CARGOCONNECT-JUNE2026 - Flipbook - Page 65
E-Commerce Supply Chain FEATURE
“The next stage of
evolution is clear: endto-end automation of
supply chain decisions.”
AKSHAY GANGRADE
Head– E-commerce, Britannia
Seasonal spikes, flash sales, and
unpredictable consumer trends
make demand forecasting
increasingly complex.
Smart Forecasting in an
Unpredictable World
In volatile markets, AI transforms traditional reactive
planning into continuous predictive intelligence,
signi昀椀cantly reducing forecasting errors and inventory
inaccuracies. It fundamentally outpaces legacy forecasting systems through several targeted capabilities,
improving demand forecasting by processing vast
amounts of historical, real-time, and external data
to identify hidden market patterns.
Shruti agrees and talks through, “AI is helping
brands move from historical forecasting to predictive and adaptive forecasting. It factors in multiple
variables — seasonality, platform events, discounting
patterns, regional demand behaviour, and even
competitor activity. This improves forecast accuracy
signi昀椀cantly, especially in fashion where demand can
shift quickly. She observes that AI helps in maintaining
optimal stock levels by continuously recalibrating
demand signals, which reduces both stock-outs and
excess inventory.
“Agentic AI will run autonomous supply chains.
The next phase is “Agentic AI” — systems capable of
taking decisions automatically instead of just generating insights,” tells Springberry’s Kumar. He further
adds that the future AI agents will reorder inventory
automatically, shift inventory across warehouses,
negotiate logistics allocation, predict cancellations,
optimise pricing dynamically, and trigger marketing
campaigns based on stock levels.
Volatility has become the new normal in e-commerce. Seasonal spikes, 昀氀ash sales, and unpredictable
consumer trends make demand forecasting increasingly complex. This is where AI is making a tangible
impact, spotlights Basu. Advanced ML models can
now process vast datasets including weather patterns,
social media trends, and macroeconomic indicators to
generate highly accurate demand forecasts. “AI-driven
systems enable dynamic inventory rebalancing,
ensuring that the right products are available at the
right locations, at the right time,” he tells.
Advancing Supply Chain Agility
and Sustainability
In today’s era, supply chain resilience is about persistence, adaptation, and transformation. Building agile
e-commerce supply chains requires transitioning
from purely cost-optimised “Just-in-Time” models to
“Just-in-Case” strategies. Organisations must balance
e昀케ciency with continuity by leveraging data-driven
visibility, diversi昀椀ed sourcing, and 昀氀exible regional
ful昀椀lment networks to absorb market shocks.
“Resilience today is about visibility and speed of
response. AI enables end-to-end visibility across the
supply chain; from production to last-mile delivery,”
emphasises Shruti. “It can simulate di昀昀erent scenarios,
昀氀ag potential disruptions early, and suggest alternate
sourcing or routing options. This allows companies
to respond proactively rather than reactively. Agility
comes from this ability to take faster, data-backed
decisions at every node,” she illustrates.
Basu highlights that recent global disruptions
have exposed the fragility of traditional supply chains.
AI is playing a critical role in building resilience
by enabling proactive risk management. With AI,
companies can predict potential disruptions before
they occur, simulate multiple “what-if” scenarios,
automatically reroute shipments or switch suppliers
in real time. This shift from reactive to predictive
operations allows businesses to maintain continuity
even in the face of uncertainty, he attests.
Digital logistics technologies can enable a signi昀椀cant
reduction in global CO2 emissions by 2030 through
optimised routing, and enhanced supply chain visibility. “Sustainability is no longer optional; it is a
strategic imperative,” asserts Basu. He explains that
AI-driven logistics tools are helping companies reduce
emissions, minimise waste, and optimise resource
utilisation. “Route optimisation algorithms reduce
fuel consumption by eliminating empty miles. AI also
enables better load planning and consolidation, ensuring
that transportation assets are used more e昀케ciently.
As regulatory pressures and consumer awareness
grow, AI will become a key lever for achieving both
Consumer
expectations
now centre
around
10-minute
delivery
convenience.
Same-day
ful昀椀lment is
becoming the
new service
benchmark.
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