Tue, 08/04/2009 - 14:35

SEMA News - August 2009

By Steve Campbell
Illustration Colby Martin

 

All Segments of the Industry Have an Interest in Employing Common Standards

SEMA News-August 2009-Good Data 01Just because a company has a highly detailed Excel spreadsheet that provides two dozen fields jammed with product data doesn’t mean that it has good data. Data is simply information. Good data is the appropriate information provided in correct formats.

As it pertains to automotive specialty-equipment businesses, data is the size, weight, quantity, price and other descriptive factors that tell a distributor, jobber or dealer about a manufacturer’s product. Ultimately, it’s the information that allows the distribution chain to pass the right product at the proper price from the maker to the end user. But as information is computerized and exchanged electronically—transformed from a written description at one end into a numeric code that is read by a machine and then reformed back into a written description at the other end—data must be strictly standardized in order to be valid. And it’s very easy for one company’s written description to be lost in translation as it moves to another company’s computer.

Bob Moore, president of Bob Moore+Partners and a member of SEMA’s Business Technology Committee, offered an excellent example: “I loaded a song by the Doobie Brothers onto my iPod,” he said. “But when I wanted to listen to it, I couldn’t find it. After scrolling through almost my entire catalog of artists, I discovered that, rather than indexing the group under ‘D’ for Doobie, my iPod had indexed it under ‘T’ for The Doobie Brothers.”

One of the most popular automotive brands in the world is fodder for another example. If Manufacturer A enters a Chevrolet part as being for a Chevy but its distributors’ computer recognizes only the automaker’s full name, the data transfer will be confused. Then throw in the jobber’s misinterpretation when its computer is looking for Chev, because that’s what the data-entry person learned to call the brand growing up. The result is a flurry of phone calls and delays—often outright missed sales—because of a basic data error. And we haven’t even mentioned the disorder wreaked by Chevy/GMC.

Human beings have the undeniable advantage of being able to interpret words, signals, signs and even subtle gestures. We immediately and automatically understand that Chevrolet, Chevy, Chev and even Chevie stand for the same company. We know that a pack is a unit that contains more than one individual item, though we might also call it a package or a box or even a crate. But a computer sees each of those terms as a distinctly different item. Any missing or incorrectly added bit of information stymies a computer’s ability to find or correctly categorize data. That’s why industry-wide data standardization has become so important.

The Product Information Exchange Standard (PIES) was developed to create universally accepted formats for key product-data items, including part number, part type, weight, size, pricing and more. As the electronic transfer of product information has proliferated and become the most widespread means by which commerce is conducted, all companies in all segments of the industry have a vested interest in employing common data standards.

Some companies—especially those that deal with a large assortment of parts or those small enough not to have a dedicated data manager—may be intimidated by the idea of having to standardize product data. And, to be realistic, it is a process that takes some time and effort. But so does picking up the phone for one transaction after another to sort out why an order was incomplete or the wrong part was shipped or the wrong quantity was received. Once standardization is complete, those problems don’t occur, and we can get on with the business of providing the parts people want to buy.

Learn more about standards and find resources.

 

A Glossary of Terms

A Quick Primer on Speaking Geek

By Gigi Ho


SEMA News-August 2009-Good Data 02AAIA Legacy: The original Automotive Aftermarket Industry Association electronic catalog standard for vehicle year, make, model and engine. Files are delivered in a flat file format.

ACES (AAIA Catalog Enhanced Standard): The current electronic cataloging standard, replacing Legacy, comprised of vehicle year, make, model, engine and vehicle attributes in a relational database. Files are delivered in an XML format.

PIES (Product Information Exchange Standards): Standardized fields of product information such as part number, descriptions, pricing, dimensions, weight, packaging, etc. Files are delivered in an XML format.

Delimited Text File: A flat file format that is an array of data separated by any character. The most common delimiters are tabs, commas and vertical bars (AKA “pipe”).

