The future of retail demands accelerated analytics

The pandemic has put to light some limitations of current data-driven decision-making in retail. The past is no longer enough to predict the future. New alternative external data streams (such as the voice of the customer in social media) must be coupled with internal sources.

The increasing uncertainty in demand and supply is forcing companies to look beyond single-scenario plans and punctual projections of what may happen. Planning activities, which were typically performed on a top-down approach to estimate the outcomes, are now more granular and localized (e.g., SKU, store, or customer level) and executed continuously.

Therefore, silos must be blurred within the organizations to support enterprise-wide performance and cross-functional interaction between teams.

Vital retailer processes were affected by these limitations, which now demand accelerated analytics that take into account the following requirements:

• Every decision in retail must be customer-centered. The starting point is to truly get to know the customer and their drivers of experience, and to understand their journey within the company. Customer behavior needs to be grasped well beyond clerk-based gut feeling, as retained customers are moving faster between pre-defined segments.
• Phygital experience (digital and in-store interactions) requires improved quality to retain customers
• An encompassing marketing-operations approach with local knowledge is fundamental, as product and service innovation pipelines are being stressed (new niches, channels, private labels).
• The perfect balance between value proposition and efficiency must be struck when shaping the optimal operating models
• An agile and resilient approach is mandatory to manage the supply chain, incorporating risk-management metrics
• Company’s real estate (including store network) needs to be redesigned, given the trend to locally sourced food, convenience formats and online channels

There’s no doubt that the massive amount of data generated by retailers and their customers holds the potential to drive real bottom-line differentiation. By applying data-driven state-of-the-art techniques to augment or automate decision-making, we can uncover and address these current retail business challenges.