Management
Distributed Order Management Systems
Theoretical or Conceptual framework
Questions addressed
Data analysis, discussion and results
Including discussion of any limitation(s))
DDSN Characteristics
SPSS Regression Statistics on DOM Investment by Velocity of Pricing
Common Order Management Module Functions
Overlaying Business Process steps with order management components
Distributed Order Management Hierarchical Model
Distributed Order Management (DOM) Conceptual Framework
Distributed Order Management (DOM) Conceptual Framework Specifics
ATP
Available to Promise; is a measure of a supply chain’s ability to report back when a product can be built
APS
Automated Planning and Schedule – a type of application used for planning production.
BTO
Build-to-order; a product strategy aimed at creating customized products where 30% of product content is custom. Appendix IV defines this concept graphically.
Configurator software application that is typically included in more complex ordering systems that is a constraint engine that makes it possible to create customized products automatically, based on selections from users configuring products on the website for potential purchase.
DOM
Distributed Order Management
Electronic Data Interchange
ERP
Enterprise Resource Planning System. Typically used for managing the production of products in factories.
ETO
Engineer-to-order; a product strategy aimed at creating customized products where 70% of product content is custom. Appendix IV defines this concept graphically.
MTS
Make-to-stock, which refers to products built specifically to mass customer requirements and are the majority of a company’s inventory
OMS
Order Management System
Quote-to-order
The process that encompasses quoting through order fulfillment. This quote-to-order process is typically combined with BTO and ETO processes to create quotes for customized products tailored to specific user’s needs. This is particularly relevant for Blueberry as they pursue the launch of new PDAs customizable by users online.
VMI
Vendor Managed Inventory, which is the coordination of inventory demand across a supplier and distributor most often – it is a method of ensuring lean manufacturing efficiencies
Part 1: Executive Summary
Order management functionality was first added to manufacturing resource planning (MRP II) systems in the form of order entry modules. As its name indicates, this module was designed to enter customer demand into the system to close the materials requirements planning (MRP) netting loop. Generally, order entry modules were designed for manufacturing, not for customer service support. As a result, most early order entry modules were cumbersome. These modules enforced a rigid process that required order numbers, customer IDs, item numbers, address IDs, remit-to addresses, etc. all to be predefined before an order could be entered. Although it inflicted all of these prerequisites on the customer order entry process in the name of completeness and integrity, the module was unable to provide customer service reps any real support for product information, pricing, or delivery dates. As if this was not bad enough, most order entry modules were created without any specific vertical industry application in mind. Over the last 15 years, software developers have attempted to add pieces of functionality to address a wider range of industry-specific issues. This has resulted in bloated and complex enterprise resource planning (ERP) order management modules that are still far from becoming the hub of the order management and customer service process. Nevertheless, the demand drivers for distributed order management systems continue to significantly expand the market for distributed order management systems, as is evidenced in Appendix a of this document, Global Order Management Market Sizing.
Figure 1 provides a graphical description of the order management function within manufacturing companies in the form of common order management module functions. Was is very clear from this graphical description is the pervasive need for integration between order management modules and the many systems it relies on for completing its critical tasks. The intent of this paper is to provide a thorough analysis of distributed order management systems, the key influences impacting them today, and the growth of the market overall.
The intent of this research is to first define how distributed order management systems are progressing from being ERP centric and more customer-focused. The unresolved question however in current research is the level of adoption for distributed order management systems across key industries and what the level of adoption translates into for transaction velocities. The major benefit of knowing if and by how much distributed order management systems increase transaction velocities has a direct impact on profitability. This research will deliver the size of the distributed order management marketplace globally, and also provide benchmarks of transaction velocities of distributed order management systems.
