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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

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

Preparing budgets and financial forecasts us history essay help

Finance

The financial manager of a firm deals specifically with the acquisition, financing, and management of assets with the overall financial security and profitability of the firm as his goal. Decisions concerning what are the best types of financing, the best financing mix; the appropriate dividend policy and how the funds will be physically acquired are all the responsibility of the financial manager. The financial manager has different degrees of operating responsibility over the firm’s assets with a greater emphasis on current asset management rather than fixed asset management.

Responsibilities of the financial manager also include capital budgeting, cash management, credit management, dividend disbursement, financial analysis and planning, pension management, insurance/risk management, and tax analysis and planning through cost accounting, cost management, governmental reporting, internal control, the preparation of financial statements, and preparing budgets and financial forecasts.

The overall goal of the firm is the maximization of shareholder wealth and profit maximization or maximizing the firm’s earnings after taxes. There are risks involved in both perspectives. In maximizing shareholder wealth there is the possibility of increasing current profits while harming the firm through deferring maintenance, issuing common stock to purchase treasury bills, and ignoring changes in the risk level of the firm. Problems associated with profit maximization include the ignoring of changes in the risk level of the firm, a zero payout dividend policy, and it does not specify timing or the duration of expected returns.

Shareholder wealth maximization takes into account the current and future profits and EPS, the timing, duration, and risk of profits and EPS, dividend policy, and other factors. Profit maximization does not prohibit the firm from being socially responsible.

The DuPont system of financial control enables the financial manager to show profitability through a return on assets. This is determined by dividing the firm’s net income for the past 12 months by the total average assets. The result is a percentage which can then be shown as a return on sales or net income of sales multiplied by asset utilization or sales of assets.

Accounting practices within the firm must take into consideration inflation, disinflation, and estimation. A clause in a contract provides for increases and decreases in inflation depending on the fluctuations in the firm’s cost of living wages and production costs. Securities such as bonds or notes guarantee a higher return than the rate of inflation if the security is held to maturity.

The percentage-of-sales method calls for the budgeting based on a percent of a sales figure, such as past sales, anticipated sales, or a combination of both. The percentage-of-sales is the most commonly used method when preparing the firm’s advertising budget.

In the breakeven analyses method, the firm can determine increased sales in order to gain a profit if the product price is discounted. It may be used to show that an increased price with subsequent reduced sales may prove to be a better strategy for the firm in achieving a profit.

Of critical importance to the firm is working capital management. Financial managers spend about 70% of their time managing the short-term accounts of the firm such as current assets and current liabilities. There are several methods in which the financial manager can administer working capital including through cash conversion or the time between paying for inventory and collecting on receivables; using the time between ordering materials and collecting cash from receivables wisely; the accounts receivable period or the average time between when a product is sold and cash is received.

Strategies such as stretching out accounts payable, turning over receivables as quickly as possible, and utilizing just-in-time inventory methods can be used to hold down the firm’s investment in inventories.

The concepts of time-value money can be used to evaluate investment opportunities such as real estate, life insurance, and mortgages. The future value of money is the sum of money invested today that will grow based on an appreciation rate. The formula for interest compounded monthly is: principal time rate times the term in years. Present value is the value in today’s dollars which is assigned to an amount of money for the future, based on an estimated rate-of-return over the long-term. Rate-of-return is calculated based on monthly compounding. Valuation, the process of determining the value of stocks and bonds, also helps the financial manager in determining the cost of financing projects for the firm. The present value of a financial asset must be known. The valuation of bonds provides investors with interest payments and the principal which is returned to the investor at the bond’s maturity. Interest payments are typically paid out semiannually.

The value of common stock is the present value of an expected stream of future dividends. Earnings must be translated into cash flows for the shareholder. If the shares of common stock do not pay dividends, then they are valued just like shares of preferred stock. Preferred stock is valued as perpetuity because it has no maturity date. It carries a fixed dividend payment and can be calculated by dividing the fixed dividend payment by the required rate of return for the investor.

The weighted average cost of capital represents the expected return on all the firm’s securities. Capital including stocks, bonds, and other debt, are given weight in the calculation according to its importance in the firm’s capital structure.

Capital budgeting or the process of choosing the firm’s long-term capital assets, takes into consideration payback or the length of time it takes to recover the initial cost of the project without regard to the time value of money. The internal rate of return takes into account the discount rate at the net present value investment of zero. The rate of a bond’s future cash flows, discounted back to today, equals its price. The net present value of the expected future cash flows is minus the cost.

The Securities and Exchange Commission focuses on protecting investors and maintaining the integrity of the securities markets. Stocks, bonds and other securities can lose value. The SEC provides rules and regulations that govern this industry in the U.S. The concept behind the SEC is that all investors must have access to basic facts about an investment before purchasing it. The SEC requires that all public companies disclose their financial information to the public so that investors can judge for themselves whether or not a stock or bond is a good investment. The SEC also oversees stock exchanges, brokers and dealers, investment advisors, mutual funds, and public utility holding companies.

Securities sold in the U.S. must be registered with the SEC. Registration and its accompanying information become public shortly after filing. However, not all securities need to be registered.

