Posts Tagged ‘mdm’

New Data Management System Implementation Common Sense

Friday, January 8th, 2010

With the ever increasing emphasis on finding ways to reduce cost, one of the clear targets is IT and more specifically data management systems. On the surface it can seem like there is real fat to trim, and many times this is true. But it is easy to become lost in the details and eliminate or negate some of the potential savings. Some of these ideas may seem obvious but are often forgotten. The evidence is clear with missed timing and over budget issues seen.

If we’re talking about a large company then inevitably with this new system comes the monolith project with whole organizations of people and processes, projects and documentation. The compulsion is to be sure that everyone, everywhere who has any relationship to it has their input and their needs accounted for. Along the way, the cost of implementation and other peripheral indirect costs have likely negated a great deal of at least any short term savings. Not to mention the potential increase in continuous maintenance costs and loss in performance. These are a few things I’ve learned from experience and I welcome yours.

Always have a specific objective when planning for development or evaluating software to purchase that overrides all others. Start with something like a mission statement, “We need this new system for….”

Determine the Real Needs. Try to separate the “must haves” from the “nice to haves”. Bells and whistles are great but there needs to be a true benefit. Seek a balance between development time, software performance, hardware performance and user experience. I always try to put special emphasis on the user group which stands to benefit the most. Having many users who can do their job faster and more efficiently can add up to real savings versus the few users who have a special need which bogs down the project and performance.

Change is inevitable. If some requests for additional features come along, evaluate them against the mission objective. There is nothing wrong with listening and investigating ideas for project add-ons as long as the benefits outweigh the costs in time and money, but there needs to be a limit or you’ll never complete the project. Good ideas can always be implemented later if it makes sense then you’ll have the benefit of the research already done, but be quick with the research. Evaluate the impact for doing it now or waiting. Here are some good questions to start with: 1) How much more money?  2) Would this be faster/cheaper for programming to do it now versus waiting and doing a more complicated enhancement?  3) Is the impact to the users great enough to warrant it?

Know the roles. Good ideas can come from anyone. Every project must have a project champion who makes the final decisions (and live with them) and also eliminate roadblocks. You need a user advocate who has done the job and knows what it takes. Have programmers who possess both talent and vision, not just code crunchers, and listen to them.

Have good documentation, and “Good” is subject to interpretation. This is another area where the KISS principle is very often not utilized. If you have to hire ten people to sit in meetings just to maintain your documentation you’ve probably overcomplicated it and certainly increased your project cost. I try to start with these principles:

  1. Document the people on the project and their responsibilities. Let there be no question as to who does what.
  2. Everyone who has a job to do needs to understand what they need to do and have the documentation to reference.
  3. Keep the language simple. Focus on getting the point across. If it takes a rocket scientist to understand it you’ve failed.
  4. Of course, document the issues, decisions made, by whom etc. but be sensible. Document enough to cover for the “he said/she said” but content is most important. No bonus points for flash.
  5. Know who is supposed to have what done and when. Another obvious one here but I see too often where target dates are determined top down with little or no thought to cost or the tasks. Don’t let the tail wag the dog. Pushing hard to get the job done is fine but be realistic. Listen to the people who know before making bold predictions.

Data Quality: Classify and Describing

Wednesday, December 2nd, 2009

As the Master Data Management industry matures, the industry focus is not only on the development of software to collect product records but software to implement the data quality process solutions supporting data governance and provenance including record history, structure, completeness and accuracy to ensure our customers are able to make confident, informed and accurate business decisions based on data accuracy. The first step of implementing a data governance program is implementing a naming classification system.

I have had experience working with single business home-grown classification structures and third party developed structures for purchase, currently I have chosen an open and public classification structure provided by ECCMA (www.eccma.org). This is beneficial to the customers that I support ensuring that they will always have access to the classification structure sometime referred to as the schema used to classify their data.