Part 2: Introduction and Background
An Order Management Revolution is Underway
If there is any one ERP module that is a victim of evolutionary functionality bloat, it is the order entry module. As mentioned earlier, it was never really designed to meet the needs of the actual users, usually customer service personnel. Five to ten years of scattered functional enhancements will add further complications:
Numerous order entry forms
Hundreds of confusing control fields
Pricing matrices that are virtually incomprehensible and impossible to maintain
An order entry process that is disconnected from many other critical supply chain processes such as planning, warehousing, and distribution
Graphical user interfaces (GUIs) that do not look any more like customer order entry forms than their character-based, green screen predecessors
So what is the answer? It may be that the order entry module needs to undergo the same level of revolutionary change as the MRP, capacity requirements planning (CRP), and master production scheduling (MPS) modules are currently undergoing as a result of advanced planning and scheduling (APS). APS is redefining the planning process to match the dynamic requirements of today’s manufacturing environment. From the design perspective, APS started from a clean sheet and leveraged current technology to develop planning software better suited to meet a wide variety of real-world requirements.
Order Management Is Not a Customer Order Capture System; it Is a Synchronization System
The many research sources consulted to complete this report share a common theme, which is the progression order management system early adopters make from order capture first, then into synchronizing all their warehouses, distribution centers, and fulfillment functions globally. The order management function within most ERP systems, however, does not provide support for many of the requirements of these extended global fulfillment functions, which, in addition to order capture and processing, might include the following:
Operating 24-hour call centers
Distributing product information or discussing product features and capabilities
Using and understanding product catalogs
Performing price lookups
Supporting ongoing problem resolution dialogs with customers
Identifying spares and service parts
Reacting to special customer requests
In ERP systems, the customer service capability revolves around the order. Without first entering an order, there is usually little or no access to product information, prices, or a placeholder for customer requests. This is one of the primary market factors influencing the growth of distributed order management systems. Figure 2 shows the intersection of customer support, collaborative planning and replenishment, order management, order fulfillment, and order entry on the business process phases that distributed order management needs to successfully support.
Figure 2:
Overlaying business process steps with order management system components
While these process steps vary by industry, they do provide a common basis of comparison across industries. Appendix B, Distribution of Order Management Systems by Industry, provides a useful glimpse into the specifics of how each industry adopts distributed order management best practices.
Part 3: Literature Review
In completing this literature review, it became apparent of how intertwined order management and the broader aspects of supply chain management have become. Inherent in this literature review is the role of the supply chain in influencing the synchronization of orders throughout multiple distribution centers, fulfillment locations, warehouses, and secondary channel partners. A high percentage of companies — around 30% — live in a world based on the complexity of the demand chain and diversity of supply chain relationships. In the past, companies have organized the business structure around channels/segments, products/supply chains, and geographies to minimize complexity. However, the move to global processes and the demand from customers to have a more unified relationship is forcing companies to rethink the systems approach and organization alignment. The approach requires a new strategy, and ERP systems will provide local execution, but not the global integration and coordination. The approach is not about functionality; it is about achieving process flexibility and data rigidity to support a distributed process.
All of these factors are propelling distributed order management as one of the top priorities for manufacturing and service companies alike.
Systems architectures must be redeployed to deliver on an integrated order management strategy
While a single instance ERP system may not be the long-term solution to the extended order management vision, it will continue to be a critical building block, providing much of the master data and transaction processing. The question is not whether there is a role for ERP systems in the order management process, but rather is it the architecture to provide the integration and coordination across the extended internal and external network of suppliers, buyers, and customers. The monolithic design of all ERP systems requires that all channels, business units, and supply chain organizations come to an agreement on the configuration of the system and the data model. AMR Research (2005) believes that companies must begin developing and redeploying current order management architectures with the focus on delivering more flexibility rather than a strategy that delivers far less. The move toward customer-driven fulfillment processes requires the ability to build and adapt channel-specific, product-specific, and customer-specific order flows quickly without an army of developers creating custom code.
However, the days of big bang, rip-and-replace implementations are over, and any significant it project must have two key attributes: the ability to use existing investments in data and business logic and the ability to be deployed iteratively. Both of these require thinking about the order management applications in terms of architectures, rather than a laundry list of features and functions. The users that are good candidates for the various types of Distributed Order Management (DOM) applications that are defined in this analysis should place significant emphasis on the architecture support across the following four key levels which are graphically presented in Figure 3, Distributed Order Management Hierarchical Model as defined by AMR Research (2003). Data Services anchor the model, followed by Application Services, Presentation Services, and a separate Presentation Services specifically for Internal and External Constituents. This model is very useful for organizing the literature review for DOM systems.