Private offerings to a limited number of people or institutions, offerings of limited size, intrastate offerings, and the securities of municipal, state and federal governments are excluded from the registration process.

Care Drivers for increased Medicaid funding online history assignment help: online history assignment help

Health Care Drivers for increased Medicaid funding: A study in the United States.

The Per capita health care spending has increased to about 2,814 in 1990 to more than $7,000 today. With such increased amounts, it is obvious that everyone in America would not be able to afford such so much. This led to the creation and the need for a program like Medicaid. Medicaid is basically a national health insurance program for people with low income. In the year 2000, about 42.7 million people received Medicaid. (Einhorn 25) This shows that Medicaid itself was a program that was a crucial factor in the medical necessities of a lot of people. The demand for health care is still expected to increase thus making an even larger part of the national economy. (Hall and Jones) Data from the National Health Interview Survey from 1997

About Medicaid

Medicaid was itself established in 1965 originally to assist states to provide medical assistance on their own choice. Thus this program was reserved for families who are either old, disable or blind. It also targeted persons whose income was low and resources weren’t sufficient to meet costs of the medical bills. This was the program was initially about. Both Medicaid and Medicare were effective in mid-1966. Even though Medicare was the one that was supported fully by the government, Medicaid however wasn’t. Thus, Medicaid and Kerr-Mills basically became an extension of the coverage

Eligibility

The eligibility criteria for Medicaid have always been a controversial topic since long. Currently, there are about 60 million people in the United States that receive Medicaid funded services. First, the boldest criteria’s will be mentioned. A major criterion for the Medicaid services is that the person should be in a medical necessity. In other words, general physician checks ups are not necessarily funded by Medicaid. Another big criterion is that the Medicaid is the last resort for the patients who require assistance in paying their bills. Thus, they will only be eligible if other financial sources or routes will not pay for the medical bills. The participants should have freedom of choice of the provider and the services that are usually there, they are available statewide.

The Medicaid and the CHIP program cover children, pregnant women, seniors, parents and individuals with disabilities. The government requires certain criteria for an individual to be available to attain Medicaid care. It should be seen that the States set the individual eligibility criteria concerning what the federal poverty level for that region is. A lot of states have increased their coverage thus making more and more people eligible. In 2011, the FPL for a family of four was $22,350 per anum. (Medicaid) This is altered every year thus altering the requirements and the eligibility almost every year.

This topic is of primary concern now because of the reforms that have been carried out in America after the passing of the Affordable Care Act of 2010. The basic aim for this reform is so that more and more people would be insured somehow. This act basically sets a minimum eligibility of 133% of the federal poverty level for all the Americans under the age of 64. This is set to get into effect in 2014 but considering the economic situation of the country, it might be effective before as well.

Even though it appears that Medicaid is quite lenient in providing services, it should be noted that many states have very restrictive Medicaid eligibility requirements. A research carried out in the Brigham and Women’s Hospital states that due to restrictive Medicaid Policies, a lot of patients are delaying medical care. (Clark) These are basically states and countries where the individuals need to be far off from the FPL in order to qualify in these programs. Clark states that even though the causes could be many, they are the main reason health care access are hindered in these areas. This is a problem because the patients are delaying the medical care that is quite urgent and is needed. A major way through way the health care access can be enhanced is by increasing the number of primary care providers. (Clark)

Major research question.

It is seen that over the years, the amount of money that the state and the government has to allocate for Medicaid has increased quite a lot. The major research question is what are the main drivers behind increased Medicaid funding in the United States? This research will collectively look at the Medicaid programs in the entire country. It will especially look at the reforms made in the program and why these reforms were necessary. Surely, there had to be some problems or hindrances in the program that caused in to alter its main goals. Furthermore, the statistics from the entire Medicaid history will be looked at. Special emphasis will be given to how Medicaid is planning to evolve subsequent to the passing of the Adorable Care Act of 2010.

The Basics of Medicaid

Before we get into why the need for funding has raised, it should be reviewed how the program actually functions. As mentioned earlier, Medicaid was initially made such that every state functioned on its own. In other words, the state basically chose itself how much it wants to fund or how much it wants to allocate its budge. One thing however is clear that every state has to function under the Medicaid State plan. The federal government basically devices the Medicaid services and states have to argue and basically chose the sort of coverage that they provide. The State also chooses which persons are eligible, the services it will prove, payment levels and providers. It should be noted that the State basically goes on to share the cost of Medicaid with the Federal government share known as FMAP.

Theory

In the research carried out the dependent variable is the change in expenditure or funding of Medicaid. What we are basically looking at is that which factors caused the changes in expenditure. Therefore, these factors would be the independent variable.

Reasons for funds

The most commonly used Medicaid services are prescribed drugs and physician services. (Grannemann and Pauly 7) the hospital out care facilities are used by about 44% of the recipients. This especially goes for those persons who have access to very large care units. About 73% of the Medicaid Payments goes to look after institutions such as hospitals, mental hospitals, nursing homes and intermediate care facilities. (Grannemann and Pauly 8) Nursing home services do not require that much contribution by Medicaid. This is because most of the elderly have some amount of money, thus they are able to pay for themselves. This basically gives an idea of what most of the funds are spent on. However, later we will see that the expenditure of Medicaid is not directly related to the number of cases enrolled alone. Other causes like dynamic policies and economic changes play a crucial role as well.

