Recently I met with a dozen senior IT folks.  Though I have known for a long time that major corporations restrict employee Internet access, I was surprised to hear how vehement these dedicated IT senior managers were about it. They cited three reasons:

1. Productivity (which they say is by far the most important)
2. Compliance, regulatory issues and concern over inappropriate messaging
3. Bandwidth usage (a distant third)

The question of productivity is nothing new. Telephones and “personal” calls or worse “personal long distance” calls caused the same productivity and cost concerns for companies in the mid 20th Century. Businesses had no ability to restrict access  so, in the absence of tech tools, they exerted professional discipline on their employees. It was expected that people would stay focused and stay off the phone on personal business. And, in some firms phone bills were spot checked after the fact. Unfamiliar long distance calls were questioned.

Compliance issues do hold a special concern, posting inappropriate content or corporate secrets to blogs, Twitter, Linkedin or Facebook is an issue. But the sharing of confidential information is nothing new. Inappropriate memos and insider trading have been with us forever and there are laws and consequences for such behavior.

So if bandwidth is not an issue, why are CIOs playing Kindergarten Cop?   Given other hugely important issues such as Security, shouldn’t CIOs be focusing more time on that and leave the issues of professionalism up to HR and management?

I was awe struck at how ineffective the CIOs were at restricting access to the Internet – people are simply using their mobile digital devices for Internet access – untraceable, available, personal. If ever there was a reason for HR to step in and set parameters for personal professional behavior, mobile access is it. Attempting to control employee Internet access is a total waste of precious CIO productivity.

A most remarkably huge section of the Wall Street Journal was wasted today on Follow The Tweets an article by three professors who set out to attempt to predict which movie would do best at the box office based on Tweets.

Reading the article was like watching a bunch of accountants put a dollar value on “good will” in a business valuation. These three academic stooges created a “model” of course. And used LOTS of servers to store LOTS of Tweets on three movies launched on the same day.

They used Twitter’s “advanced” search feature that is “capable” of measuring whether a Tweet is good or bad based on emoticons vs . OMG!  Even our academics had to admit this is not scientific. I hung in and read on…

Their “model” was a “bit” more sophisticated. REALLY? Their model adjusted for “language” issues, as in when people are talking vacuum cleaners and Tweet “it sucks!” that would be a good Tweet. Language is nuanced and notoriously tough to measure in any quantitative fashion, and it certainly can’t be done on a broad scale (thus Twitter’s silly emoticon measurement).  How much more sophisticated could these professors’ model be beyond emoticon measurement? Not much.

They were able to successfully “predict” the biggest grossing movie – but only in retrospect, which is not really predicting is it?

Beyond the obvious problems, they’re data was purely relational, there was no way of knowing how many Tweets make a winner, just that one movie got more “positive” Tweets than the others. But it could have easily been a statistically insignificant number. And here is the kicker: the true predictive information was available within 24 hours of the first weekend release, not in Tweets, but in the box office receipts. DUH.

This only proved one thing: there are enough Tweets about movies to give three professors enough data to write something utterly inane and enough ignorant editors at the WSJ to approve the article.

For other large industries this model is hardly applicable.  Products do not launch at the same time. Not everyone who Tweets is your customer. There maybe a whole lot more people who are your customers and have very strong “predictive” feelings who NEVER Tweet.

For the rest of us, in businesses and industries outside mass appeal – that would be the vast majority of companies and small businesses – this exercise is TOTALLY useless.  We are trees falling in a Tweetless forest.  Turning to Tweets as a predictive measure is a waste of time. Meaningful interactions with our customers and prospects via the medium THEY prefer a far better use of our time.

Given the increasing speed of hype cycles on the web it is absolutely NO surprise that according to Nielson, Compete.com AND Comscore Twitter traffic is tanking.

The measurements do leave out other methods of access, mobile among them. Regardless, I am nailing the the last nails in Twitter’s coffin today.

The problems with the Twitter model have been many. For one it has never been more than an easily replicatable software feature. In fact, Facebook has done a good job of doing just that with its new Live Feed. (But please don’t take that as an endorsement of Facebook, it is mercilessly unintuitive.)

Twitter is now flooded with inane commercial messages making it spam on steroids. So where it once might have been very relevant, it is fast becoming noisy cluttered and virtually useless.  If relevancy is the gold standard of the Internet – Twitter is dead.

If 2007 was the year of MySpace, 2008 the year of Facebook and 2009 the year of Twitter – what will 2010 be?

Foursquare.com, that’s my bet.