Implementing a classification requires setting up Identification Guide (IG) to establish the template definition to technically describe the product or service with enough information to support engineering, maintenance or purchasing while recognizing the limitation of software short and long description required character lengths. The IG template supports and simplifies the required information request to the manufacturer and suppliers to verify all information by our analysts to standardize the description.

To create an IG, we search the ECCMA class list; fortunately many of the classes are established. As the IG is set up we will use the ECCMA established class name convention; this will ensure that every item will be setup with the same name and format, every ball bearing item submitted will be classified as a BEARING, BALL.

The next step is to set up the properties required to describe the BEARING, BALL and for each property designated the data type requirements such as numeric, text string or designated unit of measure. The property value requirements for a BEARING, BALL might include TYPE, BORE DIAMETER, OUTSIDE DIAMETER, WIDTH, DYNAMIC LOAD CAPACITY, STATIC LOAD CAPACITY, MATERIAL and so forth. Our analysts will verify the data to the original manufacturer sometimes using xml to exchange the product information referred to as “Cataloging at Source”, the information requests are standardized and remove much of the quality issues commonly found in a non-standardized data verification or description process.

The property value description build is controlled by the sequence number of each property Item data that will make it’s way into a length restricted description field we place the most important information in the begin of the auto generated description.

Setting up the Identification Guides requires upfront strategic planning and detailed work, as you can imagine that a classification schema can be up to 10,000 classes depending on the industry but it provides a multitude of benefits including standardized requirements, a road map for our analysts to facilitate the process, improved data management reporting / metrics and enhances language translation for the global organization.

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Implementation and Use of MRO Naming Standards

Friday, October 23rd, 2009

With all the discussion focusing on Master Data Management and Data Quality, I always come back to these questions: How is the data structured and how is the accuracy and content completeness measured? In our business of managing the coding and verification of items and spare part information needed to keep manufacturing plants running, a structured schema of naming conventions (class), descriptive attribute standardization (properties) and verification at the sources of manufacture (coding @ source) is “key” to quality and completeness measurement. We are managing the ECCMA eOTD for the Automotive Industry Content Standards Council (AICSC) focusing on MRO naming definitions which is the foundation to a spare part description, just as a table of contents is the foundation of a text book.

The first step is to develop the Identification Guide (IG) in order to baseline the properties needed to best describe the class. For example, let’s take the class of SCREW, SHOULDER and the properties TYPE, MATERIAL, FINISH, THREAD SIZE, DRIVE SIZE, SHOULDER DIAMETER, SHOULDER LENGTH, THREAD LENGTH, HEAD DIAMETER, HEAD HEIGHT, SHOULDER LENGTH TOLERANCE, MINIMUM TENSILE STRENGTH, CLASS, HARDNESS RATING and PACKAGE QUANTITY. The IG also provides the information needed for our analysts to acquire properties and our applications to sequence the properties within the short and long descriptions that are built:

SCREW,SHOULDER – | TYPE: HEX HEAD | MATERIAL: 18-8 STAINLESS STEEL | FINISH: PLAIN | HEAD STYLE: HEX | THREAD SIZE: 3/8-16 INCHES | DRIVE SIZE: 3/4 INCHES | SHOULDER DIAMETER: 1/2 INCHES | SHOULDER LENGTH: 2-1/2 INCHES | THREAD LENGTH: 3/4 INCHES | HEAD DIAMETER: 3/4 INCHES | HEAD HEIGHT: 1/4 INCHES | SHOULDER LENGTH TOLERANCE: ±0.005 INCHES | MINIMUM TENSILE STRENGTH: 80.000 POUND-FORCE PER SQUARE INCH | CLASS: 2A | HARDNESS RATING: B85 TO B95 ROCKWELL A | PACKAGE QUANTITY: 2

Each time an item is submitted for coding or processing the item is imported into a master database. Through intervention by our data analysts, the item navigates its way through a number of checkpoints including an auto-suggest to propose a class. The class and properties via the IG are the requirements our coding analysts use to verify the accuracy of the information submitted, to verify the completeness and to acquire the additional information needed to enhance and build an item or spare part description for our clients to base real business decisions.