Problems in Medicaid

In 2010, the average health expenditure in the United States was 2.6trillion in 2010. This was about 8,402 per person or 17.9% of the GDP. (CMS) Out of all this expenditure, Medicaid had provided about 401.3 billion dollars. This is about 15% of all the health care expenditures of the same year. As mentioned before, the eligibility criteria are responsible for the creation of many problems. Since Medicaid is based entirely on blind, disable, age or families who have dependent children. However, many people who are residing below the poverty line, they are not eligible for Medicaid. Thus, a lot of families who are very much deserving and are in need for funded medical care do not receive the benefits of Medicaid.

Data Sources

The data that has been collected has been an amalgamation of newspaper articles and journals on the spending patterns of Medicaid. Furthermore, specific tables and charts have been incorporated from Kaiser foundation web pages and other pages with tabulated expenditures of the program.

Findings

Category

Medicaid & CHIP

Subcategory

Medicaid Spending

Growth in Medicaid Spending, FY90-FY10

Full Title

Average Annual Growth in Medicaid Spending, FY1990 – FY2010

Data Type

Percent

FY 1990-2001

FY 2001-2004

FY 2004-2007

FY2007-2010

Alabama

0.1238

0.0809

0.039655

0.049

Alaska

0.129

0.1524

0.023355

0.082

Arizona

0.1537

0.2277

0.10259

0.123

Arkansas

0.1116

0.1066

0.049142

0.084

California

0.1062

0.0851

0.050631

0.054

Colorado

0.1339

0.0695

0.035946

0.114

Connecticut

0.0941

0.0625

0.028911

0.097

Delaware

0.1513

0.1018

0.076806

0.092

District of

Hampshire

0.1319

0.0958

0.000583

0.046

New Jersey

0.1055

0.0379

0.036914

0.047

New Mexico

0.1573

0.1475

0.058765

0.093

New York

0.0919

0.0911

0.021233

0.055

North Carolina

0.1397

0.098

0.055272

0.035

North Dakota

0.0675

0.0623

0.011742

0.106

Ohio

0.0915

0.1105

0.03725

0.053

Oklahoma

0.1018

0.0723

0.091835

0.069

Oregon

0.1575

-0.0065

0.032613

0.114

Pennsylvania

0.1241

0.0892

0.0392

0.056

Puerto Rico

Residence Unknown

Rhode Island

0.0939

0.1159

0.013021

0.037

South Carolina

0.1238

0.0877

0.01503

0.075

South Dakota

0.0968

0.0648

0.028943

0.082

Tennessee

0.1298

0.0862

0.003154

0.061

Texas

0.1291

0.1159

0.081075

0.097

United States

0.109

0.093808

0.036112

0.068

Utah

0.1071

0.1401

0.035696

0.073

Vermont

0.1326

0.0988

0.040851

0.114

Virgin Islands

Virginia

0.1048

0.0829

0.080009

0.092

Washington

0.1229

0.0669

0.027831

0.068

West Virginia

0.1293

0.0774

0.036499

0.055

Wisconsin

0.0954

0.0357

0.032367

0.097

Wyoming

0.1251

0.1453

0.053867

0.075

Notes

All spending includes state and federal expenditures. Growth figures reflect increases in benefit payments and disproportionate share hospital payments; growth figures do not include administrative costs, accounting adjustments, or costs for the U.S. Territories.

Definitions

Federal Fiscal Year: Unless otherwise noted, years preceded by “FY” on statehealthfacts.org refer to the Federal Fiscal Year, which runs from October 1 through September 30.  for example, FY 2009 refers to the period from October 1, 2008 through September 30, 2009.

Sources

Urban Institute estimates based on data from CMS (Form 64) (as of 12/21/11).

From this entire chart, the entire increase in expenditure of Medicare was the most from the year 1990-2001. For United States, the entire increase was 10.9% in those years. Comparatively, the increase that occurred in the year 2007-2010 was only 6.8%. Even though the magnitude of growth was not the same, more or less Medicaid did have to increase its spending though out these years.

This graph basically gives a general idea of how Medicaid expenditure has grown exponentially ever since it started. Details of its expenditure trends will be discussed more below.

This graph was basically provided by the Washington Post. It shows how states are allotting more of their funds to health care as oppose to spending on education in the long run. As it will be discussed below, spending by Medicaid increased from 2010 to 2012 due to decreased federal funds. Future trends will be emphasized below.

Discussion.

