IBM Sterling Order Fulfillment Optimizer with Watson..
In today's world more or less every retailer in the world faced the
- Today customer expects their items 'anytime' 'anywhere' in
- Customers are asking for Free Shipping and that even next day!
Increased customer expectations around speed of delivery
- Customer experience is the top priority
- Changes to UPS and FedEx rate calculations, that include
additional charges for odd sized items .
- Bottlenecks and inefficiencies abound
- Demand for a continuous innovation
- Need to harness converging technology to build a smarter
What retailer needs?
Retailer needs an intelligent supply chain. A responsive self-correcting
supply chain is the key to deliver better customer experience and high
Order Fulfillment Optimizer with Watson
What is Order Fulfillment Optimizer with Watson?
Order Fulfillment Optimizer is a AI based analytical tool which can be
integrated with existing order management and inventory visibility
systems to to reduce overall cost of fulfilment. Retaier will be able to
act on changes in the market to maintain margins, use store capacity and
meeting delivery time line, optimize inventory and fulfillment decisions
to avoid stockouts, reduce markdowns, meet customer expectations, and
If your goal is to keep the cost of fulfillment as low as possible IBM
Watson Order Optimizer can help you reduce your total cost to serve, in
Other variables that Order Fulfillemt Optimizer gives weightage :
- Should the order ship from a nearby store(node) to reduce
- What happens if the nearest location is at low capacity and
paying overtime to get products out the door
- What if the closest store only has few items left on the
shelf, store may run out of inventory with the potential to lose sales
of walkin customers.
Order fulfillment optimizer optimizes an order, order-line for the
lowest total cost based on actual cost and profit drivers while
considering multiple objectives at once.
Benefits of IBM Sterling’s Fulfillment
Optimizer with Watson
- Optimize Inventory:
Currently (in absence of
Fulfillment Optimizer) which inventory to use to fulfill a order is
based on predefined sourcing and scheduling rules. That means it's
rule based, pre-defined and static. It can not change the sourcing
descision based on the current situation.
Where as Order
fulfillment optimizer decide sourcing location to allocate the
inventory at its most profitable price point minimizing markdowns and
out of stocks. It continuously anlyze the data to learns sales and
demand patterns and act on the next order fulfillment decision. It
prioritizes slow-moving or obsolete inventory to meet eCommerce
demand. Shifts inventory away from low-demand locations. Make better
use of returned inventory.
- Real-time Order Sourcing:
decisions on runtime to minimize the complete cost-to-serve which
includes avoiding split of orders. Sources orders in with the
knowledge on available capacity, labor, and overtime.
- Improved Experience in Monitoring and Managing:
Produce insightful reports quickly and easily for business. Provides
customized dashboards to show relevant to information for each
individual roles. Supports natural language and allows business users
to get answers in their language and take action easily. Managers can
monitor operations at a high level and detail level as an when
Users can dynamically monitor, and gain
comprehensive views across the entire enterprise. It can also detects
market trends, opportunities, and patterns using cognitive abilities.
Evaluates factors impacting fulfillment performance down to the
individual SKU and node level. Dynamically balances between different
business objectives based on time of year (peak, non-peak) and
- Reduce Costs:
It reduces shipping and
fulfillment costs. Evaluates different carriers in real-time and
acheieve least cost-to-fill. Analyzes total fulfillment costs and
performance issues such as labor cost, packaging, and time to fill. Do
split orders when ever is required to support least cost and do
balance intelligently customer satisfaction and low cost.
- Minimize Risks:
The Optimizer has the
capability to create what-if scenarios and simulate them based on data
and AI predictions on future demand to see how they will affect the
business before making the changes live to minimize risks. This
feature can also be used to test different fulfillment strategies and
compare them to ensure improved efficiency and performance.
Now the important question is does every
retailer need AI enabled supply chain?
It depends on how big is your fuflimment network? How many stores and DC
do you have? If you only couple of store and DC in a region, then you
may not need AI in your order fulfillment operation.
If you have 100s of stores and multiple DCs, Order Fulfillemt Optimizer
can be benificail at great extent. Order Fulfillemt Optimizer can look
at each order and compare to see which option is the best (and cheapest
and fastest) to fulfill that order.