The implementation of the eOTD is a two process scenario when working with our clients. First, the legacy data is mapped to the class, the item data is profiled, cleansed and enhanced to meet the requirements of eOTD IG, ensuring the client’s data quality goals are met. The updated item information needs to be applied to existing client item data. It is critical that all changes to data be tracked and logged. A properly planned and executed update to legacy ERP and CMMS systems should be initiated to incorporate the enhanced and corrected item information into the user facing systems. This is an extremely critical step as the downstream information flow will affect systems and uses such as inventory re-distribution, purchasing and contract management, engineering bills of materials and maintenance schedules. A thorough and complete mapping of data through the enterprise should be used to understand data flow across all business units. The mapping should include data entry points and data use points through all departments which set up all of the cost saving pay points as the data processing is streamlined.

The second process is an on-going data maintenance plan for new items that are introduced into the organization. This process should start at the introduction of item information into the system. All items and spare part information should be verified with the manufacturer and classified to the eOTD before setup or use in any system. The length of time the coding process requires is a critical element as the item or spare part information should be as complete as possible while at the same time be ready and waiting for the buyer to put the item on a contact or a maintenance employee to setup the tasking information in the CMMS for a piece of equipment. The only requirement for the employees who use the information after its initial entry into the system is to perform the actual requirement of their job and not to decipher a cryptic unstructured description.

If the items are pre-processed using the eOTD and the associated ISO standards, every item and spare part will be structured and standardized. The engineering, purchasing and maintenance departments will focus on the core of their day to day specialized responsibilities instead of searching for parts or dealing with trying to purchase items that a supplier does not recognize or have to acquire the missing information.

We all agree on some of the basic benefits both in process and cost such as reducing inventory with the identification of duplicate items, facilitation of inventory sharing and internal purchasing programs, reduced employee time searching for parts, common spare part usage strategies, reduced downtime in manufacturing equipment due to lack of information availability and ability to manage using a just in-time inventory model. The eOTD and its Identification guides are the building blocks and the roadmap to achieving structured and accurate data that can be reliably used to base real world decisions.

For more information on the eOTD please visit www.eccma.org.

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Data Quality: Software Innovation Please

Thursday, October 1st, 2009

I am all about the data, location management (to location and equipment), data quality, and methods to improve auto-processing, enhancing data, providing data reports and results that support our customer’s data requirements in their day to day activities.

Here is the million dollar question, this is one scenario: Over a million records in a year, legacy and new records submitted for processing from 2,500 different users and two different business processes (single submit and BOM extract). What technology would be required to intelligently automate the processing of these records to a Master Data Quality Standard?

Remember this is an on-going maintenance process, not a one time migration of non-cleansed data to a new ERP or maintenance system, nor am I referring to parsing the records into different fields of the new ERP system but ensuring that the records are verified, structured, properly attributed with full descriptions and additional information to support the business needs.

First, let’s look at the Wikipedia definition of Product Information Management (PIM) “PIM systems generally need to support multiple geographic locations, multi-lingual data, and maintenance and modification of product information within a centralized catalog to provide consistently accurate information to multiple channels in a cost-effective manner.”

Future PIM software purchasers, what evaluation methods are you using to ensure that your PIM software purchase will support the continuous update and flow of data for your entire enterprise system? Here are some items to take into consideration during your evaluation, these are all items that I ask about and would recommend that you request the answers in writing:

1. How is the change history of the data stored in the system and how easily can it be retrieved?
2. Has the performance of all modules of the software been tested and what is the base line?
3. Request references (at least three) for each module of the software.
4. What is the software product work flow and how is the data processing assigned to employees?
5. Ask to review the documentation and take the time to review; this should be a window into the complexity of the system.
6. Request the design process model and how the software company incorporates customer feedback?
7. What is the bug fix process? What is the quality system to implement a bug fix?
8. What is the software company’s philosophy on customizations at your cost?
9. How is language handled? Translations referenced to a master record?
10. If the software solution is multi module system, how are the master records referenced through
the entire solution?
11. What are the long term design strategies or road maps for each module of the software solution? Ask for the earlier road maps and the software release note to evaluate the how well the software company plans and implement updates to the systems.