It should be noted that when Medicaid started, it went off in the pattern that most of the state-based programs go on. By 1971, the annual pending had reached about 6.5 billion where as the enrollment was about 16 million people. (Klemm 106) the enrollment growth and the coverage that the program would provide were underestimated to quite an extent. Therefore, this led to a rapid increase in the spending by the program. At that time, the total expenditure was about 52.3. In the period from 1972-176, the entire expenditure was about 17.9%. These expenditures were basically as a result of the amendments that were made to the social security act. The 1972 amendment therefore created the supplemental security income. This federalized the cash assist programs for the disabled and the aged. These amendments also led to most of the beneficiaries of the SSI to attain Medicaid as well. This caused the enrollment in the aged and elderly category to increase about 8% during that year. The time period from late 1970 to 198s was marked by medical inflation. (Klemm 107) This was a result of economy wide inflation and even higher medical costs. The inflation rose to about 8.4% during this time. Even though, there was no relevant expansion of the service, it was seen that other welfare programs were declining. Due to the increasing inflation, the Medicaid enrollment actually dropped by an average of 0.7.

Following this era, in the era of retrenchment, the congress and the federal government offered the option to state for reimbursing Medicaid benefits and for creating their own options. This allowed the states to take a break from the growing expenditures of Medicaid. This occurred mainly because the federal government had cut down the amount it would provide to the state. Thus, in order to help states with the reductions, the federal government offered these propositions. It was during this time that health maintenance organizations and other programs of the community were made. Medicaid started to alter its objective from paying claims to going for managing services and the cost of care as well. Following this era, the cost of Medicaid augmented annually at an average rate of 8% between 1981 and 1984.

Following that era, the congress basically focused on expanding the Medicaid more and more. This expansion went on to make an impact on enrollments from infants to pregnant women and to low income beneficiaries. During this period, there was also the enactment of pieces of legislation that went on to later affect the eligibility, coverage and reimbursement of Medicaid. (Klemm 109)

The time period from 1991 to 1992 was quite heavy on Medicaid. This mainly occurred due to previous mandates, increasing recession and increasing caseloads on the program. Thus, due to the change in policies and amendments, the strain on the program increased to such an extent that the average annual spending increased about 27% during this era. (Klemm 110) Following the explosion of the early nineties, Medicaid had gone to be altered in many reforms for the years ahead. The welfare reform not only occurred in the medical sector but the economy as a whole prospered during these years. This led to a drop of 0.4% per year in Medicaid spending.

Now we would take a jump to the current year and the statistics that Medicaid presents with today. The annual growth in spending on the program has slowed down significantly since the last year as the economy began to improve. (Goodnough) with the Affordable care act, more people will be eligible in 2014 as well. Goodnough feels that a major reason for increased expenditure on part of Medicaid was because of the shifting situation of the economy. When Americans lost their job and health insurance, Medicaid itself had more and more enrollment. This led to increased costs for the program.

However, last year in June, the total spending on Medicaid only augmented by 2%. (Goodnough) This is very less compared to the 10% increase that occurred in 2011. Many attribute this slowdown to not only more enrollment growth but also due to the cost cutting that many states have carried out. Diane Rowland, who is the executive vise president of the Kaiser Family Foundation, stated that the major reason for the decreasing spending is due to the reining in costs.

The major cuts that were made were to reimbursement rates for hospitals and doctors. Also optional benefits like vision, dental and drug coverage was also cut down. (Goodnough) Out of fifty, about fort five states froze reimbursement rates the previous year. Similarly, many cut back on the benefits that it provided to the masses. The previous year, Medicaid spending increased about 27.5% since the extra federal Medicaid fund stopped coming. This in turn did put a lot of pressure on the state which caused it to cut down its cost as well. Thus, we should see that this is more of a viscous cycle that occurs. When the government stops giving funds to the state, the state cuts down some of the benefits and reimburses some of the funds. This in turn decreases the spending of the state and the entire Medicaid program for that matter. Therefore, it should be seen that the Medicaid spending over the years has not only been dependant on the inflow of enrollments but on the legislature and the policies that have been created overtime. Along with the aforementioned factors, it is obvious that the current state of the economy and the way other health programs are going will also have an impact on the spending.

Limitations

The analysis and conclusion that we came up with are subject to a number of limitations. Medicaid as a program has been applied differently in different states in the United States. As mentioned in the discussion, the Reagan administration allowed states to set their own rules for how much they want to cover and their own eligibility criteria. This therefore renders it difficult for us to assess the cost and apply these assessments to the entire Medicaid program. Medicaid program is split into different areas and thus one major conclusion will not be quite accurate. Furthermore, there have been changes in health care technology, drugs and further environment and social changes that have affected the general population as well. In simpler terms, it means that the funding alterations cannot be solely accredited to the policy changes or the changing political ideologies.