Distributed Order Management (DOM) Hierarchical Model
Data services: Construction of a shared and consistent repository of analytic and operational data is the single biggest challenge in effectively deploying distributed applications.
Master data services — Normalized and synchronized data on customers, products, accounts, and suppliers is the primary building block. There are several techniques for building a system of record from database consolidation to the development of virtual objects that are a composite of various systems. Regardless of the overall data management strategy, the DOM architecture must be message centric and have a metadata-driven data model. These capabilities allow the system to understand where key data resides, how to get it, and how to transform or normalize the data.
Analytical data services — in addition to transaction or operational data, the system must either support the creation of its own logical analytical data model, or feed a customer-specific data warehouse in order to measure and manage the performance of the entire process and create visibility to all stakeholders.
Application services: There are three critical components of the application services layer, which are all shared services required to manage a distributed environment.
Event and state management — This is a persistent engine that monitors the state of the order throughout its lifecycle as it travels between disparate systems, both internal and external. Coupled with the state management engine is event management, which monitors the order cycle to identify issues related to time and quantity in order to identify and manage exceptions proactively.
Order broker (integration framework) — in addition to the reliable and scalable messaging found in leading Enterprise Application Integration (EAI) systems, the systems must be specialized to deal with the way orders are decomposed and processed. First, it must have a universal order object that has several key attributes: order line independence, ability to translate a single order and order lines into all of the required activities including the generation of purchase orders, service orders, manufacturing order and distribution orders, and ability to define dependencies between the individual order lines. The order definition is then connected to the order broker, which can be based on a standard EAI system or a vendor’s own messaging layer that prepares the instructions for the various parties and defines the format of the business documents and communication methods.
Business Process Management (BPM) — This is the ability to graphically design processes and workflows inside the application and across multiple applications to enable and manage an end-to-end process. The application should enable users to define custom order processes and types based on almost any dimension, but specifically based on the customer, geography, and/or the product. Without the flexibility inherent in a BPM engine, users will struggle to support the level of customization required in all order management environments.
Process services: There are currently 12 key modules that provide the business logic to assemble and configure a complete DOM system. Few companies will require all, since priorities will be highly dependent on need and current environment. The key modules are as follows:
Configuration and quote — Including support for simple rules-based configuration to more complex attribute or parametric configurations
Pricing and contract management — Including support for global taxation
Global credit management — Including the ability to aggregate credit information from multiple internal and external sources
Product catalog — Including the ability to support, aggregate, and manage multi-vendor catalog. Columbus (2001) points to these tools specifically as leading to greater levels of closed sales throughout indirect channels.
Order promising — Including Available-to-Promise (ATP) and Capable-to-Promise (CTP), which is critical according to Sourcing and allocation — Including support for substitutions and inventory reservations
Order visibility — Including the ability to track orders internally and through logistics or contract manufacturing partners
Inventory visibility — Including the ability to synchronize all item data across system
Automated replenishment — Including support for Vendor Managed Inventory (VMI)
Delivery management — Including the ability to track delivery through logistics partners and normalize data
Service management — Including the coordination of aftermarket processes, such as parts, returns, repairs, and field service
Consolidated settlement — Including the ability to create a single invoice and all the necessary credit and debit transactions between business entities in order to settle order process
Presentation services: The key capability is to provide relevant user-specific content, data, Reports, and Alerts to support the consistent and efficient execution of the CF process. The key requirement of vendors is developing the ability for the application to be run with or without presentation services, allowing users the flexibility to leave existing user interfaces in place and use the business logic and data for application. The key enabling technology is a portal framework that includes the following services:
Role-based or context-based presentation and navigation
Identity and security services
Content management and taxonomy services
Community definition
Part 4: Theoretical or Conceptual framework for order management
From the customer’s perspective, the order management cycle extends from inquiry to account settlement and includes order processing and delivery.