And I can go on and on, the licensing; customizing and implementing software in your environment can be extremely costly and time consuming, does Caveat emptor “Let the buyer beware” work in the business world or is there a “Lemon Law” when purchasing software?

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Budget Time

Thursday, October 1st, 2009

My company’s fiscal year is based on the calendar year as many others are. So, customarily we start the budget planning process in October. It is a detailed process that all of my managers and business units participate in. We usually do a few iterations before it is finalized in mid December. Sound familiar? So here’s the question, after 2009, how do you plan for 2010? Everything we knew and could usually predict with some certainty in recent years went out the window in 2009. Where do you start to plan for the next year? Is it too early to plan for growth, if not, at what pace? What certainty can we count on when developing our plans? The simple fact is, for most of us, we don’t know enough at this stage in the recovery to forecast with certainty where our businesses will be, at least, through mid next year.

So what can be done to insure profitability, or least stability, until growth returns? Control and further reduce costs. Already been there, done that? You have cut staff, benefits, wages, renegotiated prices and terms with suppliers, cut services, slowed production, cut inventories, everything you can think of. Are you sure? How well do you manage your Enterprise wide Master Data Indirect Materials / Commodities spend? What? Everything you buy that supports your facilities and the build of your products. Most large manufactures manage direct material precisely but don’t have an organized approach to their full advantage throughout the Enterprise to strategically manage indirect materials. A solution, fully implemented, provides a number of benefits:

1. “Cleansed” data, eliminating duplication of the same item coded to several different part numbers.

2. Consistent pricing for each and every part / component verified to the OEM level with lead time and warranty information. Minimizing your need to buy spare parts / commodities from distributors or your build sources.

3. Enterprise-wide material management to the department level in every Manufacturing Operation.

4. A reuse or repurposing of excess inventory in Manufacturing Engineering.

5. Able to search inventory with standardized part naming conventions and in multiple languages.

Bottom-line, an aggressive Enterprise wide well executed strategy can and will save your company significant dollars in the first 12 months of implementation. That’s 2010 folks….

The Electronic Commerce Code Management Association (ECCMA) has approved the formation of the Automotive Industry Content Standardization Council (AI-CSC)

Friday, September 11th, 2009

Bethlehem, PA (PRWEB) September 10, 2009 — The Electronic Commerce Code Management Association (ECCMA) has approved the formation of the Automotive Industry Content Standardization Council (AI-CSC) as the fifth council with direct editorial access to the ECCMA Open Technical dictionary (eOTD). Read More…

Life Cycle Data Management Strategy

Thursday, September 3rd, 2009

Life Cycle Management implies a single “cradle to grave” plan that integrates production support planning, acquisition and sustainment strategies. Think about the importance of data flow and the criticality of accurate data throughout the complete life cycle of a piece of equipment: design, build, install, spare part acquisition, inventory management, maintenance, spare parts sharing and finally, asset disposal. From a data perspective, remember the old computer motto: “Garbage In, Garbage Out”.

What is your Life Cycle Data Management Strategy?

1) Drawing Libraries – The items in the library need to be cleansed and profiled to a classification schema. The schema requires standard naming conventions and technical descriptions. The schema can be designed within your company, priority purchased from another vendor or you can opt for using an open classification dictionary for public use such as the ECCMA eOTD.

2) Common Component Listing – provides a listing of preferred components that support the inventory management strategies for your organization. All equipment designers and builder are required to use the common components identified. Note: common components are set up in the drawing libraries.

