JD Edwards EnterpriseOne
Order Promising: Save Time and
Improve Accuracy
An Oracle White Paper
January 2004
JD Edwards EnterpriseOne Order Promising: Save
Time and Improve Accuracy
EXECUTIVE OVERVIEW
When can I have my order? Can you ship it tomorrow? Tell me now.
Your customers’ simple questions often have complex answers. Whether they are
speaking with you on the phone or placing an order on a web storefront, customers
expect immediate gratification. The moment they place an order, they want to
know when it will ship. How do you respond?
How do you balance customer delivery requirements against your need to make a
consistent profit? If you expedite the order, will your margin erode to the point that
it will cost you instead of make you money? Considering all your other orders, do
you have the ability to produce the order by the requested date? Is it more
profitable to ship the order from a distribution center hundreds of miles away or to
build and ship it directly from the factory?
You could use standard lead times to answer these questions and hope for the best,
but if the quoted lead-time is too long, your valued customer may go elsewhere. If
your lead-time is too optimistic and you miss the delivery date, your customer may
never come back. And if you incur additional expenses such as overtime and
premium freight, your valued customers may become unprofitable.
On the other hand, if you consistently deliver according to your commitments and
quickly assess your capability to respond to urgent customer orders, your customers
will become even more loyal and valuable. And if you fully understand the costs
associated with these actions, you can ensure that the orders you accept are
profitable.
This whitepaper describes the common process for promising orders and explains
how order promise software can save you significant time and improve accuracy. It
also describes the added value of Oracle’s JD Edwards EnterpriseOne Order
Promising with its integrated, real-time order promising that can instantly provide
answers to the following questions:
•
When can I deliver the order?
•
From where should I source it?
•
How much will it cost?
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•
What will the profit margin be on the order?
What Must an Order Promising Application Do?
Recognizing that every customer is different, an order promising application must
support multiple order entry points simultaneously—promising accurate and
profitable delivery dates via the internet, phone, fax, EDI transactions, customer
relationship management (CRM) applications, or multiple disparate order entry
systems.
Understanding the Status Quo
To really understand how an order promising application can impact your business,
it is important to understand the process for promising orders that exists in most
companies today (summarized in Figure 1 below).
Figure 1: The order promising cycle time.
The clock starts ticking when the customer calls in the order and asks a simple
question, “When can I have my order?” The customer service representative
attempts to contact the planning department, but the planner is in a meeting.
Several hours may pass before the planner reacts to the request. If the order
contains complex processes and multiple levels in bill-of-material structure, it may
take the planner several days to evaluate the impact of inserting the order into the
current schedule.
Once planning has the answer, the customer service representative attempts to
contact the customer. When the customer is finally reached, he may either accept
the promise date or reject it. The order may even be revised. If the promise date is
rejected or the order is modified, the process will have to be repeated, taking up
more of your, and the customer’s, valuable time.
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What Improvements Can You Expect from an Order Promising
Application?
An online order promising application supports a different process to solve this
problem, as summarized in Figure 2.
Figure 2: The application automates the order promising process.
The application fully automates the process of providing accurate order
commitments, which includes two steps. The work that the planning department
did in the manual process is externalized into a one-time setup to precondition the
enterprise for promising orders. Conceptually, this is very similar to externalizing
the setup of a piece of machinery on the shop floor.
The second step is to automatically promise accurate and optimized delivery dates
in real time. The time to promise the orders is now analogous to the run time to
produce parts on the machine.
Step 1
The sales and planning departments agree on a process for promising orders. This
might include roles and responsibilities, manufacturing facilities along with items
produced, and inventory policies for different items. The departments establish
customer rules regarding back orders, partial shipments, and product substitutions.
Next, they determine business objectives for how to fulfill customer orders. Sample
objectives would be maximization of customer service, minimization of cost, or
profit maximization. These objectives govern the details of how the promise will be
made. For example, the business objective for maximizing customer service might
search through alternatives based on meeting the delivery date at the lowest cost by
using existing inventory from multiple locations before incremental manufacturing
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is authorized. If delivery cannot be made on time, overtime can be authorized and
material can be expedited as required.
The minimizing cost objective might be based on satisfying the order at the lowest
cost, within an acceptable delivery window, from available inventory in your closest
distribution center. Manufacturing operations will not be disrupted within a specific
timeframe and you will never plan on using overtime or expedited material.
The order promising application then applies these business objectives to
customers and items. Those with similar characteristics can be grouped together for
simplicity.
Step 2
Now you are ready to start taking orders. You can accomplish promising orders in
two ways: auto-promise mode or scenario management mode.
In auto-promise mode, the best delivery date based on your predefined business
objective for the customer/item combination is automatically applied to the order.
Auto-promise mode is used by customer service representatives who typically
accept the highest-ranked promising scenario based on the customer’s assigned
business objective. Since the user never exits the business process of order entry,
this mode supports rapid, high-volume order entry. If the date promised is not
acceptable, the order can be easily transferred to a supervisor via a standard
workflow process for further evaluation. The supervisor can evaluate other
fulfillment alternatives by using a scenario manager.
In scenario management mode, the user is presented with several alternatives for
fulfilling the order. The delivery date, costs, margin percentage, and total profit are
summarized at the order level and detailed line-item information also can be
explored. For each alternative, the user can view all the constraints that impact the
order across the multisite enterprise.
How Does it Work?
Figure 3 illustrates how an online order promising application evaluates the
capabilities of the multisite enterprise to determine the potential methods available
to fulfill the order.
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Figure 3: The online order promising application evaluates the capabilities of the multisite enterprise.
First, the application performs an available-to-promise (ATP) check to see if the
item exists in inventory anywhere in the network, or if there are any scheduled
receipts currently planned. Then, if the results of this query do not satisfy the order,
the business objective, and the customer rules, the order promising application
proceeds to the next level where a capable-to-promise (CTP) check is performed to
identify a feasible production method using unallocated capacity and materials. This
query will evaluate material and capacity-constrained plans across multiple sites and
will drill down through all levels of the manufacturing routing and bill of material.
Purchased materials can be modeled by using standard supplier lead times or, the
supplier’s actual capacity can be modeled.
The Importance of Real-Time Execution Information
Integration between the live execution environment and the in-memory order
promise model is the key to making accurate promises. What many people do not
realize is that the order promising application must be tightly integrated to the back
office as well as the front office to provide real-time visibility to sales orders and all
inventory-related transactions. In fact, back office integration is the more important
and harder of the two. True, real-time back office integration can only be delivered
economically within a single software solution. Real-time execution integration is
critically important because changes that occur in the supply chain, such as late
purchase orders or scrapped work orders, need to be considered in your promises
as soon as they occur. This real-time back office integration is a key differentiator
for EnterpriseOne Order Promising.
Delivering Value
The value proposition for EnterpriseOne Order Promising real-time order
promising is as simple as 1-2-3:
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•
By understanding your true capability to fulfill customer orders, you can
reduce uncertainty across your supply chain, resulting in lower inventory
levels and improved customer service.
•
Because your promising methodology is precoordinated using the planning
knowledge base, you can achieve a more profitable use of your intellectual
capital and your supply chain assets.
•
By understanding the costs and margins associated with different fulfillment
options, you can reduce cost of goods sold and improve the profitability of
customer orders.
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JD Edwards EnterpriseOne Order Promising: Save Time and Improve Accuracy
January 2004
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