XML (Extensible Mark-Up Language): Tags that define and validate data and facilitate transmission and interpretation of data between two or more companies’ systems, the supplier of data and the receiver(s) of data.

Relational Database: A database whose structure is made up of numerous separate but linked tables of information. One of the advantages of a relational database is that duplication of entries is reduced or even eliminated. In a parts database, for example, there would be a separate table for part types/categories. For each part summary, a link is made to the applicable part type/category in the part type table. As a result the word “turbocharger” would actually be entered only once in the database but would appear linked in all applicable records.

Data Mapping/Cataloging: The creation of a full record of information about a part, cross-referenced to other records and files. Catalogers often prepare and keep up the information about the parts. Some of the information recorded includes the brand name, part descriptions, dimensions, photos, fitment on a vehicle, etc.

Learn more technology terms and jargon.

Tue, 08/04/2009 - 14:35

SEMA News - August 2009

By Steve Campbell
Illustration Colby Martin

 

All Segments of the Industry Have an Interest in Employing Common Standards

SEMA News-August 2009-Good Data 01Just because a company has a highly detailed Excel spreadsheet that provides two dozen fields jammed with product data doesn’t mean that it has good data. Data is simply information. Good data is the appropriate information provided in correct formats.

As it pertains to automotive specialty-equipment businesses, data is the size, weight, quantity, price and other descriptive factors that tell a distributor, jobber or dealer about a manufacturer’s product. Ultimately, it’s the information that allows the distribution chain to pass the right product at the proper price from the maker to the end user. But as information is computerized and exchanged electronically—transformed from a written description at one end into a numeric code that is read by a machine and then reformed back into a written description at the other end—data must be strictly standardized in order to be valid. And it’s very easy for one company’s written description to be lost in translation as it moves to another company’s computer.

Bob Moore, president of Bob Moore+Partners and a member of SEMA’s Business Technology Committee, offered an excellent example: “I loaded a song by the Doobie Brothers onto my iPod,” he said. “But when I wanted to listen to it, I couldn’t find it. After scrolling through almost my entire catalog of artists, I discovered that, rather than indexing the group under ‘D’ for Doobie, my iPod had indexed it under ‘T’ for The Doobie Brothers.”

One of the most popular automotive brands in the world is fodder for another example. If Manufacturer A enters a Chevrolet part as being for a Chevy but its distributors’ computer recognizes only the automaker’s full name, the data transfer will be confused. Then throw in the jobber’s misinterpretation when its computer is looking for Chev, because that’s what the data-entry person learned to call the brand growing up. The result is a flurry of phone calls and delays—often outright missed sales—because of a basic data error. And we haven’t even mentioned the disorder wreaked by Chevy/GMC.

Human beings have the undeniable advantage of being able to interpret words, signals, signs and even subtle gestures. We immediately and automatically understand that Chevrolet, Chevy, Chev and even Chevie stand for the same company. We know that a pack is a unit that contains more than one individual item, though we might also call it a package or a box or even a crate. But a computer sees each of those terms as a distinctly different item. Any missing or incorrectly added bit of information stymies a computer’s ability to find or correctly categorize data. That’s why industry-wide data standardization has become so important.

The Product Information Exchange Standard (PIES) was developed to create universally accepted formats for key product-data items, including part number, part type, weight, size, pricing and more. As the electronic transfer of product information has proliferated and become the most widespread means by which commerce is conducted, all companies in all segments of the industry have a vested interest in employing common data standards.

Some companies—especially those that deal with a large assortment of parts or those small enough not to have a dedicated data manager—may be intimidated by the idea of having to standardize product data. And, to be realistic, it is a process that takes some time and effort. But so does picking up the phone for one transaction after another to sort out why an order was incomplete or the wrong part was shipped or the wrong quantity was received. Once standardization is complete, those problems don’t occur, and we can get on with the business of providing the parts people want to buy.