3) Spare Part Acquisition – Place the components on purchasing contacts at the beginning of design, this will facilitate the ease of spare parts planning and purchasing. An item on contract provides purchasing the data needed to run analytical algorithms in order to better negotiate pricing organization wide. If the item is set up accurately to a standardized classification dictionary with technical descriptions only one time the whole organization can realize the benefits of the Life Cycle Data Management Strategy.

4) Inventory – supports optimal inventory management by promoting the ability to plan stocking levels and strategies with nearby facilities. Think about the implementation of spare parts sharing or an internal purchase first program. The most important requirement is the standardization or normalization of the data; the part needs to be classified only one-way and should be shown in every system the same way.

5) Maintenance –The use of standardized components coupled with a data management strategy allows the organization to streamline the number of different components used to serve the same function on different equipment. Also reducing the number of parts in inventory and maintenance management tasks.

Life Cycle Data Management Plans starts with component standardization and cleansing the data in your equipment drawing libraries and all downward systems including maintenance. This strategy avoids duplicate inventory items and at the same time promotes an internal purchase philosophy that puts a priority on inventory sharing before issuing supplier purchase orders. Standardizing inventory with information elements such as predefined stocking levels, identification of critical inventory, functionally equivalent item identification and purchasing analytics as well as enhanced vendor management are all necessary steps for a manufacturing business to remain competitive in today’s world of lean low overhead manufacturing.

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The Spare Parts World and What It Could Be

Thursday, August 20th, 2009

The conundrum of spare parts management at a high level is perceived and often approached as a process that should be simple. Looking at it from the perspective of the many different entities that form the supply chain and are required to work together symbiotically—component manufacturers, Tier One and Tier Two suppliers, and OEM manufacturers—the logistical expertise needed to coordinate the information flow is anything but simple.

To realize cost savings from new process efficiencies, these separate legal entities need to integrate the information flow and internal groups within each entity such as purchasing, manufacturing engineering, plant maintenance, facilities management, warehousing, commodity management, and asset recovery. Each area must share the mission-critical master data related to the spare parts. Truly integrating the information flow within the conceivably 50-plus business units that indirectly work together across the automotive supply chain to deliver just one item to an OEM sounds literally impossible and cost prohibitive. However, your opinion may change when you read the next couple sentences.

It is estimated that process failures and bad information cost business $1.5 trillion or more in the U.S. alone (Larry English, 2007). A study of large companies, a majority of which have revenues of more than $1 billion, found that 31 percent believe that their costs for incorrect data are $1 million or more per year (Dave Waddington, 2008). The most common element needed by (and from) all involved in the supply chain of the spare parts that keep our lines running is data quality and content as information is transmitted from one organization to another.

Figure 1. Typical Supply Chain Spare Part Data and Information Flow

There is a lot of activity and even more information available around Master Data Management (MDM). MDM and data quality initiatives have become an industry trend these days. To champion a successful MDM effort, formal strategies regarding data standardization in content and structure, as well as import, storage, display, and transmission from your enterprise resource planning (ERP) systems to industry partners are mandatory.

Every supplier, OEM, and manufacturer is using a unique set of data standards to attempt to achieve true “quality” for their data. But how powerful, efficient and beneficial to the automotive industry can the use of silo developed standards be? If all partners were using the same data standards, naming conventions, and requirements to describe spare parts, we can greatly streamline the process needed to exchange the information and at the same time reduce the number of physical and business process failures resulting from the low-quality descriptions contained in our legacy systems, and in most cases, new state of the art ERP systems.

The elements required to achieve a symbiotic information flow for the automotive industry are the same:

A common understanding of what data is needed for a particular class or type of item;
A common method to store the data;
A common method to display the data; and
A common method to transmit the data to those entities that do business together.
The answer is to simplify and standardize the methods used for the exchange of structured, accurate, and efficient data-sharing in an automated fashion, rather than manually sharing as it has traditionally been done. The Electronic Commerce Code Management Association (ECCMA) and DATAForge LLC have formed the Automotive Industry Content Standardization Council (AICSC). The purpose of the council is to facilitate the addition of automotive industry specific terminology to the electronic Open Technical Dictionary (eOTD), create identification guides for quality descriptions, or data requirement statements for individuals, organizations, locations, goods and services.

