{"id":353,"date":"2005-06-02T18:56:23","date_gmt":"2005-06-02T22:56:23","guid":{"rendered":"http:\/\/blogs.law.harvard.edu\/benadida\/2005\/06\/02\/business-and-branding-normalized\/"},"modified":"2005-06-02T18:56:23","modified_gmt":"2005-06-02T22:56:23","slug":"business-and-branding-normalized","status":"publish","type":"post","link":"https:\/\/archive.blogs.harvard.edu\/ben\/2005\/06\/02\/business-and-branding-normalized\/","title":{"rendered":"Business and Branding, Normalized"},"content":{"rendered":"

<\/a><\/p>\n

In software and, more specifically, data modeling, there is a concept called normalization. The idea of normalization is to determine the dimensions of your data in order to prevent duplication and ease data maintenance in the long run. For example, you might want to categorize your instant messenger buddies into “Work,” “Family,” and “Friends.” How should this data be stored and displayed? The simplest way is a straight-forward table:<\/p>\n

\n
\r\nPhil, friend\r\nClaire, family\r\nPierre, family\r\nOliver, friend\r\nBob, work\r\nAlice, work\r\n<\/pre>\n<\/blockquote>\n
But what happens if you want to change “work” to “colleague?” What if you want to start giving special permissions for all of your “friends” (say, they can IM you after 9pm) that work colleagues shouldn’t have? That’s when you normalize<\/b>, by taking the concepts of “friend,” “family,” and “work” and storing them (and even displaying them) separately. Your view becomes:<\/p>\n
\n
\r\nFriends - can contact me after 9pm\r\n  Phil\r\n  Oliver\r\nFamily\r\n  Claire\r\n  Pierre\r\nColleagues\r\n  Bob\r\n  Alice\r\n<\/pre>\n<\/blockquote>\n
This reduces data duplication and helps data processing. Concepts are more clearly defined (what exactly do you mean by ‘friend?’), and data is organized and displayed far more clearly. Normalization organizes your data and makes it clearer.<\/p>\n
Let’s switch gears completely for a moment.<\/p>\n
Creative Commons<\/a> allows you to license your documents to others under a more permissive regime than default copyright. If you see a CC logo, you know exactly what that means about the content. The same goes for the term “open-source” when it comes to distributing software. There is a very clear definition of what a Creative Commons-licensed document is, of what open-source software<\/a> means. These concepts are clearly defined.<\/p>\n
And I just found out, through Larry’s blog<\/a>, about a new type of “tag,” the Fair Employment Mark<\/a>. A company promises, via contract, to adopt the policies of the Employment Non-Discrimination Act (ENDA, a bill that everyone claims to support but that hasn’t yet passed), and in return, they get to use the Fair Employment logo.<\/p>\n
What does this all mean?<\/p>\n
It means that when you go to Magnatune<\/a> or Flickr<\/a>, you know something about these companies immediately from their use of Creative Commons licenses. When you find a software vendor like JBoss<\/a>, you know immediately that their software is available with source code. And, eventually, when the Fair Employment mark is adopted, you’ll know something right away about the company that displays the logo.<\/p>\n
Each concept is individually well defined, branded, and publicized. An organization can simply reference these concepts, and immediately you know something about that organization. The older behemoth had to advertise in every possible medium with catchy tunes and slogans to create a single, unique brand. Today, a small group can immediately create a “corporate image” by picking and choosing the existing, normalized concepts by which they abide, and voila, instant, composite branding.<\/p>\n
This seems quite powerful, especially for small businesses and non-profits. And, of course, it comes with the same big complication as software normalization: weak compliance with normalized concepts reduces the overall value of the system. The success of such a system is dependent on strictly-defined concepts. That’s why “CC”, “open-source” and hopefully “FE” will work. That’s also why TrustE, ISO9000, and the like mean almost nothing in practice.<\/p>\n","protected":false},"excerpt":{"rendered":"
In software and, more specifically, data modeling, there is a concept called normalization. The idea of normalization is to determine the dimensions of your data in order to prevent duplication and ease data maintenance in the long run. For example, you might want to categorize your instant messenger buddies into “Work,” “Family,” and “Friends.” How […]<\/p>\n","protected":false},"author":93,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[127],"tags":[],"class_list":["post-353","post","type-post","status-publish","format-standard","hentry","category-general"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/archive.blogs.harvard.edu\/ben\/wp-json\/wp\/v2\/posts\/353","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/archive.blogs.harvard.edu\/ben\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/archive.blogs.harvard.edu\/ben\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/archive.blogs.harvard.edu\/ben\/wp-json\/wp\/v2\/users\/93"}],"replies":[{"embeddable":true,"href":"https:\/\/archive.blogs.harvard.edu\/ben\/wp-json\/wp\/v2\/comments?post=353"}],"version-history":[{"count":0,"href":"https:\/\/archive.blogs.harvard.edu\/ben\/wp-json\/wp\/v2\/posts\/353\/revisions"}],"wp:attachment":[{"href":"https:\/\/archive.blogs.harvard.edu\/ben\/wp-json\/wp\/v2\/media?parent=353"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/archive.blogs.harvard.edu\/ben\/wp-json\/wp\/v2\/categories?post=353"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/archive.blogs.harvard.edu\/ben\/wp-json\/wp\/v2\/tags?post=353"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}