[scenarios] Noogle's decline explained by a bug in its Predictor?

Noogle's decline explained by a bug in its Predictor?

Brussels - Over the past quarters, Noogle's share price dropped significantly as the company failed to deliver on key features and updates to its service line, and service suffered from major disruptions and intrusions. Investors and clients alike have been wondering why the better half of the ex-Google imperium started to... well, for lack of a better word 's*ck'. Our undercover reporter might have found the answer: the famous Predictor software that allows Noogle to attract and retain the best of the best apparently had a fatal flaw causing thousands of 'mis-hires' in the last year alone.

Predictor is the software used by Noogle to screen applicants by predicting their performance impact. Noogle  stands for not-Google, and is the better of the two Google halfs created after courts ordered the monopolist to break itself up. The Predictor algorithms are better protected than the recipe for Coca-Cola and are assumed to be the key to the success of the steady rise of the company. The many people seeking to work for the company need to give Predictor permission to use every possible piece of information available to predict how big of an additional asset they would be to the talent pool of the company. Noone knows exactly what the Predictor looks for, but we can assume it finds your passion, learning, viewing and reading history, appraisals, goes into your social networks for your relational skills, etc. As a thank you, the many unsuccesful applicants get a list of learning resources to skill themselves in a future-proof way.
A reliable insider informs us that during one of the finetunings of the software for future trends, a bug entered The Predictor, causing thousands of mis-hires. It is not clear if the bug was accidental or the result of industrial espionage. Rumor has it Noogle compiled a list of the mis-hires, and tries to convince them to leave the company.

Note: this article and the matrix above are part of the 'learning scenarios' initiative. At Online Educa we created 4 possible scenarios for the future. They are based on the axes of how work is organised (managed versus enabled) and how work is done (data driven versus relationship driven). The fictious article above falls in the quadrant of 'big data'. For the usage and making of scenarios please refer to the learningscenarios.org site. Scenario planning is a good tool to use in an agile world. Here is what to (not) do with scenarios:

• DO : flesh them out so you can feel and smell what that future would be like
• DO : look for indicators if a particular scenario is on the rise
• DO : use the scenarios for mid- and long-term planning and investment decisions
• DO : make plans for when the scenarios become reality
• DON'T : judge. We all have preferences. They don't matter for this exercise.

Over the next posts, I'll create other fictious articles for the other quadrants. Then, I'd like to do an exercise on how leadership might be different in each of the four quadrants.

• OLD BOY : Guild Tournament Final Airs Tonight
• INCROWD : IBMzon launches Talent Cloud
• QUANTIFIED SELF : "Did you thank someone today?" asks Otto, the self coaching app
• BIG DATA : Noogle's decline caused by Predictor bug?

Oh, you should also participate in the learning scenario exercise.