Learn more about standards and find resources.

 

A Glossary of Terms

A Quick Primer on Speaking Geek

By Gigi Ho


SEMA News-August 2009-Good Data 02AAIA Legacy: The original Automotive Aftermarket Industry Association electronic catalog standard for vehicle year, make, model and engine. Files are delivered in a flat file format.

ACES (AAIA Catalog Enhanced Standard): The current electronic cataloging standard, replacing Legacy, comprised of vehicle year, make, model, engine and vehicle attributes in a relational database. Files are delivered in an XML format.

PIES (Product Information Exchange Standards): Standardized fields of product information such as part number, descriptions, pricing, dimensions, weight, packaging, etc. Files are delivered in an XML format.

Delimited Text File: A flat file format that is an array of data separated by any character. The most common delimiters are tabs, commas and vertical bars (AKA “pipe”).

XML (Extensible Mark-Up Language): Tags that define and validate data and facilitate transmission and interpretation of data between two or more companies’ systems, the supplier of data and the receiver(s) of data.

Relational Database: A database whose structure is made up of numerous separate but linked tables of information. One of the advantages of a relational database is that duplication of entries is reduced or even eliminated. In a parts database, for example, there would be a separate table for part types/categories. For each part summary, a link is made to the applicable part type/category in the part type table. As a result the word “turbocharger” would actually be entered only once in the database but would appear linked in all applicable records.

Data Mapping/Cataloging: The creation of a full record of information about a part, cross-referenced to other records and files. Catalogers often prepare and keep up the information about the parts. Some of the information recorded includes the brand name, part descriptions, dimensions, photos, fitment on a vehicle, etc.

Learn more technology terms and jargon.

Tue, 08/04/2009 - 14:35

SEMA News - August 2009

By Drew Hardin
Courtesy Source Interlink Media Archives

 

The Don

SEMA NEWS-AUGUST 2009-SEMA HERITAGEThe big man in the Milodon T-shirt is none other than Don Alderson, Milodon’s cofounder (and the “don” in Milodon). Though this archive find came with no information, the location is obviously Bonneville, and the man in the Autolite shirt and what looks to be a ’66 or ’67 GTO in the distance leads us to believe that the shot was taken in 1967. That year, Autolite asked Alderson to build a land-speed-racing Ford 427 SOHC engine for the Herda-Knapp-Milodon streamliner as a tribute to Henry Ford’s speed records set 40 years before on Daytona Beach. The ’liner was already a proven record-setter, and the 357-mph mark it posted with the Cammer on board would stand for nearly 30 years.

Though Milodon was one of SEMA’s original founding companies, Alderson, with his friend Milo Franklin, started the business in 1957 as a maker of aircraft and missile components. Alderson was an active racer on the salt, the dry lakes and at the drags, and he used the Milodon shop to build components for his own race cars. Fellow racers learned about, and asked for, Alderson’s custom-made speed equipment, and the volume of racing parts coming out of the Milodon facility soon transformed its focus from aero to automotive.

Tue, 08/04/2009 - 14:35

SEMA News - August 2009

By Drew Hardin
Courtesy Source Interlink Media Archives

 

The Don

SEMA NEWS-AUGUST 2009-SEMA HERITAGEThe big man in the Milodon T-shirt is none other than Don Alderson, Milodon’s cofounder (and the “don” in Milodon). Though this archive find came with no information, the location is obviously Bonneville, and the man in the Autolite shirt and what looks to be a ’66 or ’67 GTO in the distance leads us to believe that the shot was taken in 1967. That year, Autolite asked Alderson to build a land-speed-racing Ford 427 SOHC engine for the Herda-Knapp-Milodon streamliner as a tribute to Henry Ford’s speed records set 40 years before on Daytona Beach. The ’liner was already a proven record-setter, and the 357-mph mark it posted with the Cammer on board would stand for nearly 30 years.

