The purpose of analytics is to derive competitive advantage for the organization / firm / entity.
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Monday, November 30, 2009
Saturday, November 14, 2009
The Schism in Analytics, A response to Carrabis, Part II
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, static report listing a few numbers.
There are those who look to the future. It is perfectly possible to do very thorough analysis about what could happen in the future and optimize against those scenarios. There's a large amount of valuable competitive advantage to be had that way.
There are those who look to the future only to find evidence to justify what they want to do next. These are validation-seekers. No further analysis over and above the baseline amount of evidence is required. And, if the proof is unsatisfactory - then the data must be faulty.
I think there's a huge market for justification. In fact, I think this is why so many vendors go where the market is. They just respond to the market, don't they? And for most people, it's purely about justification. The tools aren't set up to explain anything in the past because that's not where the market is at. The result is predictable. Tens of thousands of reports generated daily, going unread and ignored: all a function of market demand.
To pin the blame solely on vendors is like blaming obesity on fast food companies. They're only giving the market what it wants, negative externalities be damned.
(Who is anybody to resist market forces?)
I think there's a smaller market for validation, largely because most analysts don't really play that game. One of the reasons why web analysts are infrequently invited to the table is because they kill creative ideas and sometimes, are completely disconnected from how managers really make decisions (this is directly to Hillstrom's point). Because web analysts are generally not very good validators, they're condemned to the bowels of the company, reporting on the past, and infrequently asked about the future.
That's the schism: between Scientist-Practitioners and Everybody Else.
And Everybody Else is kicking our ass.
There's reason for hope though!
I think there's a growing market for actual learning and competitive advantage - driven by science. This isn't justification seeking or validation seeking behavior though.
This is driven by upper management - people like Alan Wurtzel of NBC Universal (September 2009) who literally tired of drowning in data. If anything, they're looking for a consolidation of data by way of scientific methods.
There's a generation of HBR people too - who actually know what innovation really means. They know you have to get there through science.
Therein lies the gap.
Can anybody say, really honestly, that Web Analytics, as it is practiced by 80% of practitioners, is Scientific? Of course not. And we find fault with everybody else: tools, skillsets, and market demand.
Look, the tools have been there all along: SPSS, GGOBI, R. The courses have been available online for a long time. So, alright, SPSS is expensive and budgets are tight, alright, fine. GGOBI is free and so is R. But if that isn't enough, there's more help too:
One of the things that Google is doing to make it easy, part of their grand plan, is to introduce statistical functionality into the baseline tools. Google is creating a world of abstraction - where a web analyst won't need a degree in quantitative methods to be able to operate the scientific method. Truth be told, an analyst doesn't need to be a statistician to use Google Website Optimizer. No, an analyst only needs to have the political skill set an alien ambassador on Babylon 5 to get the tags actually put in.
(Hint to those threatened: That entire political world - about getting things done through a large org chart - is where a whole world of value-add can be found.)
I'm under frieNDA about what is going on elsewhere. They're a huge part of the solution too.
And, I'd like to believe, on sunnier days, that I'm also part of the solution.
Look, you don't need to understand it to use it.
And, to touch briefly on the whole 'Cult of the Amateur' Easy/Hard Towards/Away debate that Carrabis touches upon in his "hard" versus "easy" passage -
Web Analytics didn't exist when I was growing up. The new economy giveth.
Web Analytics, as it is presently practiced, won't exist someday. The new economy giveth away.
Sundry reportage - the generation of justification and validation - will probably take at least twenty years to be destroyed because of the a stubbornly long S curve. And you know what: good enough is good enough for huge swaths of the economy. I understand that there are companies out there that turn trees into toilet paper. I salute them and believe that there are analytical products that are perfect for them. I won't dare call those products "science". (And when they're ready for real science someday, I'll be there too).
I think there's a solution in the schism: honesty and retitling.
If a web analyst has the drive and desire to actually be a real scientist-practitioner, and their company isn't going to go there, then they have the duty to get out or STFU.
If a web analyst doesn't have the drive and desire, then I'd argue that we should retitle that segment of the industry as 'web reporting'. It's not worthy of the term 'analytics' at this point.