Figure 4 provides an example of this process, and the specific steps below describe them. From the enterprise perspective, the order management cycle involves five aspects of functionality:
Capture
Validate
Source
Distribute
Settle
Distributed Order Management (DOM) Conceptual Framework
Order management plays a key role when the enterprise interacts with its customers. At inquiry and order, order management captures all relevant business rules governing the sale. These rules are defined by the following factors:
In the transaction itself (e.g., quantity and delivery date)
By a hierarchy of precedents involving such items as contract, commodity, customer, customer class, customer credit condition, country, and currency
By the enterprise’s and customer’s business rules
Information captured at order time governs downstream activities in sourcing, delivery, and settlement. Figure 5 illustrates the more advanced aspects of each of the distributed order management cycle, including the key process areas that both order management and order fulfillment interact with.
Distributed Order Management (DOM) Conceptual Framework Specifics
Scope and Requirements of Order Management
Figure 5 defines the functional scope of order management from capture to settle. Complementing order management, customer asset management aids in the acquisition of customers and tracks issues and resolutions to ensure customer retention.
Capture
In capture, the enterprise acquires the customer’s demand signal (item, quantity), attending requirements (delivery, value-added processes), and specific terms and conditions. This functionality also supports inquiries, quotes, and changes.
This includes the ability to support different streams of order entry:
High-volume electronic data interchange (EDI)
Customer-direct via the Web
Telemarketing supported by customer service representatives
Direct sales supported by a field sales force
Validate
Validate ensures that attributes and content of the order conform to all relevant business rules between the enterprise and its trading partners. In most instances, these rules derive solely from the enterprise/customer relationship. They may also derive from the supplier/enterprise-customer relationship if the supplier controls the channel. This is often the case in Industrial Products where the original equipment manufacturer (OEM) may define terms and conditions between supplier and customer. Validate can be executed in real-time within capture or in nightly batch runs after the fact, depending on the implementation and business rules shared by the enterprise and trading partners. Supported by technology, best practice is pushing toward real-time validation at capture. Depending on channel, customer, and enterprise requirements, validate may include some or all of the following:
Customer credit check by any organization attribute associated with the customer
Customer order authority by commodity, order value, etc.
Pricing standard or by channel, contract, transaction-level negotiated discounts, etc.
Promotion affecting pricing, item, packaging, etc.
Product by SKU, SKU extensions, or attribute in non-SKU environments
Customer by stand-alone account or multi-organization rules
Substitutions by product life-cycle, customer-defined rules, etc.
Design in an engineer-to-order environment
In certain make-to-order environments, where committing to a customer due-date requires finding available capacity and inventory, validate can be tightly coupled to advanced planning and scheduling (APS) functionality. In other environments where delivery date and delivered cost are transportation-sensitive, such as bulk chemicals, metals, textiles and paper, validate may be tightly coupled with the reservation of transportation capacity, concurrent with capture in best practice.
Source
Source entails the steps necessary to commit inventory, work-in-process (WIP) or capacity to an order. This may be as simple as product reservation against on-hand finished goods or more complex, such as soft and hard allocation against a time-phased view of inventory status. From an ERP perspective, this view may be limited or enhanced by available-to-promise (ATP) or capable-to-promise (CTP) functionality provided by APS. In some environments, such as traditional and virtual distributors, source may be tightly coupled with procurement.
Deliver
In deliver, the final product is picked, readied, packed and shipped to the customer. The basic theme of pick-pack-ship varies by product and channel. In some environments, an enterprise may add a great deal of value between pick and pack. For example, a Consumer Electronics manufacturer employing a postponement strategy may assemble final product against specific orders between pick and pack. On the other hand, the pick-pack-ship operation adds scant value in deliver for a Shoe manufacturer.
Settle
Settle uses the business rules and data associated with the order at capture and modified in source and deliver to drive all accounting and financial transactions such as accounts receivable, billing, and cost accounting needed to close the order. Settle applies these rules and data to heed the customer/order/invoice logic governing the transaction and to allocate discounts, credits, and allowances in conformance to the customer’s organization structure and accounts payable business rules. Settle also uses the same information carried by the order for internal cost accounting by customer account and cost centers for various trade funds.
All these factors within a distributed order management system contribute to the growth of the Demand Driven Supply Chain (DDSN), which was defined by AMR Research within the last five years. The progression as it relates to distributed order management is illustrated by the Table 1, DDSN Leadership Characteristics.
