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By 13 May 2015 | Categories: Misc

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By Jaco Barnard, Head of Retail at Wipro Ltd, South Africa

The retail environment today is progressively dynamic. With increased competition, higher customer expectations and a growing number of customer touch points and channels for engagement, the need for business agility has never been more critical. Hindsight is no longer sufficient, as competitive advantage is driven by those retailers who are able to respond better and faster to the demands of customers and to rapid shifts in the market. Therefore, predictive analytics and the ability to harness big data are extremely essential in providing the retailers with valuable customer insights, to drive performance improvements and competitive advantage in an increasingly data-driven world.

While many retailers have invested in analytics solutions, the perceived challenge of big data means that these tools are not being utilised to their full potential. With data being generated faster than ever before from an increasing number of sources, many of them outside of the traditional structured channels, reactive analytics such as Business Intelligence (BI) and after-the-fact reporting do not provide the required level of insights. Successful retailers demonstrate that strategies driven by analytics deliver strong and measurable results. However, the point to be noted is that while technology is essential for tapping into big data to generate valuable insights, it alone is not sufficient. Truly leveraging predictive capability requires a shift in mind-set and the integration of analytics-based processes and culture throughout the enterprise.

Predictive analytics delivers insights that would not otherwise be available to retailers, enabling them to act on accurate information with enhanced decision-making ability. It allows companies to extract historical information and identify patterns based on an action taken or event that occurred. This information can then be used as a base or benchmark for future decisions and predicted outcomes. For example, retailers wanting to use historic data to balance their volumes margin objectives through strategic pricing could review past events where they dropped the price of their products by 5% and later 10%.  A 5% decrease in price might not have resulted in the same high volumes of sales in comparison with the 10% decrease in price. However, the lower profit margin obtained with the 10% decrease in price, despite higher volumes being sold, meant that profits overall decreased.  This demonstrates the ability to predict outcomes based on contextual historical data. With this ability in place, problems can be solved quickly and initiatives can be taken that provide a first mover advantage, something that is essential in a dynamic retail environment. An analytics-driven environment can aid retailers in maintaining and driving customer relationships.

For example, often a small section of customers is responsible for the majority of sales, and these relationships need to be nurtured. However, without the ability to effectively analyse vast data, retailers would never be able to determine who these high value customers are.

Such insights can be used to develop changes in the business strategy leading to dramatic business improvements and profitability This includes a number of operational benefits, like improved margins, enhanced levels of customer satisfaction, increased market share and more. In addition, predictive analytics offers a number of tactical advantages, such as improved planning accuracy, higher customer retention and enhanced conversion to sales for advertising and promotional spend.

Top-level leadership is essential in driving analytics, and it is critical to break down traditional siloes between departments. Only with a holistic, integrated and single view across the organisation, will insights be accurate enough for predictive capability. Ultimately, the goal is to leverage analytics capabilities to solve problems, predict outcomes and deliver results. With these abilities in place, retailers will be able to drive revenue growth and profitability while ensuring customer loyalty and enabling innovation that is critical to competitiveness today.

In a data-intensive retail market, insight is the singular driver of competitive advantage and analytics is integral in delivering this insight. Without the ability to make accurate forecasts and enable agile decision-making, retailers will not be able to serve/satisfy the evolving consumer demands, and will eventually lose out to the competition that is able to do so. Retailers that are empowered to leverage and embrace the power of predictive analytics and big data to gain insights, will be well prepared to deal with the challenges of a dynamic business environment.

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