I think that vendors who are clearly in the business of web reporting need to come out and say, "we do web reporting", and that vendors who do analytics need to come out and say, "we do analytics, scientifically". That said, we need people who are honest enough and loud enough to call bullshit when a vendor is just that. If it gets nasty, so be it.
I'm convinced that there's a large market for real science - for real strategic value - for real actual learning. It's pent up and generally angry with the web analysts fighting each other.
Whether or not we take the same people who are in the industry now will be with me in five years, is the next cause for debate.
(Monday Morning EDIRT: Eric Peterson wrote "Are you ready for the coming revolution". Some of his sentiment is echo'd in this post. Check out his post and white paper.)
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, static report listing a few numbers.
There are those who look to the future. It is perfectly possible to do very thorough analysis about what could happen in the future and optimize against those scenarios. There's a large amount of valuable competitive advantage to be had that way.
There are those who look to the future only to find evidence to justify what they want to do next. These are validation-seekers. No further analysis over and above the baseline amount of evidence is required. And, if the proof is unsatisfactory - then the data must be faulty.
I think there's a huge market for justification. In fact, I think this is why so many vendors go where the market is. They just respond to the market, don't they? And for most people, it's purely about justification. The tools aren't set up to explain anything in the past because that's not where the market is at. The result is predictable. Tens of thousands of reports generated daily, going unread and ignored: all a function of market demand.
To pin the blame solely on vendors is like blaming obesity on fast food companies. They're only giving the market what it wants, negative externalities be damned.
(Who is anybody to resist market forces?)
I think there's a smaller market for validation, largely because most analysts don't really play that game. One of the reasons why web analysts are infrequently invited to the table is because they kill creative ideas and sometimes, are completely disconnected from how managers really make decisions (this is directly to Hillstrom's point). Because web analysts are generally not very good validators, they're condemned to the bowels of the company, reporting on the past, and infrequently asked about the future.
That's the schism: between Scientist-Practitioners and Everybody Else.
And Everybody Else is kicking our ass.
There's reason for hope though!
I think there's a growing market for actual learning and competitive advantage - driven by science. This isn't justification seeking or validation seeking behavior though.
This is driven by upper management - people like Alan Wurtzel of NBC Universal (September 2009) who literally tired of drowning in data. If anything, they're looking for a consolidation of data by way of scientific methods.
There's a generation of HBR people too - who actually know what innovation really means. They know you have to get there through science.
Therein lies the gap.
Can anybody say, really honestly, that Web Analytics, as it is practiced by 80% of practitioners, is Scientific? Of course not. And we find fault with everybody else: tools, skillsets, and market demand.
Look, the tools have been there all along: SPSS, GGOBI, R. The courses have been available online for a long time. So, alright, SPSS is expensive and budgets are tight, alright, fine. GGOBI is free and so is R. But if that isn't enough, there's more help too:
One of the things that Google is doing to make it easy, part of their grand plan, is to introduce statistical functionality into the baseline tools. Google is creating a world of abstraction - where a web analyst won't need a degree in quantitative methods to be able to operate the scientific method. Truth be told, an analyst doesn't need to be a statistician to use Google Website Optimizer. No, an analyst only needs to have the political skill set an alien ambassador on Babylon 5 to get the tags actually put in.
(Hint to those threatened: That entire political world - about getting things done through a large org chart - is where a whole world of value-add can be found.)
I'm under frieNDA about what is going on elsewhere. They're a huge part of the solution too.
And, I'd like to believe, on sunnier days, that I'm also part of the solution.
Look, you don't need to understand it to use it.
And, to touch briefly on the whole 'Cult of the Amateur' Easy/Hard Towards/Away debate that Carrabis touches upon in his "hard" versus "easy" passage -
Web Analytics didn't exist when I was growing up. The new economy giveth.
Web Analytics, as it is presently practiced, won't exist someday. The new economy giveth away.
Sundry reportage - the generation of justification and validation - will probably take at least twenty years to be destroyed because of the a stubbornly long S curve. And you know what: good enough is good enough for huge swaths of the economy. I understand that there are companies out there that turn trees into toilet paper. I salute them and believe that there are analytical products that are perfect for them. I won't dare call those products "science". (And when they're ready for real science someday, I'll be there too).
I think there's a solution in the schism: honesty and retitling.
