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Software Functionality Revealed in Detail
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 wholesale trade data


Case Study: Noble Trade
Noble Trade, a wholesale distributor of industrial materials, lacked a customer relationship management (CRM) system. Customer data wasn’t organized, and

wholesale trade data  Trade Noble Trade, a wholesale distributor of industrial materials, lacked a customer relationship management (CRM) system. Customer data wasn’t organized, and customer activity history was being lost. To address these issues, managers selected Microsoft® Dynamics CRM Online as the company’s CRM solution. One of the benefits is better collaboration between sales and service, leading to increased customer satisfaction.

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Software Functionality Revealed in Detail

We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.

Get free sample report
Compare Software Solutions

Visit the TEC store to compare leading software by functionality, so that you can make accurate and informed software purchasing decisions.

Compare Now

International Trade Logistics (ITL) RFI/RFP Template

Collaboration, Content, Commerce, Product Technology  

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Documents related to » wholesale trade data

Giving Trade Companies a Fast Start: SAP Business All-in-One Fast-start Program


As a midsize wholesale distributor, you need to stand out from your competition while improving efficiency. SAP Business All-in-One Solutions offer software designed to help you with your current needs, while remaining capable of supporting future growth. Find out how this solution can help you improve transparency and coordination between the warehouse and the executive suite, but also streamline inventory management.

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TEC Industry Watch: Enterprise Software News for the Week of July 9, 2012


SOFTWARE SELECTIONSInternational distributor of high-tech metals and alloys selects Epicor ERPIndustry tags: Manufacturing, Wholesale and Retail Trade, Warehousing "The relatively small but geographically extensive company Datum Alloys made its choice based on a few underlying premises: a need for multicurrency operations in conjunction with local accounting standards, high-quality analytical

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JDA Portfolio: For the Retail Industry -- Part Five: Analysis of Market Impact


Given the competition for retail customers and wholesale orders is intense, retailers, including software vendors, must be able to meet consumer demand quickly, accurately and at the most competitive price. Despite its failed QRS acquisition, which promised to expand JDA's retail demand chain optimization applications, JDA Portfolio may be able to help retailers if it can overcome the challenges of servicing a fragmented sector and withstand the increasing competition.

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SaaS Buyer's Guide for Wholesale and Distribution


SaaS, despite its phenomenal popularity, is certainly not one-size-fits-all. You need to consider decision criteria such as fit, return on investment, and risk. Learn how SaaS works, who the major vendors are, how SaaS can help your business grow, and how to find the SaaS solution that’s right for you. It’s all in this comprehensive SaaS Buyer’s Guide for Wholesale and Distribution from TEC and SupplyChainBrain.

From a business requirements perspective, the defining characteristic of wholesale and distribution (W&D) organizations is that they operate as intermediate agents between manufacturers and retailers. Their top business needs thus focus on requirements for:

  • processing high volumes of transactions,
  • maintaining constant communication between upstream and downstream collaborators (manufacturers and retailers/customers, respectively), and
  • managing products for multiple competitors within the same warehouse or distribution center

In this guide we will explore considerations for W&D organizations that are considering adoption of the SaaS delivery model, and examine the particular business issues that arise from this change.Specifically, we will address the following considerations:

  • the differences between SaaS and on-premise delivery models
  • SaaS architectures
  • SaaS pros, cons, and other considerations
  • selection criteria for SaaS-based applications
  • viable wholesale and distribution SaaS vendors

Later in this guide, we’ll provide examples of SaaS delivery model success stories, as well as a SaaS IT directory, segmented according to business area.


