barcode using vb.net F I G U R E A 1 in Software

Encoding Data Matrix in Software F I G U R E A 1

F I G U R E A 1
Data Matrix ECC200 Recognizer In None
Using Barcode Control SDK for Software Control to generate, create, read, scan barcode image in Software applications.
Data Matrix Maker In None
Using Barcode generator for Software Control to generate, create Data Matrix image in Software applications.
Industry distribution.
Scanning Data Matrix 2d Barcode In None
Using Barcode decoder for Software Control to read, scan read, scan image in Software applications.
DataMatrix Generator In C#
Using Barcode creator for Visual Studio .NET Control to generate, create ECC200 image in .NET applications.
Pharmaceuticals 2% Chemicals & Applied Materials 18% Process = 26% Semiconductors 6% Telecom Equipment 11% A&D, Ind., Auto 6% Med. Dev. & Equip. 3% Computers 9% High Tech = 44% Electronic Equipment 15%
DataMatrix Creation In .NET
Using Barcode maker for ASP.NET Control to generate, create Data Matrix 2d barcode image in ASP.NET applications.
Paint Data Matrix In .NET Framework
Using Barcode encoder for .NET framework Control to generate, create Data Matrix ECC200 image in VS .NET applications.
Consumer Goods 30% Consumer Goods = 30%
Data Matrix ECC200 Generation In VB.NET
Using Barcode maker for VS .NET Control to generate, create Data Matrix 2d barcode image in VS .NET applications.
Print EAN / UCC - 13 In None
Using Barcode generator for Software Control to generate, create EAN13 image in Software applications.
Number of Businesses / Data Sets = 89
UPC-A Creator In None
Using Barcode creator for Software Control to generate, create UPC Symbol image in Software applications.
ECC200 Printer In None
Using Barcode generator for Software Control to generate, create DataMatrix image in Software applications.
Copyright 2004 The Performance Measurement Group, LLC
Making Code 39 In None
Using Barcode printer for Software Control to generate, create Code39 image in Software applications.
Draw ANSI/AIM Code 128 In None
Using Barcode printer for Software Control to generate, create Code 128A image in Software applications.
APPENDIX A Source and Methodology for Benchmarking Data
ISSN - 13 Printer In None
Using Barcode drawer for Software Control to generate, create ISSN - 13 image in Software applications.
Printing Code-128 In Objective-C
Using Barcode printer for iPad Control to generate, create Code 128C image in iPad applications.
F I G U R E A 2
EAN 13 Generation In None
Using Barcode creation for Excel Control to generate, create EAN / UCC - 13 image in Office Excel applications.
Bar Code Maker In .NET
Using Barcode creator for Visual Studio .NET Control to generate, create barcode image in Visual Studio .NET applications.
Primary manufacturing strategy.
Printing UCC.EAN - 128 In None
Using Barcode generation for Online Control to generate, create GS1 128 image in Online applications.
Decode Code 128 Code Set C In VB.NET
Using Barcode reader for .NET framework Control to read, scan read, scan image in VS .NET applications.
Engineer to Order 2%
Code 39 Extended Creator In Java
Using Barcode generator for Java Control to generate, create Code 39 Extended image in Java applications.
Barcode Creation In Java
Using Barcode creation for Java Control to generate, create bar code image in Java applications.
Make to Order 27%
Make to Stock 56%
Configure to Order 15% Number of Businesses / Data Sets = 89
Copyright 2004 The Performance Measurement Group, LLC
Quantitative performance is assessed using a detailed questionnaire that covers a set of SCOR-compliant metrics, as well as other questions designed to assess supply chain performance. High-level metrics such as delivery performance or cash-to-cash cycle time (SCOR level 1) are calculated based on responses to more detailed questions. For example, delivery performance to commit is calculated based on the number of orders delivered on time to the customer request date divided by the total number of orders delivered. More detailed metrics such as materials acquisition cost are collected using detailed definitions that break out all the various components (e.g., inbound freight and duty cost, a SCOR level 3 measure). The quantitative part of the survey also includes questions that provide further insight into supply chain operations, for example, number of weeks of firm forecast needed in advance of ship date window, as well as questions that assess processing of product returns and repairs. Qualitative performance is assessed using more than 270 questions that characterize supply chain practices in four areas: plan, source, make, and deliver, as well as a number of questions that address overall supply chain
Strategic Supply Chain Management
practices. Participating companies characterize both their dominant and emerging practices. This question set is used to characterize companies by stage of maturity.
CRITERIA FOR SELECTION OF BICCs
The BICC index was developed by selecting a small set of four of SCOR level 1 metrics (see Appendix C and 2). Based on an evaluation of the rationale for each metric, these metrics were selected to provide a representation of both customer-facing and internal-facing metrics.
Upside production flexibility was selected based on the assumption that companies with more flexible manufacturing capacity are better able to respond rapidly to and take advantage of changes in market conditions. Delivery performance to commit date was selected because companies have more influence over their performance that they commit to than they do over delivery performance to request, which varies considerably based on market demand, stability of supply, manufacturing strategy, and demand patterns. Cash-to-cash cycle time was selected for its comprehensive view of payables, receivables, and inventory levels. Despite being a component of cash-to-cash, inventory days of supply also was selected because it is such a widely used supply chain metric.
These choices are not meant to imply that these are the only metrics appropriate for measuring overall supply chain performance. The traditional and still widely used net asset turns metric was not selected because it is influenced by the company s choice of capital structure (i.e., short- and longterm debt-to-asset ratio). Similarly, order-fulfillment lead time was avoided because a large part of its variation can be attributed to primary manufacturing strategy. Total supply-chain management cost was considered, but this also was dropped because the companies with the lowest total supply chain management cost may not reflect the best supply chain performance (e.g., low materials acquisition, order management, and inventory management costs often are the result of spending on supply chain systems or a company s outsourcing strategy). Other level 1 metrics, such as assert turns, were not included because they are considered to be dependent on other metrics.
APPENDIX A Source and Methodology for Benchmarking Data
In order to remove industry bias within the metric values, each of the four components of the index was normalized for each organization over the industry average for the organization. For example, if a specific consumer-goods company s delivery performance is 99 percent, and the consumer goods industry average for delivery performance is 90 percent, then the company s normalized delivery performance value = (99/90), or 1.1. The score derived from the sum of the four normalized values produces the BICC index. The BICC index was used to segment the population into three subpopulations:
Best-in-class companies (BICCs). Top 25 percent of the population, or 22 companies in this case. Median companies (median). Middle 26 to 75 percent of the population, not the statistical median, or 45 companies. Worst-in-class companies (WICCs). Bottom 25 percent of the population, or 22 companies.
Copyright © OnBarcode.com . All rights reserved.