Though Milodon was one of SEMA’s original founding companies, Alderson, with his friend Milo Franklin, started the business in 1957 as a maker of aircraft and missile components. Alderson was an active racer on the salt, the dry lakes and at the drags, and he used the Milodon shop to build components for his own race cars. Fellow racers learned about, and asked for, Alderson’s custom-made speed equipment, and the volume of racing parts coming out of the Milodon facility soon transformed its focus from aero to automotive.

Tue, 08/04/2009 - 14:35

SEMA News - August 2009

By Drew Hardin
Courtesy Source Interlink Media Archives

 

The Don

SEMA NEWS-AUGUST 2009-SEMA HERITAGEThe big man in the Milodon T-shirt is none other than Don Alderson, Milodon’s cofounder (and the “don” in Milodon). Though this archive find came with no information, the location is obviously Bonneville, and the man in the Autolite shirt and what looks to be a ’66 or ’67 GTO in the distance leads us to believe that the shot was taken in 1967. That year, Autolite asked Alderson to build a land-speed-racing Ford 427 SOHC engine for the Herda-Knapp-Milodon streamliner as a tribute to Henry Ford’s speed records set 40 years before on Daytona Beach. The ’liner was already a proven record-setter, and the 357-mph mark it posted with the Cammer on board would stand for nearly 30 years.

Though Milodon was one of SEMA’s original founding companies, Alderson, with his friend Milo Franklin, started the business in 1957 as a maker of aircraft and missile components. Alderson was an active racer on the salt, the dry lakes and at the drags, and he used the Milodon shop to build components for his own race cars. Fellow racers learned about, and asked for, Alderson’s custom-made speed equipment, and the volume of racing parts coming out of the Milodon facility soon transformed its focus from aero to automotive.

Tue, 08/04/2009 - 14:35

SEMA NEWS - August 2009

By John Zinn
Illustration Colby Martin

 

Get Your Thinking And Strategy Headed Toward Efficiency And Accuracy

  SEMA News-August 2009-Data 01
  Make sure that you always spell the same information the same every time you use it. Example: Chevy and Chevrolet. We all know each of these are the same, but the computer sees two distinct makes.

The list contained below should be used as a very basic litmus test as to the usefulness of your electronic product information. Correcting or addressing all of these issues does not equal standards compliance, but it will serve to get you headed in the right direction and redirect your overall thinking and strategy.

It will also increase the efficiency and accuracy with which your product information is made available to the consumer. If you haven’t done so, please take the time to read the other articles in this issue relating to product data/product information to better understand how absolutely critical it is that you take a good, hard, honest look at what you are currently calling your “product data.”

1. PDFs Are Not Data Files: PDFs, Word documents, read-only files of any type, heavily formatted Excel files (more on this in rule number two) and any other file format that is not “relational” should never be used for electronic product information distribution. The single most universally accepted and flexible format is .CSV (comma separated values). You should always have a copy of your product information in .CSV for immediate distribution.

2. Product Data Isn’t Pretty: This relates primarily to Excel files and is one of the most common errors made in data/product information formatting and distribution. The tendency to want to “dress up” the file with colors, fonts, graphics and otherwise mimic the appearance of a catalog page renders the information contained within that file virtually useless to anybody wishing to make electronic use of the same. Good product data isn’t pretty; don’t try to force it to be so. It’s okay to have a separate file for human consumption that is dressed up, but don’t ever send that to somebody asking for electronic product information.

3. Computers Aren’t Auto Enthusiasts: Never combine information in a single data field, even if you and everybody else in the industry know exactly what it means. Electronically, product information is stored, manipulated and displayed by leveraging simple relationships between data points. If you have any data fields that look like this…

SEMA News-August 2009-Data 02

…you are guilty of this critical error. A computer cannot possibly know which model belongs to which make. Each of these “relationships” must be firm and one to one. One make to one model. Period. Repeat this for the same part number as many times as it takes to keep a one-to-one relationship between all data points.