Table of Contents


Preface

Software as a Service: A Buyer’s Guide


Spotlight on Adaptability and Agility

Thought Leadership from SAP
SAP’s Perspective on Software as a Service

SAP Case Study
Johnson Products Capitalizing on New Sales after 30-day SAP Deployment


Spotlight on Manufacturing and Distribution

Thought Leadership from Epicor
SaaS ERP for Small Manufacturers and Distributors

TECSYS Case Study
LifeScience Logistics Achieves 99.97% Inventory Accuracy with TECYS’ EliteSeries for Healthcare


Spotlight on Growing Your Company with SaaS

Thought Leadership from NetSuite
The Benefits of a Business Management Software Suite for High-growth and Midsized Businesses: Overcoming the Barriers of Stand-alone Business Applications

NetSuite Case Study
Woodworking Machinery Maker Cuts Costs, Grows Efficiency with NetSuite

NetSuite Case Study
NetSuite Helps Manufacturer Take Advantage of Fast Market Growth


Spotlight on Distribution Centers

Thought Leadership from Bond International Software
Cloud Computing for Your Distribution Workforce

IBS Case Study
Konaflex Focuses on its Core Business with IBS Distribution Management Software


Vendor Directory


Download the full copy of the TEC 2010 SaaS Buyer’s Guide for wholesale and distribution.



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What Are the Differences between the SaaS and On-premise Delivery Models?



Defining the on-premise delivery model is relatively straightforward:

  • The software is acquired by the customer up-front.
  • The software is installed, deployed, managed, and maintained at the customer’s site, generally with a great degree of involvement by the customer.
  • The customer provides the in-house infrastructure (e.g., servers, hardware, networks) to support the software.


Defining the SaaS model is slightly more complex, since different SaaS vendors offer different definitions. We’ll explore these variations in more detail shortly, but for now we’ll note the following SaaS characteristics:

  • The software vendor provides customers with access to the software via the Internet.
  • The customer pays for this service on a subscription basis (normally per user, per month, or per number of transactions).
  • The vendor is responsible for maintenance, upgrades, and software support, as well as the supporting infrastructure.

The major difference between the on-premise and SaaS delivery model lies in the ownership of the software. In the on-premise model, once the software is purchased, the customer owns it. In the SaaS delivery model, the software is not owned by the customer: it is provided to the customer in the same manner as any other service.


Download the full copy of the TEC 2010 SaaS Buyer’s Guide for wholesale and distribution.

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Data Quality: Cost or Profit?


Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and company policies that set expectations and establish data management procedures, we will explore applications and tools that help reduce the negative impact of poor data quality. Some CRM application providers like Interface Software have definitely taken data quality seriously and are contributing to solving some data quality issues.

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Data Migration Management: A Methodology to Sustaining Data Integrity for Going Live and Beyond


For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet the business impact can be significant and detrimental to business continuity when proper data management is not applied. By embracing the five phases of a data migration management methodology outlined in this paper, you can deliver a new system with quality data.

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Agile Data Masking: Mitigate the Threat of Data Loss Prevention


You may not be as protected from data loss as you think. This infographic looks at some ways in which an enterprise's data can be compromised and vulnerable to security breaches and data loss, and shows how data masking can mean lower security risk and increased defense against data leaks.

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The Value of Big Data


As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value.

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The Path to Healthy Data Governance


Many companies are finally treating their data with all the necessary data quality processes, but they also need to align their data with a more complex corporate view. A framework of policies concerning its management and usage will help exploit the data’s usefulness. TEC research analyst Jorge Garcia explains why for a data governance initiative to be successful, it must be understood as a key business driver, not merely a technological enhancement.

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Data Blending for Dummies


Data analysts support their organization’s decision makers by providing timely key information and answers to key business questions. Data analysts strive to use the best and most complete information possible, but as data increases over time, so does the time required to identify and combine all data sources that might be relevant.

Data blending allows data analysts a way to access data from all data sources, including big data, the cloud, social media sources, third-party data providers, department data stores, in-house databases, and more, and become faster at delivering better information and results to their organizations. In the past, the challenge for data analysts has been accessing this data and cleansing and preparing the data for analysis. The access, cleansing, and preparing data stages are complex and time intensive. These days, however, software tools can help reduce the burden of data preparation, and turn data blending into an asset.

Read this e-book to understand why data blending is important, and learn how combining data means that you can get answers to your business questions and better meet your business needs. Also learn how to identify what features to look for in data blending software solutions, and how to successfully deploy these tools within your business. Data Blending for Dummies breaks the subject down into digestible sections, from understanding data blending to using data blending in the real world. Read on to discover how data blending can help your organization use its data sources to the utmost.

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