Reliability

Scale: ALL VARIABLES

Reliability Statistics

Cronbach’s Alpha

Cronbach’s Alpha Based on Standardized Items

N of Items

.816

.807

Item Statistics

Mean

Std. Deviation

Hospitals

2.1744

.54361

Elderly

2.2752

.67303

Children.Funds

2.2093

.60498

Drugs

2.2287

.45931

Cost.of.Med.Aid

2.0853

.34017

Inter-Item Correlation Matrix

Hospitals

Elderly

Children.Funds

Drugs

Cost.of.Med.Aid

Hospitals

1.000

.450

.678

.387

.083

Elderly

.450

1.000

.841

.484

.374

Children.Funds

.678

.841

1.000

.508

.425

Drugs

.387

.484

.508

1.000

.330

Cost.of.Med.Aid

.083

.374

.425

.330

1.000

Summary Item Statistics

Mean

Minimum

Maximum

Range

Maximum / Minimum

Variance

N of Items

Item Means

2.195

2.085

2.275

.190

1.091

.005

Item Variances

.288

.116

.453

.337

3.914

.017

Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlation

Squared Multiple Correlation

Cronbach’s Alpha if Item Deleted

Hospitals

8.7984

2.861

.543

.569

.799

Elderly

8.6977

2.218

.740

.742

.739

Children.Funds

8.7636

2.201

.885

.844

.682

Drugs

8.7442

3.067

.546

.303

.798

Cost.of.Med.Aid

8.8876

3.560

.374

.288

.837

ANOVA with Tukey’s Test for Nonadditivity

Sum of Squares

Mean Square

Between People

.831

Within People

Between Items

2.610

.653

Residual

Nonadditivity

9.909a

9.909

Balance

68.181

.133

Total

78.090

.153

Total

80.700

.156

Total

.290

Grand Mean = 2.1946

a. Tukey’s estimate of power to which observations must be raised to achieve additivity = -9.529.

ANOVA with Tukey’s Test for Nonadditivity

Sig

Within People

Between Items

4.278

.002

Residual

Nonadditivity

74.267

.000

Grand Mean = 2.1946

Hotelling’s T-Squared Test

Hotelling’s T-Squared

df1

df2

Sig

17.390

4.246

.003

Intraclass Correlation Coefficient

95% Confidence Interval

Intraclass Correlationa

Lower Bound

Upper Bound

Single Measures

.471b

.389

.556

Average Measures

.816c

.761

.862

Two-way mixed effects model where people effects are random and measures effects are fixed.

a. Type C intraclass correlation coefficients using a consistency definition — the between-measure variance is excluded from the denominator variance.

b. The estimator is the same, whether the interaction effect is present or not.

c. This estimate is computed assuming the interaction effect is absent, because it is not estimable otherwise.

Intraclass Correlation Coefficient

F Test with True Value 0

Value

df1

df2

Sig

Single Measures

5.449

.000

Average Measures

5.449

.000

Two-way mixed effects model where people effects are random and measures effects are fixed.

Regression

Variables Entered/Removedb

Model

Variables Entered

Variables Removed

Method

Drugs, Hospitals, Elderly, Children.Fundsa

Enter

a. All requested variables entered.

b. Dependent Variable: Cost.of.Med.Aid

Model Summaryb

Model

R Square

Adjusted R. Square

Std. Error of the Estimate

.537a

.288

.265

.29160

a. Predictors: (Constant), Drugs, Hospitals, Elderly, Children.Funds

b. Dependent Variable: Cost.of.Med.Aid

Model Summaryb

Model

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

Durbin-Watson

.288

12.550

.000

1.734

b. Dependent Variable: Cost.of.Med.Aid

ANOVAb

Model

Sum of Squares

Mean Square

Sig.

Regression

4.268

1.067

12.550

.000a

Residual

10.544

.085

Total

14.812

a. Predictors: (Constant), Drugs, Hospitals, Elderly, Children.Funds

b. Dependent Variable: Cost.of.Med.Aid

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

Std. Error

Beta

Sig.

(Constant)

1.602

.142

11.268

.000

Hospitals

-.269

.068

-.430

-3.950

.000

Elderly

-.078

.075

-.155

-1.043

.299

Children.Funds

.422

.101

.750

4.180

.000

Drugs

.141

.066

.190

2.136

.035

a. Dependent Variable: Cost.of.Med.Aid

Coefficientsa

Model

Collinearity Statistics

Tolerance

VIF

Hospitals

.485

2.061

Elderly

.260

3.839

Children.Funds

.178

5.607

Drugs

.722

1.384

a. Dependent Variable: Cost.of.Med.Aid

Coefficient Correlationsa

Model

Drugs

Hospitals

Elderly

Children.Funds

Correlations

Drugs

1.000

-.109

-.148

-.105

Hospitals

-.109

1.000

.313

-.602

Elderly

-.148

.313

1.000

-.787

Children.Funds

-.105

-.602

-.787

1.000

Covariances

Drugs

.004

.000

Hospitals

.000

.005

.002

-.004

Elderly

.000

.002

.006

-.006

Children.Funds

.000

-.004

-.006

.010

a. Dependent Variable: Cost.of.Med.Aid

Collinearity Diagnosticsa

Model

Dimension

Variance Proportions

Eigenvalue

Condition Index

(Constant)