This also helps develop an automotive supply chain specific spend analysis classification. The dictionary being maintained by ECCMA and the AICSC is ISO standard and public domain; any organization can benefit from its use. ECCMA and the AICSC work with automotive-centric businesses to standardize the way data and information is stored, viewed, and exchanged.

Figure 2. Quality Description:

ECCMA has brought together thousands of experts from around the world and provides them a means of working together in the fair, open, and extremely fast environment of the Internet to build and maintain the global, open-standard dictionaries that are used to unambiguously label information. ISO 22745 spare parts data is capable of being used in any ISO 8000 computer application (neutral exchange), is easily translated, and must stand the test of time (long-term data retention) by using a public domain concept identifier.

Jacqueline Roberts is vice president of DATAForge LLC. For more information about ECCMA, visit the ECCMA Web site.

View web publication:

 http://aiag.informz.net/admin31/content/template.asp?ps=4683&sid=4683&brandid=4002&ptid=406&uid=0&mi=390242

The Spare Parts World

Tuesday, August 11th, 2009

Spare parts management at a high level is perceived and often approached as a process that should be simple. Looking at it from perspectives of the many different entities that form the supply chain and are required to work together – component manufacturers, tier 1 suppliers, tier 2 suppliers, and manufacturers, the logistical expertise needed to coordinate the information flow is anything but simple.

To realize cost saving from new process efficiencies, these separate legal entities need to “integrate” the information flow to manufacturers and within each manufacturer to internal groups such as purchasing, manufacturing engineering, plant maintenance, facilities management, warehousing, commodity management, and asset sharing / recovery need to share the mission critical master data related to the spare parts. A truly integrated information flow could conceivably touch a number of business units that indirectly work together across the supply chain to deliver just one item to a manufacturer. The most common element needed by (and from) all involved in the supply chain of the spare parts that keeps the equipment running is data standardization, data quality and an electronic method of transmittal. A study of large companies, a majority of which have revenues of more than $1 billion, found that 31% believe that their costs for incorrect data are $1 million or more per year.1

Data standardization and data cleansing cost should be covered with cost saving initiatives. In addition to the initial data cleanup; strong data governance processes should be implemented for on-going data setups.

1Dave Waddington, “Growing Adoption of Master Data Management by Business?” citing an Information Difference survey of 112 companies, 65% of which had revenues of more than $1 billion, IT-Director.com, IT Analysis Communications Ltd., June 23, 2008.

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DATAForge LLC scheduled to present Maximo best practices at Purdue University

Wednesday, July 29th, 2009

DATAForge LLC is scheduled to present our best practice “Electronic Structured Spare Parts Data Population of Maximo” at the Facilities Management Maximo Users Group (FMMUG) http://www.fmmug.org/ hosted by Purdue University on October 11th and 12th. Setting up spare parts and tasking in Maximo starts at the beginning of equipment design with the bill of materials parts list, the equipment asset number and plant location. Our best practice, provides a complete and automatic electronic transfer of the Bill of Material for a piece of equipment that mashes up to an equipment listing with location. The data is imported with the item records referenced to a category key of perishable spare / non spare. The perishable spares are imported to a data verification tool where analysts process and cleanse the spare part records. Once the equipment with plant location and all associated spare parts are complete we use a simple to use interface for transfer of data to Maximo, thus giving users the power to move thousands of records at a time creating Equipment, Items, Companies, Spare Parts, etc. with all of the correct fields related, to take advantage of the Maximo hyper-linking ability. The results are a fully accurate data enabled Maximo without manual part verification or data entry of equipment, items, spare parts or companies. The documented time savings for one program is two skilled trade persons for two years. Look for our best practice case study in October.