Saturday, May 19, 2012

Is Pete Fader right that Big Data doesn't imply big money?

He's right, in that Big Data doesn't necessarily lead to big money, but I think he exaggerates for pedagogical effect. Why he feels the need to do so is instructive, especially for Big Data acolytes.

Some days ago there was agitation in the Big Data sociosphere when an interview by Wharton marketing professor Peter Fader questioned the value of Big Data. In The Tech, Fader says
[The hype around Big Data] reminds me a lot of what was going on 15 years ago with CRM (customer relationship management). Back then, the idea was "Wow, we can start collecting all these different transactions and data, and then, boy, think of all the predictions we will be able to make." But ask anyone today what comes to mind when you say "CRM," and you'll hear "frustration," "disaster," "expensive," and "out of control." It turned out to be a great big IT wild-goose chase. And I'm afraid we're heading down the same road with Big Data. [Emphasis added.]
I think Pete's big point is correct, that Big Data by itself (to be understood as: including the computer science and the data analysis tools, not just the data -- hence the capitalization of "Big Data") is not sufficient for Big Money. I think that he's underestimating, for pedagogical effect, the role that Big Data with the application of appropriate business knowledge can have in changing the way we do marketing and the sources of value for customers (that is both the job of marketer and the foundations of business).

This is something I've blogged about before.

So, why make a point that seems fairly obvious (domain knowledge is important, not just data processing skills), and especially why make it so pointedly in a field that is full of strong personalities?

First, since a lot of people working in Big Data don't know technical marketing, they keep reinventing and rediscovering old techniques. Not only is this a duplication of work, it also ignores all knowledge of these techniques' limitations, which has been developed by marketers.

As an example of marketing knowledge that keeps being reinvented, Pete talks about the discovery of Recency-Frequency-Money in direct marketing,
The "R" part is the most interesting, because it wasn't obvious that recency, or the time of the last transaction, should even belong in the triumvirate of key measures, much less be first on the list.*    [...]
Some of those old models are really phenomenal, even today. Ask anyone in direct marketing about RFM, and they'll say, "Tell me something I don't know." But ask anyone in e-commerce, and they probably won't know what you're talking about. Or they will use a lot of Big Data and end up rediscovering the RFM wheel—and that wheel might not run quite as smoothly as the original one.

Second, some of the more famous applications of machine learning, for example the Netflix prize and computers beating humans at chess, in fact corroborate the importance of field-specific knowledge. (In other words, that which many Big Data advocates seem to believe is not important, at least as far as marketing is concerned.)

Deep Blue, the specialized chess-playing computer that defeated Kasparov, had large chess-specific pattern-matching and evaluation modules; and as for the Netflix prize, I think Isomorphismes's comment says all:
The winning BellKor/Pragmatic Chaos teams implemented ensemble methods with something like 112 techniques smushed together. You know how many of those the Netflix team implemented? Exactly two: RBM’s and SVD.    [...] 
Domain knowledge trumps statistical sophistication. This has always been the case in the recommendation engines I’ve done for clients. We spend most of our time trying to understand the space of your customers’ preferences — the cells, the topology, the metric, common-sense bounds, and so on.

Third, many people who don't know any technical marketing tools continuously disparage marketing (and its professionals), and some do so from positions of authority and leadership. That disparagement, repeated and amplified by me-too retweets and Quora upvotes, is what makes reasonable people feel the need for pointedly making their points.

Here are two paraphrased tweets by people in the Big Data sociosphere; I paraphrased them so that the authors cannot be identified with a simple search, because my objective is not to attack them but rather illustrate a more widespread attitude:
It's time marketing stopped being based on ZIP codes. (Tweeted by a principal in an analytics firm.)
Someone should write a paper on how what matters to marketing is behavior not demographics. (Tweeted by someone who writes good posts on other topics.)
To anyone who knows basic marketing, these tweets are like a kid telling a professional pianist that "we need to start playing piano with all fingers, not just the index fingers" and "it's possible to play things other than 'chopsticks' on the piano." (Both demographics and ZIP codes have been superseded by better targeting approaches many decades ago.)

These tweets reflect a sadly common attitude of Big Data people trained in computer science or statistics: that the field of marketing cannot possibly be serious, since it's not computer science or statistics. This attitude in turn extends to each of these fields: many computer scientists dismiss statistics as something irrelevant given enough data and many statisticians dismiss computer scientists as just programmers.

