The Age of “never normal” is driving the digital transformation of retail hardlines.
Common retail hardlines
challenges by role
- ”Predicting and supporting surges in consumer home improvement spending.”
- “Significant shift in channel mix between the contracting and consumer channels with the need to support various store formats and omnichannel options.”
- “Constant introduction of new items (Green innovation) to address changing consumer tastes.”
- “Massive volumes of customer, supplier, product, and market data available but not being used effectively to gain insights, drive decisions and business results.”
- “Our market visit reports are all on email – no way to reference them systematically.”
- “Our business is highly cyclical we need to better sense market signals.”
- “Analyzing a huge amount of data and trends to build hyper-localized assortments that are relevant to consumer demographics.”
- “We have Poor Inventory & Order status Visibility.”
- “We have a lack of collaboration between various links in the supply chain, causing poor decisions leading to over/under stocks.”
- “Efficiently flowing high cube products to stores taking into account DC/store labor, storage capacity and available transportation.”
- “Prices for lumber and other building materials can be volatile and creates inventory risk”
- Slow, siloed planning processes without clear view on constraints leading to sales and margin alignment gaps between finance, merchandising and operations.
- Lack of integration between merchandise financial planning and assortment planning leads to lack of clarity in financial performance.
- “Our AOP / finance process is disconnected from the rolling forecasting and replenishment processes”
- "Our people productivity needs to improve – Most work is offline, Low adoption of systems of engagement."
Aim big, start small, iterate rapidly.
Top 5 quick-win o9 capabilities that retail hardlines 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 corrective 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.