Value Creation from Big Data
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Value Creation from Big Data

4 capabilities companies need to harness big data to create value


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Fortunes are being spent on consultants and solutions to bring companies up-to-speed with the huge advances in data collection and analytics at the heart of the digital ‘Big Data’ revolution.

Before your organization joins the rush to spend yet more on big data, it is salutary to consider what really works and what management capabilities your organization needs to be able to actually extract value from big data.

New research from Keith Glaister, Associate Dean and Professor of International Business at Warwick Business School and Dr Jing (Maggie) Zeng of Kent Business School, provides useful insight. Their core finding is that it is not the data itself, or individual data scientists, that generate value creation opportunities. Rather, value creation occurs through the process of data management, where managers are able to democratize, contextualize, experiment, and execute data insights in a timely manner. 

Using detailed evidence from China, the world’s largest digital market, where many firms actively engage in value creation activities from big data, Glaister and Zeng explored how firms transform big data in order to create value and why some firms are better at extracting real value than others.

The use of big data enables organizations both to know fundamentally more about their businesses, and to translate that knowledge into better decision-making and improved performance, but unfortunately many struggle to create value from the data they hold due to its volume, velocity and variety.

What’s more, Glaister’s research reveals that the data itself does not automatically generate value for customers. It is what firms do that leads to value creation both internally within the firm and externally across the extended-data network. Data scientists alone do not maximize value creation from big data. Rather, value creation is closely associated with a collective process that transmits relevant knowledge across the firm.

There are four capabilities organizations need internally for harnessing big data to create value: data democratization, data contextualization, data experimentation and data execution.

Data democratization is capability to integrate data across the firm and enable a wide range of employees to access and understand data where it is needed at any given time. The sheer volume of data can be a challenge, but this can be alleviated when employees across the firm can benefit from extracting insights from the data. Data scientists transmitting relevant knowledge across internal firm boundaries to enable wider and collective data application is positively associated with better value creation.

Data contextualization is the ability to assign meaning as a way of interpreting the data within which an action is executed. Firms collect a significant amount and different types of data, including data on customer behaviour, market demand, shifting preferences and changing customer needs. The capability to identify the contextual clues to gain a holistic view of customers is positively associated with better value creation.

Data experimentation is the firm’s capability to promote ‘trial and error’ and continuous experimenting with the data and monitor the changes. The research suggests that a ‘trial and error’ organizational culture, when coupled with a greater level of data accessibility, tends to have a better chance to transform value from big data within the firm. Firms that put a lot of emphasis on the robustness of the data itself rather than on experimentation are less successful at extracting value.

Data execution is the capability to transform data insights into actions that lead to identification of new opportunities that increase customer engagement thus creating value. The researchers found variation in how firms execute big data insights and that the real value of big data depended heavily on the speed of the firm’s execution ability.

Beyond focusing on creating value from internal data, organizations also need a collaborative strategy to create value indirectly from their data network, where a diversified and dynamic knowledge base becomes a heterogeneous resource network that is rare, scarce and difficult for competitors to imitate. To this end, managers should seek broader potential value creation opportunities with external partners. “By being the enabler in the inter-connected data network, a firm can have more influential power in managing such an expanded network, which leads to much more sustainable value creation opportunities,” say Glaister and Zeng.

Warwick Business School is a leading thought-developer and innovator, in the top one per cent of global business schools.

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