That's a pernicious attitude: that what has been known by others isn't worth of consideration, because we have a shiny new tool. That attitude needs deflating and that's what Pete's piece does.

-- -- -- --

* An explanation of the importance of recency is that it's a proxy  for "this client is still in a relationship with our firm." There's a paper by Schmittlein, Morrison, and Colombo, "Counting your customers," Management Science, v33n1 (1987), that develops a model of market activity using a two-state model:  the purchases are Poisson with unknown $\lambda$ in one of the states (active) and there's an unobserved probability of switching to the other state (inactive), which is absorbing and has no purchases. Under some reasonable assumptions, they show that recency increases the probability that the consumer is in the active state. BTW, I'm pretty sure that it was Pete Fader who told me about this paper, about ten years or so ago.

Friday, May 11, 2012

A tale of two colloquia

It was the best of talks, it was the worst of talks.

(Yes, I understand that Dickens's opener has been used to the cliché limit; but the two examples I have in mind really bracket the space of possible talks. At least those talks with voluntary attendance.)

The best of talks: Michael Tilson Thomas at TED.

Even if you don't like art music, this talk is well worth watching for the presentation skills demonstrated by MTT:

MTT opens with a personal story of an interesting coincidence (his father's name was Ted); this is not my preferred type of opener, but he builds a personal narrative out of that opener and then merges it with his main topic very well.

MTT sits at a baby grand piano, which he occasionally plays to illustrate points about music evolution. This interactive production of the presentation material, similar to writing and running code or analyzing data in a technical presentation, has three main presentation advantages that make up for its risks:

1. Visual and physical variety, or more generally, presentation process variety. Every few seconds the image changes, the activity changes, the type of presentation changes: speaking, playing piano, describing a photo, narrating a video, watching a video without narration, listening to recorded music. Compare that with 18 minutes of speaking to slides bearing bullet points.

2. Clear demonstration of expertise, which projecting a video or playing recorded music  cannot do. In a live demonstration or performance there's always a risk that something will go wrong, which is why many presenters avoid this kind of demonstration. But the willingness to take that risk is a strong signal to the audience of the presenter's competence and expertise.

3. Adaptability (not really used by MTT, since his was not a talk with audience interaction). This is particularly important in teaching technical material, I think: allowing the students to ask questions and see the answers come from the techniques that we're teaching them is a lot better than just showing them slides. (Of course real learning happens when the students do the work themselves, but this kind of demonstration helps begin the process and motivates them to act.)

The supporting materials were superbly chosen and executed. Credit here is due to a large supporting cast for MTT: this presentation uses materials and skills from the education and multi-media presence of the San Francisco Symphony, an organization whose main business is performing. But here are five important lessons that these materials illustrate:

1. No bullet points, and few words (mostly as subtitles for foreign language). The projected materials (including a large camera shot of MTT when no other materials are using the screen) are there to support what MTT is saying, not to remind MTT of what he wants to say.

2. The production values of the materials are professional (you can assess their quality on the 720p video) and that signals that this presentation is important to MTT, not something put together in the flight down, between checking email and imbibing airline liquor.

3. MTT's presentation never mentions the support, only the content: he doesn't say "this slide shows a photo of my father," he tells the story of discussing music with his father as the photo appears on screen. The photo is a support for the narrative instead of the narrative taking a detour to acknowledge the technology and the specifics of the material that is supporting it.

4. The interaction between materials, speech, and piano playing was choreographed in advance, with the video producer knowing which shots to use at each time. This comes from the extensive documentary and educational work of the San Francisco Symphony under MTT, but to some extent can be replicated by presenters of more technical material if they take the time to think of their presentation as a series of "cuts" in a video production.

5. It's not on the video, but it's obvious from the fluidity of the speaking, piano playing, and video materials that this talk was carefully planned and thoroughly rehearsed. That's not surprising: after all, a dress rehearsal is nothing new to a performing artist, and MTT clearly saw this talk as a performance. Most presenters would benefit from seeing their talks as performances (once they get the content part well taken care of, obviously).

The speech was well structured, with a strong opener and closer, repetition of the key points with different phrasing at the bridge points, and with the right mix of entertainment and education that is expected of a TED talk.