If a web analyst has the drive and desire to actually be a real scientist-practitioner, and their company isn't going to go there, then they have the duty to get out or STFU.
If a web analyst doesn't have the drive and desire, then I'd argue that we should retitle that segment of the industry as 'web reporting'. It's not worthy of the term 'analytics' at this point.
I think that vendors who are clearly in the business of web reporting need to come out and say, "we do web reporting", and that vendors who do analytics need to come out and say, "we do analytics, scientifically". That said, we need people who are honest enough and loud enough to call bullshit when a vendor is just that. If it gets nasty, so be it.
I'm convinced that there's a large market for real science - for real strategic value - for real actual learning. It's pent up and generally angry with the web analysts fighting each other.
Whether or not we take the same people who are in the industry now will be with me in five years, is the next cause for debate.
(Monday Morning EDIRT: Eric Peterson wrote "Are you ready for the coming revolution". Some of his sentiment is echo'd in this post. Check out his post and white paper.)
Thursday, November 12, 2009
The Schism in Analytics, A response to Carrabis, Part I
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 down to a difference between two wildly successive authors.
It's more than two authors. They're just latest incarnations of that schism.
How do we stitch the face back together?
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 down to a difference between two wildly successive authors.
It's more than two authors. They're just latest incarnations of that schism.
How do we stitch the face back together?
Sunday, November 8, 2009
South Park and implications for Social Marketing
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 onto the same page, and then I'll write, at length, about the implications for advertisers (Harley in particular) and the implications for social marketing.
The episode starts with a pretty huge insight: the damage that bikers do to communities. In effect, bikers produce a negative externality, the production of a massive amount of noise, to the detriment of all others. (Ever been on a patio in Toronto? Yup - South Park covers that too.)
You can watch the full episode at the link below and follow along. If you don't have the time, a summary follows.
If you want to watch on the Comedy Network, you're looking for South Park, Season 13, Episode 12.
http://www.southparktv.info/season-13/season-13-episode-12
In the beginning, the boys are enjoying a wonderful day outside.
Then they hear that loud noise of the motorcycle.
The motivations of bikers for making such noise is laid bear by Parker and Stone in the subsequent scene. It's all about the need of bikers for attention.
What then follows is the appropriation of the term 'fag' to bikers at 2:28 by Eric Cartman.
The bikers end up being even louder, which prompts the boys to hatch a plan. At 5:43 into the episode, Butters does a nice speech empathizing with the bikers. He's summarily dismissed and the boys plan to take dumps on the bikers seats and to write "go away fags" in a number of places about town.
Predictably, at 8:20 into the episode, Big Gay Al and Mister Slave, two recurring and tolerant characters on the show, are walking down the street and sees these huge words written everywhere.
Outrage ensues and a town meeting is held. The mayor is pissed.
Stan and Kyle take total credit for it.
At 9:20, they remark that the term 'fag' has nothing to do with 'gay people'. In effect, they don't see the relation at all between the term 'fag' and 'gay'.
At 9:40, the bikers retreat the library and to the dictionary. Stone and Parker actually recite the long history of the word fag, and are clearly setting up the next huge act of the show.
At 11:40, the boys are pulled in front of a board, where the adults proceed to try to understand the term. Fag becomes known as "an inconsiderate douchebag".
The boys ask: "Don't you people keep up with today's lingo at all"? (I lolled.)
At 13:00 Big Gay Al goes into an organization to rally behind the boys, supporting the re-definition.
At 14:00 the mayor signs an ordinance making the term permissible and re-defined.
At 15:15, the mayor freaks out and calls the boys into her office, now. Predictably, the progressives are freaked out about the actual term within the dictionary as being pejorative to homosexuals.
At 16:00, the boys solution is that they have to change the dictionary definition so they could be free to call Harley drivers 'fags'.
Predictably, at 16:50, the bikers decide to resort to violence.
At 17:10, South Park welcomes the head dictionary editor in an effort to convince them to change the term.
This sets up the climax.
In a delicious piece of esoteric satire, Emmanuel Lewis is the dictionary editor ("What Choo Talkin' 'bout Lewis?") comes to town. The bikers show up to beat the crap out of everybody, including Emmanuel Lewis.
