The Southpark Google Organizational Information Flow Patent Application

Ok, my title is a mouthful, but you have to love a patent filing that uses South Park characters in examples. Even if it is a somewhat odd patent filing.

Kyle, Stan, Kenny, and Cartman are programmers who report their daily code production to Mr. Garrison. Kyle creates a node datum 1001 reporting 111 lines.

The node datums are illustrated as using a markup language although any defined data format can be used. Kenny creates a node datum 1003 reporting 141 lines.

Cartman creates a node datum 1004 reporting a massive 214 lines. Cartman also creates a node datum 1002 for Stan reporting 66 lines.

Perhaps Stan should not trust Cartman.

[0045]The programmer’s node datums 1001-1004 are sent by each programmer’s node to Mr. Garrison’s node where they are aggregated to produce node datum 1005 reporting 532 lines were produced by Mr. Garrison’s third graders. Node datum 1005 is sent to Principal Victoria.

This patent application seems like it might work more towards describing an internal organizational process than a commercial one (though I’m not ruling out the possibility of commercial application).

Which leads to the question, how does information flow from person to person at the Google?

We just may have been given a little insight into how information runs from one person to another at the Googleplex (beyond the use of their Moma intra-network).

The patent application, published this week at the USTPO and assigned to Google, discusses a system that captures both formal and informal information flows through a large organization.

A “formal” information flow is something like reporting and task assignment that flows through a hierarchical organization. An example of an “informal” information flow is gossip.

One of the authors of the patent filing, Tal Dayan, was the Director of Architecture, Human Capital Management, at PeopleSoft before joining Google. The patent application is:

Distributed metrics collection
Invented by Tal Dayan and Brian Chatham
US Patent Application 20070293144
Granted December 20, 2007
Filed June 16, 2006


Distributed metrics collection systems and methods can be used to help bind together a large organization by implementing both formal and informal information flows. Hierarchical reporting and tasking are formal information flows. Gossip is an informal information flow.

Users use a set of modules to configure distributed metrics collection. Management type users can configure data flows that appear similar to hierarchical reporting. All users can configure data flows that simply distribute items of interest.

Over time, the data flows evolve in an organic manner as users appear, move, change interests, and leave.

There are a few illustrations of how this system might be set up, and a number of examples, including a distributed information database, electronic signatures, encryption of data, metrics, how employees report to management, and how management assigns tasks to employees, how productivity might be reported, and how people might be rewarded.

The other SouthPark example in the patent document shows how this system can be used to reward people:

Principal Victoria is rewarding the third graders with 1000 cheesy poofs in recognition of their 532 lines of code.

She creates node datum 1101 which is sent to Mr. Garrison’s node. Mr. Garrison’s node uses a distribution transform to transform node datum 1101 by distributing the reward to Kyle, Stan, Kenny, and Cartman.

The specific distribution that Mr. Garrison uses divides 40% of the reward to the programmers based on each programmer’s reported productivity.

Mr. Garrison’s node transforms Principal Victoria’s node datum into node datums 1102-1105. Node datum 1102 rewards Kyle with 83 Cheesy Poofs. Node datum 1103 rewards Stan with 49 Cheesy Poofs. Node datum 1104 rewards Kenny with 106 Cheesy Poofs. Node datum 1105 rewards Cartman with 160 Cheesy Poofs.

Mr. Garrison’s node also generates report 1106 informing Mr. Garrison that he also gets Cheesy Poofs.


Author: Bill Slawski

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