MTT had a teleprompter at his feet and notes on top of the piano, which in the video appear to include a couple of lines of music score, possibly as a reminder of the harmonic evolution he demonstrates at timecode 5:28 to 6:02. Many presenters are afraid that using speaker notes makes them look unprepared or "just reading their speech." This is an erroneous attitude for five reasons:

1. Expertise can be demonstrated in different ways, like MTT playing the piano. And as a general rule, the audience will have some idea of the expertise of the presenter, established ahead of time by other means.

2. Open discussion or question and answer periods allow the speaker to wow the audience with his or her ability to extemporize. (As a general rule, I suggest speakers prepare notes on some of the more likely questions that may need some thinking ahead, but not read them verbatim.)

3. Reading a speech is a difficult skill; most people can't do it correctly. Even when I write a speech for myself, I find that I also make notations on it and end up using it more as a psychological crutch than an actual speech to read. It's fairly obvious that MTT is not reading the speech verbatim.

4. Even if MTT is partially reading a prepared speech, it's most likely one that he had a big input in writing. Other than celebrities, politicians, and CEOs, most presenters will have written their speeches, and most audiences will expect that they did.

5. Ironically, many people who look down on unobtrusive speaker notes or teleprompters put their speaker notes on the screen as bullet points, confusing the materials that are there to help the speaker (notes) with the materials that are there to help the audience process the presentation (visual support).

The material MTT covers meshes with music history so he uses stories and storytelling as the main text form. Stories are one of the six tools for memorability the Heath brothers recommend in the book Made To Stick, and they work very well here. MTT also uses what Edward Tufte calls the P-G-P approach to exposition, presenting a Particular case first, then making a General point, then capstoning that point with another Particular example.

Dancing and singing aren't common techniques in presentations, but MTT uses them to great effect at timecode 2:24. In other presentations some acting or character impressions can be used for the same purpose: break the solemnity of the occasion, signal that you take the subject seriously but you don't take yourself too seriously, or to bridge topics.

(On a video that's no longer available online, John Cleese of Monty Python keeps interrupting his own presentation on creativity techniques with "How many X does it take to change a light bulb" jokes, as a way to give the audience breaks. And those jokes are part of a running arc that he established at the beginning of "there's no real training for creativity so I might as well spend my time telling jokes.")

Personally I don't recommend singing, dancing, or telling jokes in a talk unless you are a professional singer, dancer, or comedian, and even so only sparingly. Note that MTT did it for a very specific and memorable point: that a "piece of 18th Century Austrian aristocratic entertainment" turned into the "victory crow of [a] New York kid," and that's the atemporal power of music.

And as a closer, MTT rehashes the opening theme "what and how" and adds a cornerstone "why," ending on a good note and high energy. It's always important to have a strong closer, almost as important as a good opener.

Two minor observations:

1. MTT should have had a sip of water right before the talk and sloshed it around his mouth and lips, to avoid that smacking sound when he speaks. That sound is created by dryish areas in the mouth letting go at inappropriate times; sloshing the water solves it, drinking doesn't.

2. I assume that MTT's fleece was chosen to match his clothes and accessories, but he could have one custom-made in that color with the logo of the San Francisco Symphony. Maybe this is my crass commercialism rearing its ugly head, but with not flaunt the brand?

The worst of talks: a presenter who will remain anonymous at an undisclosed conference.

For clarity of exposition I'll call the presenter EF, for "Epic Fail," and use the pronoun "he" without loss of generality over gender.

EF started his presentation with a classic: computer trouble.

EF's talk was the last in a four-talk session; the other three presenters had installed their presentations in the podium computer during the break before the session, but EF did not. An alternative to using the podium computer would be to connect his laptop and test the setup during the pre-session break. A third possibility would be to connect his computer while the previous presenter was taking questions from the audience; personally I find this disruptive and avoid it, but it's better than what happened.

And what happened was that after four minutes of failed attempts to connect his computer to the podium (out of a total time per speaker of twenty minutes, including the Q&A period), EF asked the audience for a flash drive so he could transfer his presentation to the podium computer.

Presentation starts after six minutes of unnecessary computer-related entropy.

The room where this happened was an executive education classroom, with U-shaped seating, two projection screens side-by-side at the front and large flat screen TVs on the side walls so that the people on the straight part of the U could look at them instead of the front screens. These TVs also serve as a way for the presenter to see what's on screen while looking towards the audience.