Table 1: DDSN Characteristics
Part 5: Method and design
The method and design used for completing this analysis relies on the AMR Research order management hierarchical model and the Demand Driven Supply Network (DDSN) model as the basis for analysis overall. The hhypothesis is that distributed order management systems significantly increase transaction velocities. The variables used in this analysis include the market sizing for global distributed order management systems in key vertical markets, transaction velocities before and after system implementation (measured in inventory turns), and a definition of the size of the markets for sourcing, brokering, service lifecycle management, and reverse logistics applications acquired, installed, and used within each vertical market.
Part 6: Questions addressed
The key questions asked include the following:
What is the distribution of order management systems by industry globally today?
What are the dynamics of transaction velocities on order management systems today and their ROI?
How does the AMR Research Order Management Hierarchical Model and the DDSN framework contribute to understanding the key dynamics of this market?
What are the implications across vertical markets for distributed order management adoption?
Part 7: Data analysis, discussion and results (Including discussion of any limitation(s))
The following are key aspects of the data and methodology:
In completing this report key industry analysts and experts were contacted, including a recent survey from LWC Research on the forecast of global order management systems.
LWC Research primary data was also provided for the completion of the Appendices of this document.
In terms of the analysis, the following steps are used:
Microsoft Excel and SPSS will be used for analysis of market forecasts.
Expected results: That distributed order management systems significantly increase transaction velocity and accuracy, and make a major financial contribution to companies.
Discussion and Results
Using the forecasts and historical data from LWC Research (2006) and running an SPSS regression analysis where spending on distributed order management systems that specifically have pricing enforcement and optimization functionality included as the independent variable, and the per unit change in pricing strategies of companies who participated in the LWC Research study, a statistically significant correlation emerges. A Multiple R. emerges of.98, which is significant at the.05 and.01 levels of confidence.
SPSS Regression Statistics
Multiple R
Square
Adjusted R. Square
Standard Error
Observations
ANOVA df
SS
MS
Regression
Residual
Table 2:
SPSS Regression Statistics on DOM Investment by Velocity of Pricing
This translates into the following series of discussion points and observations relative to the growth of distributed order management and the emerging class of pricing applications included within them:
Distributed order management applications are having a statistically significant effect on the growth of pricing velocities in the companies that are adopting these technologies. This translates into significant ROI and influence on pricing velocities, and proves the hypothesis of this study.
Pricing applications as a part of a distributed order management suite of applications is gaining in the industries studied, as can be see from the 14 vertical markets profiled in Appendix a.
Part 8: Final recommendations
In evaluating distributed order management applications, companies need to keep the following specific requirements in mind. These recommendations are result of the research completed for this analysis:
Companies are strongly encourage to evaluate associated back-office benefits and be prepared to build a single, stronger business case for both. Focusing on the ROI of implementing distributed order management is critical.
For many companies who have prematurely adopted order management, it shows that the time is now to plan how technology will support the current and future order management process. Every user should have a three-to-five-year roadmap for distributed order management systems.
The research shows that Distributed Order Management is a viable technology, but because of the risk associated with failures in the OEM process it must be deployed incrementally by module on a global basis or by channel more holistically.
Investment in data synchronization and integration is a prerequisite to any distributed technology deployment, which will also require more involvement in industry-based efforts to develop integration standards across companies.
Users with significant investments in a single ERP provider should certainly consider instance consolidation as the first options as long as they fully understand the limits of the system when substantial flexibility is required to support demand or supply complexity.
Focus on the aspects of being demand driven by making distributed order management a key functional area of your organization – this forces your organization to put fulfillment and order synchronization of all efforts.
Part 9: Summary and conclusions
Global competition has created the need for manufacturers to synchronize their order management functions with greater urgency and accuracy than ever before. The critical need is to define and implement systems that can span between capturing, validating, sourcing, distributing, and settling transactions. This is a critical set of processes to overarch, and as Figure 6 shows, there are only stop-gap vendor alternatives today with the exception of ERP vendors that span across all five key process areas.
Scoping Distributed Order Management (DOM) Process Coverage
What is continually forcing the globalization of order management and higher levels of system than ever before is the role of pricing, product availability, and visibility throughout supply chains. These dynamics are forcing companies to transform their distributed order management systems to be more agile and customer focused than ever before.
