Thinking Out Cloud - Mass Customization and Market Data
from Xand : Joel York - 31st December 1969
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Henry Ford once said: "Any customer can have a car painted any color that he wants, so long as it is black." Then, in 1923 Alfred Sloan came along and cleaned his clock by offering a tremendous variety in colors and models. But, Sloan didn't do it one customer at a time. GM redesigned its manufacturing line with the flexibility to produce a multitude of models and colors without compromising the inherent economies-of-scale of Ford's assembly line innovation-a practice that today has evolved into the concepts of flexible manufacturing and mass customization.
What does any of this have to do with cloud computing? And for that matter, what does it have to do with financial market data? This is the third post in a series called "Thinking Out Cloud" with the aim of helping financial services and market data IT professionals charged with developing cloud computing strategies separate the cloud buzz from the cloud reality. This post explores the important idea of mass customization in the cloud and its relevance to market data management.
Mass Customization and Market Data
According to Wikipedia, mass customization is about providing "services to meet individual customer's needs with near mass production efficiency" by offering a "tremendous increase in variety and customization without a corresponding increase in costs." Or rather, have it your way at a cost you can afford. In the last installment in this series entitled Thinking Out Cloud - The Market Data Sweet Spot, I pointed out that the best way to identify market data that can benefit from cloud computing is to look for data that is hard-to-use, hard-to-manage, and hard-to-access. Mass customization on the cloud strikes at the core of the "hard-to-use" problem by replacing inflexible data feeds and files in static formats with financial Web services that allow applications to select and consume highly customized market data sets on the fly.
Mass Customization, Meta Data and Web Services
In software, mass customization is achieved by converting hard-coded application functions into meta-data, so that the functional behavior of the software can be controlled through data on an ad-hoc basis. For example, the only real difference between this Xignite Wordpress blog and a million other Wordpress blogs comes down to a few theme files and the store of data that comprises the brilliant blog posts within. The posts in turn get shuffled around the Internet using RSS (really simple syndication). The RSS standard lies at the heart of the Web 2.0 revolution, powering the distribution of widely varied content such as blogs, news, friends, tweets, music, video, etc., all because a few abstract meta-data elements like "title", "description", and "link" can be generalized to contain an enormous and disparate variety of data. Swapping out this data can literally change one blog to any other blog (or one friend to any other friend!).
In cloud computing, meta-data abstraction is realized through Web services (like RSS). Web services take the concept of configurability through meta-data abstraction to its natural limit, because every operation of a Web service is inherently abstracted to meta-data in the XML inputs and outputs of the API. For example, the Xignite delayed stock quote Web service allows applications to retrieve a single quote for a single symbol, multiple quotes for multiple symbols, intraday tick-by-tick prices, market volume and news, simply by varying the Web service operation and the input parameters, i.e., the meta data. Providing access to such a wide variety of information in an ad-hoc fashion from a statically formatted feed or file is simply not possible without lots of hardware, software and custom development-most likely to create a Web service.
Wrap it Up, I'll Take It!
More plainly, market data Web services are built for mass customization, because they cleanly wrap the underlying market data and data management infrastructure in meta-data enabling highly customized output based on variable input. Therefore, applications that require highly varied, ad-hoc market data subsets will be better served by Web services over the static formats of data feeds and files. Or, as we like to say at Xignite: "There's an op[eration] for that!"