At 21:30, Stone and Parker make a direct appeal to the audience, breaking the fourth wall, calling upon all children to call all bikers faggots across America. At 22:00, the editor of the dictionary declares the definition.
Kyle walks forward, breaking the fourth wall again, and says, "this day, we've made history".
The new definition of the word 'fag' appears on the screen:
"1. An extremely annoying, inconsiderate person most commonly associated with a Harley rider. 2. A person who owns or frequently rides a Harley"
The episode cuts to the familiar credits.
Implications for the Harley Davidson Brand
This is a complete, unmitigated disaster, for Harley Davidson.
South Park, while on the decline with the general pubic since 1999, has a very strong influence on Millennial through to late Gen X males. It has one of the biggest groups on Facebook (nearly 3 million fans) at the time of writing.
(At the time of writing, Harley has a share price of $25.73).
South Park has a major impact on language. Terms such as "derp" and "three fiddy" continue to be used by this self-referential market segment - years and years after their introduction.
While Harley's current demo is very much geared towards older males, the tainting of the Harley customer is total and complete. Because Parker and Stone started off with a massive insight: that the behavior of Harley drivers is inconsiderate to the extreme, the truth resonates throughout the episode. In fact, the lingering fear that people will be beat up by Bikers is directly referenced in the episode itself. The smearing is made complete with Butters becoming the voice of empathy. (A regular watcher of the show will understand why that, unto itself, is devastating.)
The second implication is that Parker and Stone are calling on Children to actively socially denigrate bikers. Having watched 11 year olds shout "giggity" at the top of the lungs, I can say with some degree of confidence that this could really happen.
Parker and Stone are actively trying to introduce a negative externality into the experience of riding a Harley. They seek to return negative attention and return the favor. This might have their desired impact of making the experience of riding a Harley socially unacceptable, and so allowing all of us to enjoy the peace.
This is a deliberate social experiment directed at the heart of the Harley Brand.
I have good reason to believe that it will be effective in some quarters.
Implications for Language
Marketers really like tag lines that stick out in the head (it helps message recall).
"Where's the Beef" is one example. "I don't always drink beer, but when I do, I prefer Dos Equis" is another.
If you're going to be a social marketer, you have to understand language and context.
What's interesting here is that it's the first time, at least to my knowledge, that the producers of a show have actually tried to force the re-definition of a word.
It's this transposition of a hate word from one group to another that is particularly interesting.
This is an important case study.
Yes - it's just a show. Yes - it's such a hateful word. Yes - there's a lot wrong with it.
I'm incredibly interested in how this experiment goes down. What is the impact of a carefully seeded message, hammered away over a period of 22 minutes, with some 2 to 3 million people watching?
Will the definition actually shift, or will it go down as a failure?
And if so, with such high penetration amongst such a dedicated group of people, what are the implications for social marketing?
The choice of subject matter is unfortunate. I didn't write the experiment and I don't necessarily support it.
Serious social analysts need to sit up and take note.
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 onto the same page, and then I'll write, at length, about the implications for advertisers (Harley in particular) and the implications for social marketing.
The episode starts with a pretty huge insight: the damage that bikers do to communities. In effect, bikers produce a negative externality, the production of a massive amount of noise, to the detriment of all others. (Ever been on a patio in Toronto? Yup - South Park covers that too.)
You can watch the full episode at the link below and follow along. If you don't have the time, a summary follows.
If you want to watch on the Comedy Network, you're looking for South Park, Season 13, Episode 12.
http://www.southparktv.info/season-13/season-13-episode-12
In the beginning, the boys are enjoying a wonderful day outside.
Then they hear that loud noise of the motorcycle.
The motivations of bikers for making such noise is laid bear by Parker and Stone in the subsequent scene. It's all about the need of bikers for attention.
What then follows is the appropriation of the term 'fag' to bikers at 2:28 by Eric Cartman.
The bikers end up being even louder, which prompts the boys to hatch a plan. At 5:43 into the episode, Butters does a nice speech empathizing with the bikers. He's summarily dismissed and the boys plan to take dumps on the bikers seats and to write "go away fags" in a number of places about town.
Predictably, at 8:20 into the episode, Big Gay Al and Mister Slave, two recurring and tolerant characters on the show, are walking down the street and sees these huge words written everywhere.
Outrage ensues and a town meeting is held. The mayor is pissed.
