Analytics continues to be a very manual process because of the great disconnect between data collection tools, data analytics tools, data vizualiation tools. The analyst frequently takes data out of the collection tools and puts it into an analytics tools (sadly, an excel spreadsheet where it’s tortured) and then from an excel spreadsheet into a communication medium (Powerpoint, Word, GGOBI, another excel spreadsheet). This movement of data from one place to another is touching. Should human fingers touch data? There have been great advancements within the data measurement tools in 2009: Google, Omniture, Coremetrics, Web Trends, Unica. We’re able to slice and dice and vizualize data like never before within these tools. I applaud that. Progress has been made. I[…]
I’ve just learned of eScience as a result of a book entitled “The Fourth Paradigm”. While I don’t have that much to say about the essence of the Fourth Paradigm yet, I have to admit that I feel immediately at home with this group within eScience. One of the best quotes in the book is: “Need driven versus curiosity driven. Basic science is question driven; in contrast, the new applications science is guided more by societal needs than scientific curiosity. Rather than seeking answers to questions, it focuses on creating the ability to seek courses of action and determine their consequences.” Substitute ‘societal needs’ with ‘business needs’, and I have myself a nice bridge between eScience and commercial eScience. I[…]
If the output of an analytics program is competitive advantage – it follows that it’ll be a source of profit to be optimized as opposed to a cost to be minimized. Web reporting is to marketing as accounting is to business. Analytics is to marketing as management science is to business. This is about as clear of an argument as I can make for the scientific practice of analytics.
Preliminary results from a membership survey suggest a strong level of satisfaction with the work coming out of the Web Analytics Associations’ Research Committee. And that’s heartening, since the volunteers do a lot of work. I’ve participated in some of that research over the years, and it’s always pretty enlightening. It’s good news.
I’ve spent a lot of time this week managing complexity. And it’s gone well. I think looking for simple and remembering the end goal are two key ingredients. Backcasting happens a lot. Expecting exogenous shocks instead of being all outraged when they happen is another. That’s all that’s really on the mind. That and how much code I have left to write. 🙂
1. The purpose of analytics is to derive competitive advantage for the organization / firm / entity.2. Data alone does not yield competitive advantage.3. A sequence of progressive hypothesis testing is the most efficient and effective method to derive competitive advantage from data.4. Predicting the future requires an understanding of cause and effect.5. Correlation is not always Causality.6. Accuracy over Precision.7. It is possible for there to be two optimal, equally true, answers to a problem. (And Sometimes More!) (X^2 = 4, x=-2, 2). And what’s the point of the seven axioms? I’m stating, as clearly as possible, what I believe to be at the root of how analytics should be practiced and it should be anchored to reality. Explicit[…]
It is possible for there to be two optimal, equally true, answers to a problem (And sometimes more!). (X^2 = 4, x=-2, 2). .
Accuracy over Precision. .
I published seven axioms over the past week – in a not so humble fashion. I’m taking the James Burke line to heart and just putting it out there. The Seven Axioms are: 1. The purpose of analytics is to derive competitive advantage for the organization / firm / entity. 2. Data alone does not yield competitive advantage. 3. A sequence of progressive hypothesis testing is the most efficient and effective method to derive competitive advantage from data. 4. Predicting the future requires an understanding of cause and effect. 5. Correlation is not always Causality. 6. Accuracy over Precision. 7. It is possible for there to be two optimal, equally true, answers to a problem. (And Sometimes More!) (X^2 =[…]
I’m reading Sam Ladner’s thesis. It’s strong work, and quite possibly one of the best reading experiences I’ve had since “Reading Virtual Minds”. On Page 149, there’s a quote in explaining the common occurrence for ‘fires’ to occur as a result of low-ball estimation: Curt: Why do they have the fires? Sam: Yes Curt: There could be a million different reasons if you think about it, I mean, clients coming in with aggressive timelines period or everybody will come in with big dreams, right?…Like you never lose the champagne dream even if you’ve got a beer bottle budget, right? You always dream big but you might not be, like, okay…” And I’m in awe. What a gem. And I ask[…]