We use cookies and other similar technologies (Cookies) to enhance your experience and to provide you with relevant content and ads. By using our website, you are agreeing to the use of Cookies. You can change your settings at any time. Cookie Policy.


Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 10

Originally published December 2, 2010

Part 1 of this series defined the EDW and summarized its data contents. Parts 2, 3, 4, 5 and 6 described and quantified 30 major benefit opportunities. Part 7 contained 10 business analysis examples for enabling benefits and summarized the benefit potentials as a percent of annual revenues. Part 8 continued with a description of 30 best practices to ensure success. Part 9 briefly described the governance process and provided a recommended organizational structure for a manufacturing EDW.This final installment in Messerli's series on enterprise data warehousing in manufacturing summarizes and concludes the series.

Conclusion

A successful EDW is not built overnight. It should be implemented in phases based on a comprehensive architecture and plan. Phases should focus on source systems and data content, rather than on requirements for a specific functional area. When extracting data from source system files or tables, extract all data with potential business intelligence relevance, rather than only what is needed for one functional area. This “touch it, take it” approach will minimize total EDW implementation cost because you won’t have to go back to the same sources later and change the extraction processes to meet requirements for another functional area.

Implementation priority should be driven by business requirements, but manufacturers often begin with customer, product, order, and invoice data from their fulfillment systems. These subject areas focus on customer relationships, product information, demand, and revenue, providing benefits to all functional areas. It is recommended that you capitalize on each EDW phase during development, then amortize investment for that phase over five years beginning upon implementation of the phase. This financial strategy aligns costs with savings and meets accepted accounting principles for strategic investments. And, it is easier to gain business unit acceptance because it won’t have a negative impact on operating income during development.

The “EDW” acronym is sometimes misused by vendors to describe architecture components or alternative approaches to business intelligence. BI tools are a component of the information delivery architecture, but the BI tool is not the EDW. Some vendors and system integrators advocate a “federated EDW” approach consisting of multiple data marts. Federated data marts require extensive data replication and do not deliver enterprise visibility, nor do they provide the comprehensive functionality and benefits described. The federated approach stems from technology or skill set constraints. People with transaction processing experience often attempt to craft a business intelligence solution based on their skill set, rather than the right technology. Technologies designed for transaction processing are different than the MPP (massively parallel processing) technology designed and optimized by Teradata for an EDW.

There are numerous best practices and organizational considerations that affect the cost and success of an EDW implementation. Proactive leadership to develop financial justification and gain broad executive support is an ideal starting point. Initiative and leadership for an EDW may come from IT or any credible executive with vision. Because the EDW impacts all functional areas and business units, executive committee or operating committee support is an important success factor. That support should include establishing a central organization responsible for the EDW, including data standardization and integration, shared processes and applications, and tool set support for all functional areas and business units.

Contact the author for assistance in the following areas:
  • communicating EDW vision, strategy and business benefits to executives
  • understanding best practices for achieving results
  • developing scope, road map, justification, architecture and organization
  • establishing appropriate processes, governance, roles and responsibilities

In reading this series, you have learned why an enterprise data warehouse is the best solution for business intelligence.  The EDW provides comprehensive and timely information meeting the requirements of all levels of executives, management, and all knowledge workers throughout the organization who use information to make decisions.  The EDW has been proven to enable a new and better way of managing a manufacturing enterprise. Many variables affect the specific opportunity for your company, but the impact will be substantial.  An EDW represents one of the best investments you can make and realistically represents reinventing business.

 
Links to each installment of this series follow:

Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 1

Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 2

Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 3

Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 4

Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 5

Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 6

Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 7

Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 8

Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 9

Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 10


  • Allen MesserliAllen Messerli
    Allen Messerli, President of Messerli Enterprise Systems LLC, specializes in enterprise data warehouse consulting, and has provided vision, direction and leadership for 400 major enterprises globally. Previously he had more than thirty years experience in a wide variety of positions at 3M, with an extensive record of successfully managing large-scale, innovative information technology solutions across supply chain, manufacturing, sales and marketing functions. 3M is a diverse global manufacturing company, with 40 business units operating in all countries and selling 500,000 products through most market channels. Al conceived, justified, architected, and directed implementation of 3M’s Global Enterprise Data Warehouse, which contributed more than $1 billion net business benefits with a very large ROI, and is now a global best practice enterprise data warehouse. He has extensive leadership experience in industry, national, and international logistics and electronic commerce organizations, and was a pioneer in electronic business and data warehousing, often speaking on these subjects around the world.

Recent articles by Allen Messerli

 

Comments

Want to post a comment? Login or become a member today!

Be the first to comment!