Stan and Kyle take total credit for it.
At 9:20, they remark that the term 'fag' has nothing to do with 'gay people'. In effect, they don't see the relation at all between the term 'fag' and 'gay'.
At 9:40, the bikers retreat the library and to the dictionary. Stone and Parker actually recite the long history of the word fag, and are clearly setting up the next huge act of the show.
At 11:40, the boys are pulled in front of a board, where the adults proceed to try to understand the term. Fag becomes known as "an inconsiderate douchebag".
The boys ask: "Don't you people keep up with today's lingo at all"? (I lolled.)
At 13:00 Big Gay Al goes into an organization to rally behind the boys, supporting the re-definition.
At 14:00 the mayor signs an ordinance making the term permissible and re-defined.
At 15:15, the mayor freaks out and calls the boys into her office, now. Predictably, the progressives are freaked out about the actual term within the dictionary as being pejorative to homosexuals.
At 16:00, the boys solution is that they have to change the dictionary definition so they could be free to call Harley drivers 'fags'.
Predictably, at 16:50, the bikers decide to resort to violence.
At 17:10, South Park welcomes the head dictionary editor in an effort to convince them to change the term.
This sets up the climax.
In a delicious piece of esoteric satire, Emmanuel Lewis is the dictionary editor ("What Choo Talkin' 'bout Lewis?") comes to town. The bikers show up to beat the crap out of everybody, including Emmanuel Lewis.
At 21:30, Stone and Parker make a direct appeal to the audience, breaking the fourth wall, calling upon all children to call all bikers faggots across America. At 22:00, the editor of the dictionary declares the definition.
Kyle walks forward, breaking the fourth wall again, and says, "this day, we've made history".
The new definition of the word 'fag' appears on the screen:
"1. An extremely annoying, inconsiderate person most commonly associated with a Harley rider. 2. A person who owns or frequently rides a Harley"
The episode cuts to the familiar credits.
Implications for the Harley Davidson Brand
This is a complete, unmitigated disaster, for Harley Davidson.
South Park, while on the decline with the general pubic since 1999, has a very strong influence on Millennial through to late Gen X males. It has one of the biggest groups on Facebook (nearly 3 million fans) at the time of writing.
(At the time of writing, Harley has a share price of $25.73).
South Park has a major impact on language. Terms such as "derp" and "three fiddy" continue to be used by this self-referential market segment - years and years after their introduction.
While Harley's current demo is very much geared towards older males, the tainting of the Harley customer is total and complete. Because Parker and Stone started off with a massive insight: that the behavior of Harley drivers is inconsiderate to the extreme, the truth resonates throughout the episode. In fact, the lingering fear that people will be beat up by Bikers is directly referenced in the episode itself. The smearing is made complete with Butters becoming the voice of empathy. (A regular watcher of the show will understand why that, unto itself, is devastating.)
The second implication is that Parker and Stone are calling on Children to actively socially denigrate bikers. Having watched 11 year olds shout "giggity" at the top of the lungs, I can say with some degree of confidence that this could really happen.
Parker and Stone are actively trying to introduce a negative externality into the experience of riding a Harley. They seek to return negative attention and return the favor. This might have their desired impact of making the experience of riding a Harley socially unacceptable, and so allowing all of us to enjoy the peace.
This is a deliberate social experiment directed at the heart of the Harley Brand.
I have good reason to believe that it will be effective in some quarters.
Implications for Language
Marketers really like tag lines that stick out in the head (it helps message recall).
"Where's the Beef" is one example. "I don't always drink beer, but when I do, I prefer Dos Equis" is another.
If you're going to be a social marketer, you have to understand language and context.
What's interesting here is that it's the first time, at least to my knowledge, that the producers of a show have actually tried to force the re-definition of a word.
It's this transposition of a hate word from one group to another that is particularly interesting.
This is an important case study.
Yes - it's just a show. Yes - it's such a hateful word. Yes - there's a lot wrong with it.
I'm incredibly interested in how this experiment goes down. What is the impact of a carefully seeded message, hammered away over a period of 22 minutes, with some 2 to 3 million people watching?
Will the definition actually shift, or will it go down as a failure?
And if so, with such high penetration amongst such a dedicated group of people, what are the implications for social marketing?