Bibliography
AMR Research (2006) – What is Demand Visibility? AMR Research Report. Published March 14, 2006. Accessed with permission from the publisher. Lora Cecere and Roddy Martin.
AMR Research (2005) – the Handbook of Becoming Demand Driven. AMR Research Report. July 15, 2005. Accessed with permission from the publisher. Lora Cecere, Roddy Martin, Debra Hofman.
AMR Research (2003) – Configuration is the Heart of Customer Fulfillment for Complex Product Manufacturers. AMR Research Report. Monday March 31, 2003. Retrieved from the Internet on May 3rd, 2006 at http://lwcresearch.com/filesfordownloads/ConfigurationIstheHeartofCustomerFulfillmentforComplexProductManufacturers.pdf
Askegar and Columbus (2002) – Channel Management Best Practices: It’s All About Orders. AMR Research Report. Monday September 9, 2002. Retrieved from the Internet on May 7, 2006:
http://lwcresearch.com/filesfordownloads/SqueezetheRevenueOutofSPRs.pdf
Columbus (2001) – Defining Your Direction in Guided Selling. AMR Research Report. October, 2001. Retrieved from the Internet on September 22, 2006:
http://www.lwcresearch.com/filesfordownloads/DefiningYourDirectioninGuidedSellin.pdf
Columbus (2002) – the Sell-Side E-Commerce Market: It’s All About Integration. AMR Research Report. Monday April 1, 2002. Retreived from the Internet on March 6, 2006:
http://lwcresearch.com/filesfordownloads/SellSideECommerceMarketIsAllAboutIntegration.pdf
Columbus (2003) – Squeeze the revenue out of your Special Pricing Requests. AMR Research Alert. Tuesday November 11, 2003. Retrieved from the Internet on May 7, 2006:
http://lwcresearch.com/filesfordownloads/SqueezetheRevenueOutofSPRs.pdf
LWC Research (2005) – User Speak out about SAP NetWeaver and Order Management. Published December 31, 2005. Distributed through arrangement with the publisher.
LWC Research Order Management Study (2006) – Global Distributed Order Management Forecast, 2006-2011. LWC Research. Irvine, CA
Accessed by permission from the publisher.
Appendices
Appendix a: Global Order Management Market Sizing (LWC Research Order Management Study, 2006)
Order Management Market Sizing
All dollars in millions)
Interactive Selling and Multi-Channel Order Capture – (Worldwide License Revenue)
Quoting Systems
Pricing (majority of larger deals are optimization)
Configuration
Catalog Management (Structured Sell Side)
Sell Side order Management (Order Capture)
Interactive Selling and Multi-Channel Order Capture – (Worldwide Maintenance Revenue)
Quoting Systems
Pricing (majority of larger deals are optimization)
Configuration
Catalog Management (Structured Sell Side)
Sell Side order Management (Order Capture)
Order Orchestration / Administration Worldwide License Revenue
Sourcing and Promising
Decomposition and Brokering
Post-Sales Support (Service Lifecycle Management)
Returns and Reverse Logistics
Order Orchestration / Administration Worldwide Maintenance Revenue
Sourcing and Promising
Decomposition and Brokering
Post-Sales Support (Service Lifecycle Management)
Returns and Reverse Logistics
SUMMARY OUTPUT Regression Statistics Multiple R. 0.986894446 R. Square 0.973960648 Adjusted R. Square -1.25 Standard Error 18.45252893 Observations 1 ANOVA df SS MS F. Regression 5-50942.825-10188.56-149.6137 Residual 4-1361.9833-340.4958 Total 9-52304.808 Coefficients Standard Error’t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0-0-23 -1E-270-3.1E-270-28 4.6E+229 -5E+229-31 1.31E+84-1.31E+84-41 0-0-1 -3.65E+84-3.65E+84 -3.7E+84-3.65E+84-53 2.22059997-0.1815452-12.23167-0.000257-1.71654975-2.72465-1.71655-2.72465-64 RESIDUAL OUTPUT PROBABILITY OUTPUT Observation Predicted 30 Residuals Standard Residuals Percentile 30-1-5.39018E+85 -5.39E+85 -3-50-40.8 Correlation of Global Pricing Velocity and Investments in Order Management Systems
Appendix a: Distribution of Order Management Systems by Industry (LWC Research Order Management Study, 2006)
License Revenue Share by Vertical, 2006-2007
Manufacturing
Textiles
Apparel
Wood Products, Paper, Printing
Petro Products, Chemicals, Plastics
Pharmaceuticals/Biotechnology
Primary/Fabricated Metal
Machinery (Farm, Construction, Factory)
Computers and Electronics (Peripherals, Communication Equipment, Semiconductors)
Automotive and Auto Parts
Aerospace & Defense
Food, Beverages, Consumer Packaged Goods