4. Spelling Counts: Make sure that you always spell the same information the same every time you use it. Example: Chevy and Chevrolet. We all know each of these are the same, but the computer sees two distinct makes. If this were imported into a website as is, for example, the vehicle selection drop-down menu would offer you both choices—Chevy and Chevrolet. Which do you choose? And each selection will display only the products listed with that spelling. So the customer or counter/phone salesmen won’t see everything that’s available regardless of his selection.

5. Asterisks, Footnotes and Caveats: You make a part that fits an F-150 but not the Harley-Davidson model. So you do the very human thing and list that part number thusly: “Make: Ford, Model: F-150*.” Then, someplace else in the file, you say: “*Does not fit Harley-Davidson model.” As with the spelling in rule number four and the relationships in rule number three, the computer has no idea what you mean. It only sees a new model—F-150*—and some extraneous data elsewhere that isn’t related to anything (the footnote). This logical error will either crash the program or simply drop the information as unusable/unrelated. All such qualifications, footnotes, etc., should exist in their own data field directly related to the part number that they reference.

Learn more about standards and find resources.


John Zinn is the senior vice president of Advanced Digital Strategies and the chairman of the communications subcommittee of the SEMA Business Technology Committee . He may be contacted via e-mail at jzinn@digstrat.com or via telephone at 949/528-6522.

Tue, 08/04/2009 - 14:35

SEMA NEWS - August 2009

By John Zinn
Illustration Colby Martin

 

Get Your Thinking And Strategy Headed Toward Efficiency And Accuracy

  SEMA News-August 2009-Data 01
  Make sure that you always spell the same information the same every time you use it. Example: Chevy and Chevrolet. We all know each of these are the same, but the computer sees two distinct makes.

The list contained below should be used as a very basic litmus test as to the usefulness of your electronic product information. Correcting or addressing all of these issues does not equal standards compliance, but it will serve to get you headed in the right direction and redirect your overall thinking and strategy.

It will also increase the efficiency and accuracy with which your product information is made available to the consumer. If you haven’t done so, please take the time to read the other articles in this issue relating to product data/product information to better understand how absolutely critical it is that you take a good, hard, honest look at what you are currently calling your “product data.”

1. PDFs Are Not Data Files: PDFs, Word documents, read-only files of any type, heavily formatted Excel files (more on this in rule number two) and any other file format that is not “relational” should never be used for electronic product information distribution. The single most universally accepted and flexible format is .CSV (comma separated values). You should always have a copy of your product information in .CSV for immediate distribution.

2. Product Data Isn’t Pretty: This relates primarily to Excel files and is one of the most common errors made in data/product information formatting and distribution. The tendency to want to “dress up” the file with colors, fonts, graphics and otherwise mimic the appearance of a catalog page renders the information contained within that file virtually useless to anybody wishing to make electronic use of the same. Good product data isn’t pretty; don’t try to force it to be so. It’s okay to have a separate file for human consumption that is dressed up, but don’t ever send that to somebody asking for electronic product information.

3. Computers Aren’t Auto Enthusiasts: Never combine information in a single data field, even if you and everybody else in the industry know exactly what it means. Electronically, product information is stored, manipulated and displayed by leveraging simple relationships between data points. If you have any data fields that look like this…

SEMA News-August 2009-Data 02

…you are guilty of this critical error. A computer cannot possibly know which model belongs to which make. Each of these “relationships” must be firm and one to one. One make to one model. Period. Repeat this for the same part number as many times as it takes to keep a one-to-one relationship between all data points.

4. Spelling Counts: Make sure that you always spell the same information the same every time you use it. Example: Chevy and Chevrolet. We all know each of these are the same, but the computer sees two distinct makes. If this were imported into a website as is, for example, the vehicle selection drop-down menu would offer you both choices—Chevy and Chevrolet. Which do you choose? And each selection will display only the products listed with that spelling. So the customer or counter/phone salesmen won’t see everything that’s available regardless of his selection.

