The potential of advanced analytics and AI in retail

The further and more reliably companies can see into the future, the better they are able to make strategic decisions and ensure their long-term success. Certain uncertainties remain, of course, but the use of AI systems helps to assess factors such as production, supply chain, demand and market dynamics. Advanced analytics is the magic word: advanced analysis programmes sift through volumes of data, interpret them and provide a database for making more informed decisions.

The management consultancy Boston Consulting Group (BCG) and the Retailers Association of India (RAI) have jointly analysed the Indian retail market. In the study report "₹400 Bn EBITDA: Opportunity with Advanced Analytics and AI in Retail", they analyse how international retail companies are using AI and advanced analytics to increase their economic success. The report also provides an overview of how Indian retailers are currently using advanced analytics and predictive analytics and the challenges they face. The authors of the study see great potential for Indian retailers to generate more sales through targeted measures and investments in AI technologies. The report provides practical recommendations for this.

The tasks that intelligent analytics programmes can perform are becoming increasingly complex. While they initially helped to identify the current status and any anomalies, they now carry out complicated, meaningful analyses and derive predictions for the future. In this way, they become a real decision-making support for the executive board or at departmental management level. The ultimate step in the future would be for AI systems to make and execute decisions independently, if desired.

Tasks for intelligent analytics software are becoming more sophisticated:

• Record and visualise the current status (e.g. stock levels or the process flow for online customer orders)
• Show me anomalies in the data (e.g. missing items or errors in the online ordering process)
• Play through different decision scenarios (e.g. different stock levels or variables in the ordering process)
• Predict what will happen in future period X (e.g. the development of stock levels based on expected demand or a higher conversion rate by improving the ordering process)
• Provide me with autonomous recommendations for action (e.g. for the purchase quantity of my items or for optimising the ordering process)
• Make decisions independently and execute them (e.g. automatic adjustment of the purchase quantity of items or automatic modification of the user experience in the ordering process)

There are numerous examples of processes from a wide range of business areas that have been analysed and subsequently optimised and (partially) automated using AI systems. The study draws on international case studies to indicate the range of application areas.

• Logistics: automated movement and provision of goods in warehouses
• Procurement: AI-based demand forecasting, inventory tracking and ordering
• Assortment management: AI-based recognition of consumer trends
• Shop layout: suggestions for optimising the shop layout and placement of goods
• Customer service: Avoid queues through AI-based image recognition and checkout opening
• CRM: AI-driven personalised offers and communication
• Pricing: dynamic pricing based on demand forecasts

Based on the findings of the international market study, the authors of the study generated some tips for Indian retailers on how to approach the topic of advanced analytics strategically:

1. Identify the challenges that affect your core business
2. Test solutions that ensure sustainable value creation
3. Use a practical and rapid test-and-learn cycle
4. Scale new solutions incrementally
5. Build strong in-house teams of experts
6. Establish strategic external partnerships to complement in-house expertise
7. Ensure data quality and a single source of truth
8. Involve employees and be open to suggestions
9. Establish a culture of change across all levels of the business

Spending on advanced analytics and AI in India has tripled between 2018 and 2021, according to the report by BCG and RAI. India also accounts for 16 per cent of the global talent for advanced analytics and AI. Nevertheless, India lags behind other Asian countries in terms of advanced analytics maturity, especially in the areas of technology, people and skills, and data management.

However, Indian retailers are catching up. Large brick-and-mortar and online retailers have implemented various solutions along the entire value chain. According to the study, medium-sized Indian retailers are also pursuing a pragmatic approach with focussed use cases.

The enormous potential of advanced analytics and AI promises to fundamentally transform the Indian retail industry and enable significant revenue growth and efficiency gains.

Source: BCG + rai Report