Other Manufacturing
Non-Manufacturing
Resource Extraction (Metal Ore, Oil & Gas, Coal)
Utilities (Electric, Gas, Water, Sewer)
Telecommunication Services
Wholesale Trade
Retail Trade
Transportation & Warehousing
Information (Publishing, Media, Info. Services, Excluding Telecommunication Services)
Finance & Insurance
Healthcare & Social Assistance
Education
Other Services
Public Administration
Source; LWC Research
Note: All analyses included in tables by vertical sum to 86%. Not included are the following vertical sectors:
Apparel
Wood Products, Paper, Printing
Utilities (Electric, Gas, Water, Sewer)
Healthcare & Social Assistance
Education
Other Services
Distributed Order Management Systems
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- We have a quality assurance that reviews the paper before it gets to you. As such, we ensure that you get a paper that meets the required standard and will most definitely make the grade.
In the event that you don’t like your paper:
- The writer will revise the paper up to your pleasing. You have unlimited revisions. You simply need to highlight what specifically you don’t like about the paper, and the writer will make the amendments. The paper will be revised until you are satisfied. Revisions are free of charge
- We will have a different writer write the paper from scratch.
- Last resort, if the above does not work, we will refund your money.
Will the professor find out I didn’t write the paper myself?
Not at all. All papers are written from scratch. There is no way your tutor or instructor will realize that you did not write the paper yourself. In fact, we recommend using our assignment help services for consistent results.
What if the paper is plagiarized?
We check all papers for plagiarism before we submit them. We use powerful plagiarism checking software such as SafeAssign, LopesWrite, and Turnitin. We also upload the plagiarism report so that you can review it. We understand that plagiarism is academic suicide. We would not take the risk of submitting plagiarized work and jeopardize your academic journey. Furthermore, we do not sell or use prewritten papers, and each paper is written from scratch.
When will I get my paper?
You determine when you get the paper by setting the deadline when placing the order. All papers are delivered within the deadline. We are well aware that we operate in a time-sensitive industry. As such, we have laid out strategies to ensure that the client receives the paper on time and they never miss the deadline. We understand that papers that are submitted late have some points deducted. We do not want you to miss any points due to late submission. We work on beating deadlines by huge margins in order to ensure that you have ample time to review the paper before you submit it.
Will anyone find out that I used your services?
We have a privacy and confidentiality policy that guides our work. We NEVER share any customer information with third parties. Noone will ever know that you used our assignment help services. It’s only between you and us. We are bound by our policies to protect the customer’s identity and information. All your information, such as your names, phone number, email, order information, and so on, are protected. We have robust security systems that ensure that your data is protected. Hacking our systems is close to impossible, and it has never happened.
How our Assignment Help Service Works
1. Place an order
You fill all the paper instructions in the order form. Make sure you include all the helpful materials so that our academic writers can deliver the perfect paper. It will also help to eliminate unnecessary revisions.
2. Pay for the order
Proceed to pay for the paper so that it can be assigned to one of our expert academic writers. The paper subject is matched with the writer’s area of specialization.
3. Track the progress
You communicate with the writer and know about the progress of the paper. The client can ask the writer for drafts of the paper. The client can upload extra material and include additional instructions from the lecturer. Receive a paper.
4. Download the paper
The paper is sent to your email and uploaded to your personal account. You also get a plagiarism report attached to your paper.
PLACE THIS ORDER OR A SIMILAR ORDER WITH US TODAY!!!