Which is why everyone was puzzled when EF walked to one side of the front screens, turned his back to the audience and started talking in a monotone, while -- apparently -- clicking the remote at random. Really: he moved his slides up and down apparently at random and at high speed, maybe one-second on screen per slide, and without any connection to what he was saying.

But that's fine, because what he was saying was also disconnected within itself. In fact, I don't think he had any idea -- let alone a clear idea -- of what he wanted the audience to take away from the talk.

As far as I could gather, from reading the abstract about four times until I made some sense of it by writing a modal logic model of the essential words therein and crossing the 90% of words that were filler: there's a well-established phenomenon that is observable in a series of measures $X(p)$ as we vary the parameter $p$. The presentation was about changing the parameter space from $P_1$ to $P_2$, with $P_1 \subset P_2$. All tests in the literature concern themselves with the effects measured in $P_1$, and this paper tests the effects in $P_2$. This was not clear in the abstract or the presentation.

One of the slides that was on-screen several times, for about 4 seconds at a time, showed a table with the results from the literature, that is $X(p), p\in P_1$. Every time EF wanted to say something about these results, he moved several slides up and down, looking for the bullet point he wanted -- a point about the table that he had therefore removed from the screen. But that's not the worst.

After spending ten minutes explaining to an audience of experts in the subject matter a well-known point in the field of their expertise, EF glossed over details of his measurement technique, experimental procedure, and data processing, and presented his table of $X(p), p\in P_2$.

Without the $X(p), p\in P_1$ values for comparison.

Let me repeat that: he presented his results, which are to be compared and contrasted to the established results, on a separate table. Now, the phenomenon is well-established, but this is a table of numbers with three or four significant digits, so the details aren't that easy to recall. They are even harder to recall when EF keeps changing slides to look for bullet points about this table, again removing the table from the screen. Let me also point out that these are about 12 rows of 2 numbers per row, 4 with the comparison, well within the capacity of a one-slide table.

Every so often EF would stop abruptly in the middle of a sentence and silently move his slides up and down looking for something, then start a whole new sentence, without stopping the up-and-down movement of the slides.

But the clincher, the payoff after this painful exercise?

EF had no conclusions. His team was still analyzing the data, but so far it appeared that there was no change at all from the well-established phenomenon.

Now, in many fields, showing that a well-established phenomenon applies beyond the boundaries of the previous experiments is a valuable contribution. But in this case the expansion from $P_1$ to $P_2$ was trivial at best.

At this point, and about four minutes over time, EF invited the audience to ask questions. There were no takers, so EF asked one of the audience members (presumably an acquaintance) what he thought of some minor detail that EF had actually not talked about. The audience member said something noncommittal, and EF pressed the point, trying to get a discussion going. The rest of the audience was packed and ready to leave, but EF paid them as much attention during this failed attempt at a dialog as he had during his failed attempt at a presentation.

I was told later by another attendee that this presentation was not atypical for EF.

(Suggestions for improvement? I wrote a post about preparing presentations before.)

Coda: An unfair comparison, perhaps?

MTT is a performing artist, a showman by profession. The presentation he delivered was designed by a support team of graphic artists, cinematographers, writers: it fits within the education efforts of the San Francisco Symphony. MTT's audience is mostly there for entertainment and positively predisposed towards the celebrity presenter. His material is naturally multi-media, interactive, and pleasant, requiring very little effort on the audience part to process it. And, let's not forget, the presentation event itself was a team effort -- MTT is not operating the video screen or the teleprompter at his feet.

EF is a researcher and a professor. His presentation was designed by him, an untrained presenter (obvious from the talk), and delivered to an academic audience: hard to impress, critical, and possibly even hostile. His material is technical, dry, and requires significant effort (even in the best circumstances) to process and follow. He didn't have a teleprompter (though he could have speaker notes had he chosen to) nor a presentation support team.

So, yes, it seems that I'm being unfair in my comparison.

Except that there were, in that very same conference, three keynote speakers with equally dry, non-multimedia, hard to process material, who did a great job. They varied a lot in style and delivery but all made their points clear and memorable, kept their presentations moving along, and didn't use their projected materials as a crutch.

Above all, they had something interesting and important to say, they knew precisely what it was, and they made sure the audience understood it.