5. Asterisks, Footnotes and Caveats: You make a part that fits an F-150 but not the Harley-Davidson model. So you do the very human thing and list that part number thusly: “Make: Ford, Model: F-150*.” Then, someplace else in the file, you say: “*Does not fit Harley-Davidson model.” As with the spelling in rule number four and the relationships in rule number three, the computer has no idea what you mean. It only sees a new model—F-150*—and some extraneous data elsewhere that isn’t related to anything (the footnote). This logical error will either crash the program or simply drop the information as unusable/unrelated. All such qualifications, footnotes, etc., should exist in their own data field directly related to the part number that they reference.

Learn more about standards and find resources.


John Zinn is the senior vice president of Advanced Digital Strategies and the chairman of the communications subcommittee of the SEMA Business Technology Committee . He may be contacted via e-mail at jzinn@digstrat.com or via telephone at 949/528-6522.

Tue, 08/04/2009 - 14:35

SEMA NEWS - August 2009

By John Zinn
Illustration Colby Martin

 

Get Your Thinking And Strategy Headed Toward Efficiency And Accuracy

  SEMA News-August 2009-Data 01
  Make sure that you always spell the same information the same every time you use it. Example: Chevy and Chevrolet. We all know each of these are the same, but the computer sees two distinct makes.

The list contained below should be used as a very basic litmus test as to the usefulness of your electronic product information. Correcting or addressing all of these issues does not equal standards compliance, but it will serve to get you headed in the right direction and redirect your overall thinking and strategy.

It will also increase the efficiency and accuracy with which your product information is made available to the consumer. If you haven’t done so, please take the time to read the other articles in this issue relating to product data/product information to better understand how absolutely critical it is that you take a good, hard, honest look at what you are currently calling your “product data.”

1. PDFs Are Not Data Files: PDFs, Word documents, read-only files of any type, heavily formatted Excel files (more on this in rule number two) and any other file format that is not “relational” should never be used for electronic product information distribution. The single most universally accepted and flexible format is .CSV (comma separated values). You should always have a copy of your product information in .CSV for immediate distribution.

2. Product Data Isn’t Pretty: This relates primarily to Excel files and is one of the most common errors made in data/product information formatting and distribution. The tendency to want to “dress up” the file with colors, fonts, graphics and otherwise mimic the appearance of a catalog page renders the information contained within that file virtually useless to anybody wishing to make electronic use of the same. Good product data isn’t pretty; don’t try to force it to be so. It’s okay to have a separate file for human consumption that is dressed up, but don’t ever send that to somebody asking for electronic product information.

3. Computers Aren’t Auto Enthusiasts: Never combine information in a single data field, even if you and everybody else in the industry know exactly what it means. Electronically, product information is stored, manipulated and displayed by leveraging simple relationships between data points. If you have any data fields that look like this…

SEMA News-August 2009-Data 02

…you are guilty of this critical error. A computer cannot possibly know which model belongs to which make. Each of these “relationships” must be firm and one to one. One make to one model. Period. Repeat this for the same part number as many times as it takes to keep a one-to-one relationship between all data points.

4. Spelling Counts: Make sure that you always spell the same information the same every time you use it. Example: Chevy and Chevrolet. We all know each of these are the same, but the computer sees two distinct makes. If this were imported into a website as is, for example, the vehicle selection drop-down menu would offer you both choices—Chevy and Chevrolet. Which do you choose? And each selection will display only the products listed with that spelling. So the customer or counter/phone salesmen won’t see everything that’s available regardless of his selection.

