The Age of “never normal” is driving the Digital Transformation of grocery supply chains.
challenges by role
- “Changing consumer preferences with the move towards fresh, natural/organic/healthy, convenience foods and locally sourced items impacting sales plan.”
- “We are seeing a shift in channel preferences with the need to support various store formats and omnichannel options.”
- “Constant introduction of new items to address changing consumer tastes stresses shelf space and supply chain.”
- “We have massive volumes of customer, supplier, product, and market data available but not being used effectively to gain insights, drive decisions and business results.”
- “Balancing trade offs: Replenish stores to minimize food waste, ensure freshness, and at the same time lower out of stocks.”
- “Creating granular yet accurate store level forecasts by day of week.”
- “A lack of collaboration between various links in the supply chain, causing poor decisions leading to over/under stocks.”
- “Efficiently flowing products to stores taking into account DC/store labor, storage capacity and available transportation is getting more difficult.”
- “Allocation of constrained supply is often contentious and sub-optimal."
- “Changing assortments and new item launches are resulting in excess inventory and food waste.”
- “Slow, siloed planning processes without clear view on constraints leading to sales and margin alignment gaps between finance, merchandising and operations.”
- “We see Increasing volatility of raw material / finished goods costs as well as unpredictability in transportation costs.”
- “Our growth return on marketing & promotion is not meeting our expectations.”
- “We cannot answer management what-if questions without timely offline spreadsheet work.”
Aim big, start small, iterate rapidly.
Top 5 quick-win o9 capabilities that grocery clients are starting with
AI/ML Powered Forecasting and Demand Planning
Using market knowledge, unleash the potential of AI/ML forecasting to more accurately predict demand. Incorporate machine learning to dramatically improve daily forecast accuracy for all omnichannel options.
Supply Chain & Logistics for Retail
Replenishment & Flow Planning
Optimally replenish stores taking into account the tradeoffs between on-shelf availability and expiry.
Utilize machine learning on shopper big data to offer hyper-localized assortments that are relevant to consumer demographics.
Retail Control Tower
Supply Chain Analytics, Planning & Control Tower
Take proactive actions to resolve unexpected network bottlenecks, supply shortages and demand disruptions in real-time. Connect to advanced replanning capabilities, with what-if scenario evaluation.
Market & Supply Chain Data - Knowledge Foundation
Connect the dots across products, channels, customers, and markets. Leverage the vast amounts of data now available – e.g. Shopper Loyalty Data, mobility data, POS data, customer trends, economic activity, weather, etc., – to better understand your markets and customer demand drivers.