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360° Analytics - A Data-Driven Business Model for Retailers

This paper shows how a holistic consideration of the four drivers of digital change and the use of the 360° analytics approach can create a new, data-driven business model which delivers lasting market and growth potential.

How retail companies can leverage the opportunities of digital change

The impact of digital change on traditional business models
Retail companies as well as manufacturers active as retailers, are challenged by the new needs of digital consumers and the growth of strong competitors emerging from the digital marketplace.

Four main factors — mobility, social media, Big Data and cloud computing, drive the digital shift, which in turn raises the question: How do these four factors affect the retail business and its value chain and change the environment in which retailers are operating?

The results of a simple Google search of key terms reveal that these factors are already the subject of much discussion among the general public.

The four drivers of digital change have a 'disruptive' effect on a majority of companies, they challenge traditional successful business models. What makes things even more complex is that these four drivers are mutually interdependent and in some cases, enforce each other. This makes a holistic view inevitable. Accordingly, companies must realign themselves and initiate a transformation of many of the business processes and systems to which they have become accustomed. The sole exceptions are the 'pure players,' businesses that operate online only – like Amazon, Google and eBay.

Opportunities arising from digital change
It is important to not overlook the fact that the four main drivers of digital change also offer huge opportunities for retailers, given their close relationships with digital consumers, as long as the necessary transformative steps are taken towards building a 'data-driven business model'.

One key feature of a ‘data-driven business model’ is that it makes systematic use, across all departments, of all data that helps to achieve business targets. The crucial factor is not to be put off by the complexity this undertaking seems to pose to the organization at first sight. It is important to 'start the journey' with an open spirit, testing new solutions early on, gathering precious experience and learning quickly by trial and error.

Conclusion
Looked at critically, most of the questions listed in the data-drive business model are not new in principle. After all, the retail business has already made extensive use of data analysis in the past. What makes Big Data analytics different is that it offers significantly more extensive opportunities for arriving at considerably more meaningful answers to important questions.

The extended analysis and interpretation options now available can transform Big Data, into solid knowledge for improved decision-making and clear answers. For the first time, it is possible to do this promptly, in near real time. Easy-to-use analytical tools with extensive visualization options enlarge the potential audience for data analyses across all departments, unlocking the business benefits of Big Data analysis applications.

The digital change offers retailers tremendous potential for better meeting customers' needs. This opportunity can be leveraged and transformed into a lasting competitive advantage if the company initiates a transformation based on a 360° analytics approach and moves toward a data-driven business model.

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