5. Asterisks, Footnotes and Caveats: You make a part that fits an F-150 but not the Harley-Davidson model. So you do the very human thing and list that part number thusly: “Make: Ford, Model: F-150*.” Then, someplace else in the file, you say: “*Does not fit Harley-Davidson model.” As with the spelling in rule number four and the relationships in rule number three, the computer has no idea what you mean. It only sees a new model—F-150*—and some extraneous data elsewhere that isn’t related to anything (the footnote). This logical error will either crash the program or simply drop the information as unusable/unrelated. All such qualifications, footnotes, etc., should exist in their own data field directly related to the part number that they reference.

Learn more about standards and find resources.


John Zinn is the senior vice president of Advanced Digital Strategies and the chairman of the communications subcommittee of the SEMA Business Technology Committee . He may be contacted via e-mail at jzinn@digstrat.com or via telephone at 949/528-6522.

Tue, 08/04/2009 - 14:35

SEMA NEWS - August 2009

By John Zinn
Illustration Colby Martin

 

Get Your Thinking And Strategy Headed Toward Efficiency And Accuracy

  SEMA News-August 2009-Data 01
  Make sure that you always spell the same information the same every time you use it. Example: Chevy and Chevrolet. We all know each of these are the same, but the computer sees two distinct makes.

The list contained below should be used as a very basic litmus test as to the usefulness of your electronic product information. Correcting or addressing all of these issues does not equal standards compliance, but it will serve to get you headed in the right direction and redirect your overall thinking and strategy.

It will also increase the efficiency and accuracy with which your product information is made available to the consumer. If you haven’t done so, please take the time to read the other articles in this issue relating to product data/product information to better understand how absolutely critical it is that you take a good, hard, honest look at what you are currently calling your “product data.”

1. PDFs Are Not Data Files: PDFs, Word documents, read-only files of any type, heavily formatted Excel files (more on this in rule number two) and any other file format that is not “relational” should never be used for electronic product information distribution. The single most universally accepted and flexible format is .CSV (comma separated values). You should always have a copy of your product information in .CSV for immediate distribution.

2. Product Data Isn’t Pretty: This relates primarily to Excel files and is one of the most common errors made in data/product information formatting and distribution. The tendency to want to “dress up” the file with colors, fonts, graphics and otherwise mimic the appearance of a catalog page renders the information contained within that file virtually useless to anybody wishing to make electronic use of the same. Good product data isn’t pretty; don’t try to force it to be so. It’s okay to have a separate file for human consumption that is dressed up, but don’t ever send that to somebody asking for electronic product information.

3. Computers Aren’t Auto Enthusiasts: Never combine information in a single data field, even if you and everybody else in the industry know exactly what it means. Electronically, product information is stored, manipulated and displayed by leveraging simple relationships between data points. If you have any data fields that look like this…

SEMA News-August 2009-Data 02

…you are guilty of this critical error. A computer cannot possibly know which model belongs to which make. Each of these “relationships” must be firm and one to one. One make to one model. Period. Repeat this for the same part number as many times as it takes to keep a one-to-one relationship between all data points.

4. Spelling Counts: Make sure that you always spell the same information the same every time you use it. Example: Chevy and Chevrolet. We all know each of these are the same, but the computer sees two distinct makes. If this were imported into a website as is, for example, the vehicle selection drop-down menu would offer you both choices—Chevy and Chevrolet. Which do you choose? And each selection will display only the products listed with that spelling. So the customer or counter/phone salesmen won’t see everything that’s available regardless of his selection.

5. Asterisks, Footnotes and Caveats: You make a part that fits an F-150 but not the Harley-Davidson model. So you do the very human thing and list that part number thusly: “Make: Ford, Model: F-150*.” Then, someplace else in the file, you say: “*Does not fit Harley-Davidson model.” As with the spelling in rule number four and the relationships in rule number three, the computer has no idea what you mean. It only sees a new model—F-150*—and some extraneous data elsewhere that isn’t related to anything (the footnote). This logical error will either crash the program or simply drop the information as unusable/unrelated. All such qualifications, footnotes, etc., should exist in their own data field directly related to the part number that they reference.