Hospitals

Elderly

4.884

1.000

.00

.054

9.529

.20

.01

.14

.035

11.851

.04

.54

.08

.019

15.910

.70

.01

.05

.008

25.185

.06

.44

.74

a. Dependent Variable: Cost.of.Med.Aid

Collinearity Diagnosticsa

Model

Dimension

Variance Proportions

Children.Funds

Drugs

.00

.04

.06

.01

.13

.00

.81

.95

.00

a. Dependent Variable: Cost.of.Med.Aid

Residuals Statisticsa

Minimum

Maximum

Mean

Std. Deviation

Predicted Value

1.5907

2.5293

2.0853

.18261

Residual

-.64876

1.24087

.00000

.28700

Std. Predicted Value

-2.708

2.432

.000

1.000

Std. Residual

-2.225

4.255

.000

.984

a. Dependent Variable: Cost.of.Med.Aid

Charts

Descriptives

Descriptive Statistics

Minimum

Maximum

Mean

Std. Deviation

Skewness

Statistic

Std. Error

Hospitals

1.00

3.50

2.1744

.54361

-.178

.213

Elderly

1.50

4.00

2.2692

.67386

1.702

.212

Children.Funds

1.50

4.00

2.2077

.60291

1.145

.212

Drugs

1.50

3.50

2.2269

.45797

1.183

.212

Cost.of.Med.Aid

1.25

3.75

2.0846

.33894

2.130

.212

Valid N (listwise)

Descriptive Statistics

Kurtosis

Statistic

Std. Error

Hospitals

-.477

.423

Elderly

2.122

.422

Children.Funds

.695

.422

Drugs

.553

.422

Cost.of.Med.Aid

6.714

.422

Frequencies

Statistics

Hospitals

Elderly

Children.Funds

Drugs

Cost.of.Med.Aid

Valid

Missing

Mean

2.1744

2.2692

2.2077

2.2269

2.0846

Median

2.0000

Mode

2.50

2.00

Std. Deviation

.54361

.67386

.60291

.45797

.33894

Variance

.296

.454

.364

.210

.115

Skewness

-.178

1.702

1.145

1.183

2.130

Std. Error of Skewness

.213

.212

Kurtosis

-.477

2.122

.695

.553

6.714

Std. Error of Kurtosis

.423

.422

Minimum

1.00

1.50

1.25

Maximum

3.50

4.00

3.50

3.75

Frequency Table

Hospitals

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1.00

4.6

4.7

1.50

17.7

17.8

22.5

2.00

30.0

30.2

52.7

2.50

33.1

33.3

86.0

3.00

13.1

13.2

99.2

3.50

Total

99.2

Missing

System

Total

Elderly

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1.50

10.8

2.00

59.2

70.0

2.50

16.9

86.9

3.00

2.3

89.2

4.00

10.8

Total

Children.Funds

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1.50

18.5

2.00

48.5

66.9

2.50

20.0

86.9

3.50

12.3

99.2

4.00

Total

Drugs

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1.50

4.6

2.00

66.9

71.5

2.50

10.0

81.5

3.00

15.4

96.9

3.50

3.1

Total

Cost.of.Med.Aid

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1.25

1.50

1.5

1.75

13.1

14.6

2.00

64.6

79.2

2.25

4.6

83.8

2.50

11.5

95.4

3.00

1.5

96.9

3.25

2.3

99.2

3.75

Total

Bar Chart

This 53% change is caused by the variables included in the research and the remainder 47% variance in the social phenomenon is caused by other factors.

Hence this research covers a major part of the variables which cause the change in the data whereas other aspects could be social, economical, and demographic or otherwise which cause the 47% variation. The model fitness is good since the major percentage change is covered in the statistical analysis.

The Durbin Watson value is 1.7 which shows positive correlation in the data set and it is favorable to the research function.

The F. value is 12 which is positive so that the respective hypothetical outcomes presented in the start of the research are accepted

The degree of freedom (df) is 4 and 124 on upper and lower level which gives a large room for the variations to take place in the real life phenomenon and hence the statistical data confirms that the change is cost is majorly due to the independent variables.

References

Clark, Cheryl et al. “State Medicaid Eligibility and Care Delayed Because of Cost.” New England Journal of Medicine, 368 (2013): 1263-1265. Print.

Ellwood, Marilyn Rymer et al. An Exploratory Analysis of the Medicaid Expenditures of Substance Exposed Children Under 2 Years of Age in California. U.S. Department of Health and Human Services, 1993. Print.

Goodnough, Abby. “October 25th.” The New York Times. 25th October. 2012. Web. 29th March 2013. [http://www.nytimes.com/2012/10/26/us/spending-on-medicaid-has-slowed-survey-finds.html?_r=0].

Grannemann, Thomas W. And Mark V Pauly. Controlling Medicaid Costs: Federalism, Competition, and Choice. Washington DC: American Enterprise Institute, 1983. Print.

Hall, R and C. Jones. “The Value of Life and the Rise in Health Spending.” The Quarterly Journal of Economics, 122. 1 (2007): Print.

Klemm, John D . “Medicaid Spending: A Brief History.” Health Care Financing Review, 22. 1 (2000): Print.

Kliff, Sarah. “Graph of the day: States are spending more on Medicaid, less on education.” Washington Post, December 14th. 2012: Print.

Medicaid.gov. “Eligibility | Medicaid.gov.” 2011. Web. 28 Mar 2013. .

Medicalxpress.com. “Restrictive Medicaid eligibility criteria associated with higher rates of delayed medical care.” 2013. Web. 28 Mar 2013. .