The choice of subject matter is unfortunate. I didn't write the experiment and I don't necessarily support it.
Serious social analysts need to sit up and take note.
Monday, November 2, 2009
Analytics as a source of competitive advantage and the Medium
What should the outputs of an analytics program be?
I'll argue the outputs should include: profit, evidence (historical), clarified-concrete-measurable goals, decision support (scenario analysis), forecasts, customer intelligence, and competitive intelligence: all resulting in an expanding base of knowledge and competitive advantage.
I didn't mention mediums in that description.
The medium is both the message and the problem preventing most programs from becoming a source of competitive advantage for their organizations.
We've got some pretty big problems with the mediums.
There's a huge amount of work that's going into moving data from multiple systems into a single system: a process called aggregation.
What's the most common aggregation point?
A spreadsheet. It's excel.
It's a not a very good solution. Usually it isn't semi-automated or effectively QA'd.
I've pushed excel beyond it's natural limit. Even when it's made very pretty and functional it is at best a stop-gap solution.
Excel should be to an analytics practitioner as Visio is to an information architect.
It can be a useful tool to express the model, view, and controller to a tech: but it shouldn't be the platform. It shouldn't be the principle medium through which a practitioner communicates with a huge audience.
I'm expanding on that word: communicates.
Have you ever watched somebody open up an excel spreadsheet? Have you ever watched them consume the data on the page?
Just watch them.
Chances are you see a heavy sigh and a whole lot of squinting. You'll also note that the time spent with the page will vary from just a few seconds to a few minutes (at most).
I've watched others take the spreadsheet and run sums and functions on the data. They're effectively torturing it themselves to make the spreadsheet talk. They're trying to learn something from the data.
Spreadsheets don't teach on their own.
I've done it myself. Once I'm satisfied with understanding what is going on, I immediately jump to finding out why it is going on and how I can improve it.
In figuring out that why, my first instinct is to go to the go-to people and start asking questions. Frequently an hour worth of talking can save a week's worth of digging. Sometimes I need more data - but I know how to phrase a query.
I can report that phrasing a query can be very hard to do and it's seldom done really well.
The memegenerator below demonstrates what happens next.
Humans have a hard time guessing how long it takes to put something together. If it only took somebody a minute to read something - then it must have only taken the analyst ten minutes to put together. (right?)
Excel sheets within any organization proliferate (how secure are all those sheets, anyway?). The result is the perception that they're cheap. And if they're cheap, the demand for MOAR comes far and furious.
But that's the wrong medium. They might scream for more dashboards - but a dashboard can't possibly answer a complex query or tackle a complex problem.
A dashboard doesn't tell anybody why something is happening. It tells them what is going on.
It offers a very small incremental competitive advantage. Sure, they might know MOAR WHAT is going on, but better decisions are made using causality, not knowledge of past state alone.
Analytics becomes a source of spreadsheets instead of a source of competitive advantage.
If Excel is not the right Medium - what is?
I'm arguing that the medium ought to match the objective.
If you are replying to a complex query, a presentation - or dare I even suggest it - an animation/video through visualization ought to be the right medium (GGOBI is free). A complex question typically results in a simple answer that need a long explanation to have face validity.
For instance - if the CFO were to ask the web analyst "what are the traits of our most valuable customers?" - the answer might be simple: "People who buy often and say good things about our products". The story explaining why is just that: a story.
You don't use a spreadsheet for that.
If you are asked for ongoing data so that a manager knows what is happening with their section of the website - then it ought to be a tight dashboard based on clear business goals: tied as closely to how that manager is bonused as possible. That dashboard ought to be in a web based format that is designed for dashboarding. Ideally, the dashboard would have a function that enables self-exploration. (Enter the world of vizualization and democratic access).
There's another reason too:
Inquiries for WHY something is going on naturally lead to demands for MOAR metrics to be added. This means that what is born as a small dashboard of 10 metrics grows into a 111 metric disgrace of a report.
The medium of an excel spreadsheet is simply incapable of keeping up with the wave of human curiosity that is aroused from seeing the surface of the data.
If you believe that the principle output of an analytics program is just data: then the MOAR cycle of metrics is not a problem for you. That's just fine and we have nothing to talk about.