Learn more about standards and find resources.


John Zinn is the senior vice president of Advanced Digital Strategies and the chairman of the communications subcommittee of the SEMA Business Technology Committee . He may be contacted via e-mail at jzinn@digstrat.com or via telephone at 949/528-6522.

Tue, 08/04/2009 - 14:35

SEMA NEWS - August 2009

By John Zinn
Illustration Colby Martin

 

Get Your Thinking And Strategy Headed Toward Efficiency And Accuracy

  SEMA News-August 2009-Data 01
  Make sure that you always spell the same information the same every time you use it. Example: Chevy and Chevrolet. We all know each of these are the same, but the computer sees two distinct makes.

The list contained below should be used as a very basic litmus test as to the usefulness of your electronic product information. Correcting or addressing all of these issues does not equal standards compliance, but it will serve to get you headed in the right direction and redirect your overall thinking and strategy.

It will also increase the efficiency and accuracy with which your product information is made available to the consumer. If you haven’t done so, please take the time to read the other articles in this issue relating to product data/product information to better understand how absolutely critical it is that you take a good, hard, honest look at what you are currently calling your “product data.”

1. PDFs Are Not Data Files: PDFs, Word documents, read-only files of any type, heavily formatted Excel files (more on this in rule number two) and any other file format that is not “relational” should never be used for electronic product information distribution. The single most universally accepted and flexible format is .CSV (comma separated values). You should always have a copy of your product information in .CSV for immediate distribution.

2. Product Data Isn’t Pretty: This relates primarily to Excel files and is one of the most common errors made in data/product information formatting and distribution. The tendency to want to “dress up” the file with colors, fonts, graphics and otherwise mimic the appearance of a catalog page renders the information contained within that file virtually useless to anybody wishing to make electronic use of the same. Good product data isn’t pretty; don’t try to force it to be so. It’s okay to have a separate file for human consumption that is dressed up, but don’t ever send that to somebody asking for electronic product information.

3. Computers Aren’t Auto Enthusiasts: Never combine information in a single data field, even if you and everybody else in the industry know exactly what it means. Electronically, product information is stored, manipulated and displayed by leveraging simple relationships between data points. If you have any data fields that look like this…

SEMA News-August 2009-Data 02

…you are guilty of this critical error. A computer cannot possibly know which model belongs to which make. Each of these “relationships” must be firm and one to one. One make to one model. Period. Repeat this for the same part number as many times as it takes to keep a one-to-one relationship between all data points.

4. Spelling Counts: Make sure that you always spell the same information the same every time you use it. Example: Chevy and Chevrolet. We all know each of these are the same, but the computer sees two distinct makes. If this were imported into a website as is, for example, the vehicle selection drop-down menu would offer you both choices—Chevy and Chevrolet. Which do you choose? And each selection will display only the products listed with that spelling. So the customer or counter/phone salesmen won’t see everything that’s available regardless of his selection.

5. Asterisks, Footnotes and Caveats: You make a part that fits an F-150 but not the Harley-Davidson model. So you do the very human thing and list that part number thusly: “Make: Ford, Model: F-150*.” Then, someplace else in the file, you say: “*Does not fit Harley-Davidson model.” As with the spelling in rule number four and the relationships in rule number three, the computer has no idea what you mean. It only sees a new model—F-150*—and some extraneous data elsewhere that isn’t related to anything (the footnote). This logical error will either crash the program or simply drop the information as unusable/unrelated. All such qualifications, footnotes, etc., should exist in their own data field directly related to the part number that they reference.

Learn more about standards and find resources.


John Zinn is the senior vice president of Advanced Digital Strategies and the chairman of the communications subcommittee of the SEMA Business Technology Committee . He may be contacted via e-mail at jzinn@digstrat.com or via telephone at 949/528-6522.