. The case studies covered both private and state-owned enterprises across a variety of industries, and all had significant experience with big data. Representatives from ICAEW, SNAI and Inspur then conducted face-to-face interviews with senior representatives from finance, IT and business functions in the companies.
This report summarises the main themes drawn from this research. While we provide only limited and anonymised examples from the businesses studied, for reasons of confidentiality, our findings are based on detailed conversations with management.