Statehealthfacts.org. “Growth in Medicaid Spending, FY90-FY10 – Kaiser State Health Facts.” 2009. Web. 28 Mar 2013. .

Differentiation of Personal Computer Makers history assignment writing help

Product Differentiation: Personal Computer Makers

If one has gone computer shopping in the last ten years, one would have seen two computer brands present in the computer aisles in every computer store. Hewlett-Packard and Dell were the leaders in laptops, notebooks and desktop PCs Both of these companies have consistently delivered differentiated netbooks, laptop and desktop systems, with Lenovo entering the market within the last decade . when it comes to notebooks and personal computers. Both brands offer high quality PC’s at a reasonable price tag and use the Windows operating system on an Intel processor. While there are similarities among these three personal computers, differences in products exist. Lenovo, one of China’s largest and most diversified electronic manufacturers, entered the global PC market in late 2004 via the acquisition of IBM’s PC business for $1.75B (Dickie, Guerrera, Lau, London, et.al.). To fully appreciate just how different Dell, HP and Lenovo are, it’s useful to evaluate the competitive dynamics and rivalry in this industry. Figure 1, Fives Forces Model of PCs defines how each aspect of the Porter Model is driving a very high level of competitive rivalry throughout this industry.

Figure 1:

Five Forces Model of PCs

Sources: Based on the Porter Five Forces Model

(Porter, et.al)

(Dell Investor Relations) (Gunasekaran, Angappa, Ngai, 319)

Hewlett-Packard

Hewlett-Packard (HP) otherwise known has HP, has firmly established its brand as a favorite with younger, computer-literate consumers who are looking for a stylish system that can also deliver high performance in gaming, imaging, and other software-intensive tasks. An example of this positioning is their “The Computer Is Personal” campaign that features a variety of celebrities using their HP systems to create music and collaborate with each other. HP’s legacy as a high tech manufacturer is heavily based on their ability to continually innovate while reducing costs and increasing performance (Patell, 809). HP strives to design-in differentiation at the product level, taking the time to work with suppliers to develop state-of-the-art product and software configurations well ahead of the actual production process (Daniel, Guide, Muyldermans, Van Wassenhove, 282). By taking this approach to differentiation, HP can quickly move through product introductions of dozens of laptop, netbooks, and desktop PCs that all align to their core messaging and unique value. Because of this, HP has been able to create entire product lines of tablet PCs, laptops and desktops that are precisely aligned to their brand faster than any other competitor, capturing new customers and getting existing customers to trade in their existing PCs for new ones.

As can be seen from Figure 1, the PC market is consolidating quickly based on the cannibalization being brought on by tablet PCs and network-ready netbooks and notebooks. The ability to connect to any Wi-Fi network at any time, and in the case of HP’s advanced tablet PC, netbook and laptop business, the addition of EV-DO chipset that allows any device to connect to the Internet anywhere and at any time (Daniel, Guide, Muyldermans, Van Wassenhove, 285). HP continues to differentiate their product line with broad product and services offerings across their tablet PCs, netbooks and laptops. HP is striving to continually differentiate on these innovative new products while also positioning itself as a provider of cloud computing services for consumers, small businesses, and enterprises. HP will continue to differentiate with technically elegant systems that can connect to the Internet from anywhere, anytime and provide customers with the chance to share updates across the many social network sites they are members of. HP’s ability to quickly move from product concept to product introduction and quickly ramp sales is predicated on how well the company is managing its suppliers, all aligned at delivering high performance systems to customers. They differentiate on a unique brand backed up with strong supply chain and production expertise.

Dell

Dell Computer began in the dorm room of founder and CEO Michael Dell while he was attending the University of Texas. He quickly realized that create build-to-order PCs at affordable prices for students was a sizable and highly profitable business to be in (Dell Investor Relations). Over the next two decades the rise of e-commerce as a viable selling channel would propel Dell Computer into a global business generating sales in excesss of $1B a year primarily through their innovative build-to-order selling strategies supported by online product configurators (Dell Investor Relations). Dell was often considered a primary disintermediator of the channel structures of the PC market as a result, with many e-commerce experts saying their model was the future of merchandising and channel management (Gunasekaran, Ngai, 425). Today Dell sells through both its massive direct channels including its global series of e-commerce websites that on high volume days can generate over $250M in sales alone, which is a significant soruce of revenue for this $50B+ business (Dell Investor Relations). Its indirect sales channels include Best Buy, Costco, Walmart and others, and this channel also generates a signficant proportion of revenue as well.

All of these lessons learned have made Dell a formidable competitor in the global PC market. Their primary differentiation is based on the ability to customize a PC for any customer, anywhere in the world, and deliver it within 72 hours providing overnight delivery is available (Dell Investor Relations). Dell differentiates on the ability to quickly take orders and send out customized PCs regardless of the complexity of the given configuration as well, which is a strength based on their intensive supply chain integration expertise (Gunasekaran, Angappa, Ngai, 319). Dell can make commitments to customers and meet or exceed them based on how well integrated their supply chyains are to each of the product configuraiton strategies they have. Figure 2 is derived from an analysis of the Dell Annual Reports and filings with the Securities and Exchange Commission (SEC). Depending on the level of customization, Dell uses a different selling strategy. Assemble-to-order products take the least customization and engineer-to-order, the most. Dell has found differentiating selling strategies can help them to capture more sales and attreact the right kind of customers for the best possible products.

