THE OFFICE RADAR O'REILLY

THE SITUATION
Margaret M. was an overweight and unattractive office assistant serving the sales staff of an Internet marketing firm. She didn't have much of a sense of humor, and didn't socialize much among the office staff. However, she was reliable and dependable, there were never any complaints about her getting her job done, and she rarely complained. While the quality of her work was appreciated, she was not the squeaking wheel that got the grease when pay raises were issued.

It wasn't until Margaret and three of her staff each gave two-week notices within a month of each other and left to go to a competitor that Margaret's true value became recognized. The office literally disintegrated - important though low-profile tasks like routing invoices had always been handled by Margaret, and descriptions of critical job functions hadn't been updated in years (if you needed to know how to do something, you would just ask Margaret). Even months after over-staffing with repalcements, the office did not run as efficiently as it had on fewer employees, and some customers used to the way things had been done during Margaret's tenure did not return.

CURRENT TECHNOLOGY
The primitive tools previously available focus primarily on discipline and loss prevention; none have the ability to recognize unique abilities, or individuals at the center of complex communications, and none can reconstruct the historical work habits of an employee.

THE VIEWSENDER SOLUTION
viewSender tracks all of an employee's activities on the computer screen, and also reduces all screen content to its text equivalent. By reverse logic, this means that for every text file there is an associated screen image. Therefore, if you wanted to know who in an organization was performing a task associated with a set of keywords, you would need only to search viewSender's captured text archives for those keywords, and then request the user associated with the most matches. In the example cited above, you might search on "route invoices" and discover that Margaret had historically been doing those tasks. You could then pull up the images associated with those keywords, and work backwards and forwards through the associated images to create a filmstrip of all the steps Margaret used in various sessions when she routed invoices.
viewSender could also tell you when Margaret and her clerks were becoming dissatisfied, getting other offers, or putting their resumes together, and why, based on keywords. You could then prevent their leaving by rewarding them more handsomely, or at worst, be better prepared for their departure with some respect for the work they had been doing.

One of the most exciting features of viewSender is an optional text analysis tool (available later) which can discern the flow of information across an organization. This tool scans incoming captured text for unique keywords and seeks similar patterns in previously scanned text. It can in this manner detect the spread of e-mails, files, information, negativity, and gossip across the organization. It can detect the significant relationships between individuals - that Margaret always had to prepare Bill's expense reports, for example, as well as screen his e-mail. It can see that important procedural questions were originated elsewhere but were relayed at some point to Margaret. In other words, this optional feature can be set up to identify key individuals and roles in an organization (even if outside the job descriptions) and ensure those key players are being rewarded and otherwise cared for in the best interests of the organization.