Correlation is not always Causality. .
Predicting the future requires an understanding of cause and effect. .
A sequence of progressive hypothesis testing is the most efficient and effective method to derive competitive advantage from data. .
Data alone does not yield competitive advantage. .
I’ve been reading four books simultaneously these days. Of course, I shouldn’t really say simultaneously. I can only read one at a time. More accurate language would be ‘jumping between four books’. The first is Sam Ladner’s excellent thesis on the commodification of time in the new economy. It’s a pretty awesome read. The second is Gladwell’s latest book. And it’s a manageable read because the chapters are well contained. It’s called “What the dog saw”, and that line is pulled from one of the Chapters on Caesar Milan. Fun! The third is a seminal 500 page book about competition. And it’s a sobering read. And the fourth is about mental structures in the new economy. And I haven’t decided[…]
The purpose of analytics is to derive competitive advantage for the organization / firm / entity. .
You may or may not have been hearing about a debate going on in web analytics. To most, it might seem like a lot of inside pool. And I suppose most of these things are. I want to talk a little bit about some of that inside pool. Over the course of my WAA Research Committee work last week, I stumbled upon a paper entitled “Assumptions, Explanations, and Prediction in Marketing Science: “It’s the Findings, Stupid, Not the Assumptions” by Eric W. K. Tsang. In it, he replies to a debate that’s been going on for a long time, but what natural scientists had settled a hundred years ago. Richard Staelin back in 1998 said that there’d always be debates[…]
The central scar, the central schism, as I view it, is in the disconnect about what analytics should be and what it actually is. There are those who look to the past. It is perfectly possible to do very thorough analysis about why what happened in the past, happened. There’s a large amount of valuable competitive advantage to be had that way. There are those who look to the past only to find evidence to confirm what they remember having thought. These are proof-seekers or justifiers. No further analysis over and above the baseline amount of proof is required. And, if the proof is unsatisfactory – then the data must be inaccurate. Frequently, all that is required is a simple,[…]
I applaud Joseph Carrabis for writing “The Unfulfilled Promise of Online Analytics, Part 1“. You need to read it if you want in on the debate. There’s been a fundamental schism in analytics since the 1930’s – between ‘advertising’ and ‘marketing’, really, as far as I can tell, since Hopkins died and was forgotten. So when Joseph holds up a mirror to the web analytics industry of course it’s going to be ugly. Of course you’re going to see a massive, gaping, puss-filled wound running diagonally across the face. I’m not going to shoot the person holding the mirror. Neither should you. And I’m not going to personalize the debate, either. I think we might be tempted to boil this[…]
An episode of South Park called “The F-word” aired on Friday night in the US, and Saturday night in Canada. Matt Stone and Trey Parker aired what many of us in social analytics knew already: the re-appropriation of the F-Word. The word has a lot of history attached to it. I don’t like the hateful connotation of the word myself. I’m not using it in that connotation. Far from it. I can get past history that to discuss an important phenomenon and the implications. So, if you’re uncomfortable with the implications of the term – stop reading and move along. I’m stating, very clearly, that if you don’t like the word – stop reading. ……. I’ll start by bringing everybody[…]