Figure 2: Comparing the Differentiated Selling Strategies of Dell Corporation

Source: (Dell Investor Relations)

In conclusion, Dell differentiates through the use of a very rapid tablet, netbook and laptop product introductions and a continual stream of new products across its many product divisions. In conjunction, this differentiaiton strategy has the goal of providing customers with greater flexibility than any other tablet, netbook, laptop or PC manufacturer in terms of product configuration and customization (Gunasekaran, Ngai, 426). Of the three companies in this analysis Dell competes best on accuracy of custom configurations and speed of their new product development and time-to-market strategies. They are also the quickest at adopting new technoplogies from Intel and other suppliers, which translates into exceptional price/performance for their consumer and corporate customers.

Lenovo

Lenovo is the world’s second-largest PC vendor. Its popularity stems from its ThinkPad line of notebooks, which have become almost a standard among business professionals as many companies were offering them as complimentary machines for work. Lenovo had previously been one of the world leaders in electronics component production and research, and today is considered one of the leading high technology manufacturers in China. Their acquisition of the IBM PC business including the flagship ThinkPad Series began in 2004 and was completed in 2005 for $1.75B (Dickie, Guerrera, Lau, London, et.al.). Lenovo is known as a far more risk-taking culture than IBM, and promtply began morphing the ThinkPad product design into tablet and netbook PCs, often displaying them at the Consumer Electronics Show every January in Las Vegas, Nevada. Lenovo senior management wanted to add some vitality and energy to the brand of the ThinkPad and also quickly began showing advaned graphics processes and the ability to have a disconnected tablet — which was far ahead of the current Google Android-powered devices so prevalent in 2013. This paradoxically has helped Lenovo with its core differentiation strategy around being the de facto PC for enteprise customers.

IBM had allowed the ThinkPad to become boring, and fall behind competitors in terms of features. Despite the Thinkpad being one of the best-selling PCs for enterprises, more companies were looking to Dell for greater customizable flexibility and HP for higher performance. Consumers were bored with Lenovo, seeing their systems as being ideal for large business or the enteprirse yet lacking in what they needed. Lenovo quickly differentiated their PCs with netbooks and laptops with advanced graphics displays and more control over the performance parameters, going so far as to create a product configurator consumers could use to design their own high performance systems (Xie, Wei, and Steven White, 413). Lenovo also started differentiating through EV-DO chipsets that made it possible to connect to the Internet from any of their devices at any time. The combination of their emerging tablet PCs and netbooks with the combination of EV-DO-based systems rejuvenated Lenovo and made it more competitive. Lenovo has a commanding market share in China, and is considered in the top three of PC producers on a consistent yearly basis there (Xie, Wei, and Steven White, 418). They have been able to gain a sizable consumer base of customers in China partially due to the nationalism PC buyers have in that country for high tech manufacturers based there. For Lenovo to gain greater market share in the U.S., they will need to continue purusing an aggressive strategy of uniqueness and allowing customers greater flexibility in how they customize systems to their own needs.

Works Cited

V Daniel, R. Guide, Jr., Luc Muyldermans, and Luk Van Wassenhove N. “Hewlett-Packard Company Unlocks the Value Potential from Time-Sensitive Returns.” Interfaces 35.4 (2005): 281-93.

Dell Investor Relations . Dell Investor Relations. 2013. Photograph. n.p. Web. 4 Apr 2013. http://www.dell.com/Learn/us/en/uscorp1/about-dell-investor?c=us&l=en&s=corp

Mure Dickie, F. Guerrera, Justin Lau, Simon London. “Lenovo Buys IBM’s PC Unit for $1.75B.” Financial Times: 21. Dec 09, 2004.

Gunasekaran, a., and E.W.T. Ngai. “Build-to-Order Supply Chain Management: A Literature Review and Framework for Development.” Journal of Operations Management 23.5 (2005): 423-51.

Gunasekaran, Angappa, and Eric W.T. Ngai. “Modeling and Analysis of Build-to-Order Supply Chains.” European Journal of Operational Research 195.2 (2009): 319.

Patell, James M. “Cost Accounting, Process Control, and Product Design: A Case Study of the Hewlett-Packard Personal Office Computer Division.” The Accounting Review 62.4 (1987): 808-817.

Porter, Michael E. “The Five Competitive Forces that Shape Strategy.” Harvard business review 2008: 78-93.

Ro, Y.K., J.K. Liker, and S.K. Fixson. “Modularity as a Strategy for Supply Chain Coordination: The Case of U.S. Auto.” IEEE Transactions on Engineering Management 54.1 (2007): 172-189.

Xie, Wei, and Steven White. “Sequential Learning in a Chinese Spin-Off: The Case of Lenovo Group Limited.” R & D. Management 34.4 (2004): 407-422.

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