If you believe that the principle output of an analytics program is competitive advantage for a firm: the mediums we use as practitioners must shift. If you agree with me - then we have a lot to talk about.
I'll argue the outputs should include: profit, evidence (historical), clarified-concrete-measurable goals, decision support (scenario analysis), forecasts, customer intelligence, and competitive intelligence: all resulting in an expanding base of knowledge and competitive advantage.
I didn't mention mediums in that description.
The medium is both the message and the problem preventing most programs from becoming a source of competitive advantage for their organizations.
We've got some pretty big problems with the mediums.
There's a huge amount of work that's going into moving data from multiple systems into a single system: a process called aggregation.
What's the most common aggregation point?
A spreadsheet. It's excel.
It's a not a very good solution. Usually it isn't semi-automated or effectively QA'd.
I've pushed excel beyond it's natural limit. Even when it's made very pretty and functional it is at best a stop-gap solution.
Excel should be to an analytics practitioner as Visio is to an information architect.
It can be a useful tool to express the model, view, and controller to a tech: but it shouldn't be the platform. It shouldn't be the principle medium through which a practitioner communicates with a huge audience.
I'm expanding on that word: communicates.
Have you ever watched somebody open up an excel spreadsheet? Have you ever watched them consume the data on the page?
Just watch them.
Chances are you see a heavy sigh and a whole lot of squinting. You'll also note that the time spent with the page will vary from just a few seconds to a few minutes (at most).
I've watched others take the spreadsheet and run sums and functions on the data. They're effectively torturing it themselves to make the spreadsheet talk. They're trying to learn something from the data.
Spreadsheets don't teach on their own.
I've done it myself. Once I'm satisfied with understanding what is going on, I immediately jump to finding out why it is going on and how I can improve it.
In figuring out that why, my first instinct is to go to the go-to people and start asking questions. Frequently an hour worth of talking can save a week's worth of digging. Sometimes I need more data - but I know how to phrase a query.
I can report that phrasing a query can be very hard to do and it's seldom done really well.
The memegenerator below demonstrates what happens next.
Humans have a hard time guessing how long it takes to put something together. If it only took somebody a minute to read something - then it must have only taken the analyst ten minutes to put together. (right?)
Excel sheets within any organization proliferate (how secure are all those sheets, anyway?). The result is the perception that they're cheap. And if they're cheap, the demand for MOAR comes far and furious.
But that's the wrong medium. They might scream for more dashboards - but a dashboard can't possibly answer a complex query or tackle a complex problem.
A dashboard doesn't tell anybody why something is happening. It tells them what is going on.
It offers a very small incremental competitive advantage. Sure, they might know MOAR WHAT is going on, but better decisions are made using causality, not knowledge of past state alone.
Analytics becomes a source of spreadsheets instead of a source of competitive advantage.
If Excel is not the right Medium - what is?
I'm arguing that the medium ought to match the objective.
If you are replying to a complex query, a presentation - or dare I even suggest it - an animation/video through visualization ought to be the right medium (GGOBI is free). A complex question typically results in a simple answer that need a long explanation to have face validity.
For instance - if the CFO were to ask the web analyst "what are the traits of our most valuable customers?" - the answer might be simple: "People who buy often and say good things about our products". The story explaining why is just that: a story.
You don't use a spreadsheet for that.
If you are asked for ongoing data so that a manager knows what is happening with their section of the website - then it ought to be a tight dashboard based on clear business goals: tied as closely to how that manager is bonused as possible. That dashboard ought to be in a web based format that is designed for dashboarding. Ideally, the dashboard would have a function that enables self-exploration. (Enter the world of vizualization and democratic access).
There's another reason too:
Inquiries for WHY something is going on naturally lead to demands for MOAR metrics to be added. This means that what is born as a small dashboard of 10 metrics grows into a 111 metric disgrace of a report.
The medium of an excel spreadsheet is simply incapable of keeping up with the wave of human curiosity that is aroused from seeing the surface of the data.
If you believe that the principle output of an analytics program is just data: then the MOAR cycle of metrics is not a problem for you. That's just fine and we have nothing to talk about.
If you believe that the principle output of an analytics program is competitive advantage for a firm: the mediums we use as practitioners must shift. If you agree with me - then we have a lot to talk about.
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