Today e-commerce is growing at an unprecedented rate. The move to online buying was already underway, but the pandemic accelerated the shift to consumers adopting online shopping channels. For instance, consumers who earlier stopped by the physical store for essential goods have now pivoted online, indicating a massive change in consumer behavior.
McKinsey reports that only 13% of shoppers bought groceries or other household goods online before the pandemic. By late March 2020, it increased to 31%.
With the CPG market transformed almost overnight, global e-commerce retail sales have undoubtedly doubled. As per eMarketer, by 2024, 19.2% of all US retail spending will be via e-commerce.
That said, e-commerce channels have changed the way consumers shop. Digital solutions are now becoming widespread and part of larger digital transformation initiatives. As global CPG companies continue to jump onto the e-commerce bandwagon, it brings new possibilities and unique challenges across the value chain.
CPG companies are tackling critical challenges, from lack of near-real-time demand signals to shrinking delivery windows. As sales volumes increase, it is increasingly difficult to fulfill demand without accurate, real-time off-take data to manage inventory.
Moreover, many CPG organizations do not have access to data in a useable form, which results in lost sales, missed shipments, and penalties.
The real challenge lies in data availability. Deriving meaningful insights from data that comes from various sources in different formats and forms is challenging. Thus, the value of that data can only be harnessed when consolidated and harmonized.
Lack of real-time data results in:
How can CPG companies drive more sales and ensure visibility over the competition? How can they make agile, data-driven decisions?
Reliable, accurate, and timely data can help CPG companies effectively forecast demand and ensure their brand visibility in online retail channels.
Hence, CPG companies need a comprehensive data and analytics foundation to provide a feedback loop.
Our Solution uses Artificial Intelligence (AI) and Machine Learning (ML) techniques to convert raw information into valuable insights, enabling better decision making and driving more effective e-commerce operations.
The onset of the pandemic accelerated the shift to consumers adopting online shopping. It also transformed the CPG sector overnight with difficulties in fulfilling demand. This is due to the lack of accurate, real-time data to build an effective process both for forecasting demand and ensuring visibility over the competition. Learn how e-commerce is growing at an unprecedented pace & how data helps unlock the opportunity.
One of our leading CPG clients was experiencing low case-fill rates for its e-commerce channel. The sell-in requests from this channel were erratic and intermittent, thus resulting in a low fill rate and ‘out of stock’ penalties.
Challenge — The e-retailer provided its ‘sell-out’ forecast at the national week level, but it was not always aligned with the sell-in request at the SKU- Distribution Center level with a fulfillment window of just 48 hours.
With the TradeEdge Platform and a probabilistic forecasting method, the client was able to improve case-fill rates by 6% while keeping the inventory low. This resulted in a significant improvement in customer experience and the bottom line.