As a visiting scholar at Pacific Timesheet, I recently completed a research study: “Whacky Technology Ideas That Cannot Even Be Called Silly.” Though it was not my intention, it has become a tribute to how great Steve Jobs really was, by surveying the thousands of bad ideas and new product road kill created by other lesser brains during the Age of Steve (1979 – 2011). The study included a way to watch TV with an inhaler (don’t ask), a new kind of ethanol you could manufacture from old bed sheets, and force-field furniture for people who move a lot and have no friends. However, my favorite example of a failed technology product was “The Data Hat.”
The Data Hat
The Data Hat was developed in Silicon Valley, where “prima donna engineers,” as they are called, outnumber all living things by 100:1. The product’s history began in 2002 when the senior managers of BBS LLC (Big Biolife Stuff) and RTC, Inc. (Really Tiny Chips) got stuck in an elevator in the San Jose Convention Center during the rolling blackout season. After arguing why no one thought to take the stairs when there were only two floors, they began “sharing” about their biggest business problems. Jim Parker, RTC CTO, said “I wish we knew what our best engineers were working on.” Joshua Chen, Chief Information Officer of BBS, finally admitted that “many of our engineers won’t reveal much beyond their employee ID number, like they’re a POW or something.” Staring blankly into the elevator floor buttons panel, Jim Parker interjected: “If only we could get them to fill out timesheets.” Everyone was aghast. The smallest smile started to curl at the corner of Jim’s mouth and Joshua said with a growing laugh, “You joker, you know that’ll never happen.” They laughed for an hour. All of this led to nothing for these companies, but there was a courier in the elevator car who, overhearing everything, told his neuro-engineer cousin Billy Tendra of the need to solve this problem. Tendra worked night and day and came up with “The Data Hat,” a new way to capture data from a person's brain. They would wear the "data hat" while they thought of the data they wanted to upload to the hat’s database. In effect it turned a person’s brain into a kind of keyboard. Tendra first tested the device, which looked like the little sailor hat worn by Mick Jagger briefly during the late 1980’s, with a pilot group of prima donna engineers at ten major semiconductor and biotech life science firms. These prima donnas qualified for the pilot if no one ever knew what they did at work, but yet they kept their jobs anyway. The test was simple. An engineer would place The Data Hat on his head at the end of the week when he wanted to record his time allocation by job or project. He would think about what he did and for how long and the hat would capture the data and upload it to a server on the network. At first, the hats (with an initial price point of $105,000 USD each) were defined as a shared resource similar to the early days of the mainframe time-sharing model. This caused several problems. Having only ten hats shared by 400 engineers in 25 locations led to high courier costs which within only five months more than offset the cost savings of having so few hats. If this continued, a corporate accountant argued in the cafeteria one day, the courier costs would soon be in excess of $12 million. The hats also required radioactive sterilization services because dry cleaning would damage the brim, which was a WIFI antenna, after only three cleanings. There were two classes of engineers, the OCDs , who washed their hair twice a day, and the LICEDs who had not washed their hair since Full House went off the air. The germiphobic OCDs demanded sterilization after each use and the generally left-leaning LICEDs would not put on a radiated hat. Sterilization costs zoomed. Within a month, the outcome was the same; prima donna engineers not providing information on how they were spending their time. Beside the out-of-control costs, there were operational problems. The hats unintentionally would capture so-called “negative or outlier thoughts” that were forbidden in the TDH Project Time Tracking Manual. Though many hours of required training urged the engineers to control their thoughts when wearing the hat, their timesheets became strewn with profanities, song lyrics, and sometimes complicated food recipes. On the day 1,500 employees were laid off at one company, an “18 dirty words and phrases” filter had to be configured so the payroll department would continue processing timesheets. Worse, a so-called “ghost” data effect meant that the thoughts captured from one engineer might linger in the hat and download by mistake into the mind of the next engineer. This led to engineers inadvertently using each other’s passwords, speaking in languages they did not know, and increase the already high number of them wandering around the courtyards aimlessly muttering to themselves. Finally, in 2004 “The Data Hat” project was killed, no refunds were made and the founder Tendra went into the mortgage financing business. In 2007, I ran into Tendra at a Whole Foods in San Jose. He said he just left the mortgage business and was now working full time for the Mitt Romney for President campaign. He said The Data Hat lawsuits were still dogging him, but that he was glad to see me. He knew that I was now a visiting scholar with Pacific Timesheet and had learned, all too late, that Pacific Timesheet had a web-based R & D engineering time tracking solution that allowed engineers to record their percent time allocation by project and/or phase in about 15 seconds using a web timesheet. I asked him why he was still wearing a Data Hat while shopping. He said the upload feature was buggy but that he could download grocery lists into his mind easily. I asked if I could try it on for old time’s sake. I did and a flood of his thoughts entered into my mind. Apparently, he had reviewed the feature lists of the Pacific Timesheet web site that morning. I could see the most relevant features highlighted in his mind: percent time entry, multiple billing rate options, multiple approvals, multiple timesheet templates, published APIs and import/export utilities, hundreds of locales and multiple holiday schedules worldwide, excellent client testimonials and easy-to-use web site navigation. He asked me not to blog about anything he discussed because that would be crass commercialism and be unfairly promoting Pacific Timesheet in a scholarly blog post. I agreed that I would not do that.