Month: July 2009

Analyst: creative or canned?

I picked up the term “creative analyst” in late June on the phone with Lyzasoft CEO Scott Davis. But what does he mean?

He described one analyst he’s known of. This guy arrived at a new job with strong recommendations for his ability to tear apart a dataset. He could slice, dice, build related charts and pivot tables — but only with canned data. That is, data someone had given him. This analyst struggled with synthesis — blending separate datasets, for example, or making a formula to derive values, or simply experimenting and asking unforeseen questions.

The ability to improvise and create something new is a “prime differentiator” among analysts, says Davis.

Many of these creative, synthesizing analysts, he says, also tend to feel they have a personal brand. They have a style of charting they prefer, for example, and they produce a distinct set of information that is uniquely attractive to their subscribers within the company.

“You can sort of think of them as publishers,” he says. “They create these things that are in some ways more useful than reports from the BI tool. And they gauge their effectiveness by how many people follow them.”

Such lists have been around quite a while. Before PCs, people did the same kind of thing in hardcopy, producing a dozen or two binders with a distribution list clipped on the cover.

There’s a future, too. Davis expects to see Enterprise 2.0 — social networking within businesses — grow fastest among these analysts. They already have the social habits: commenting, trust, wikis, etc.

He says, “A spreadmart is nothing but a primitive social networking mechanism.”

Analysts run on “maker’s schedule”

Most of those versatile researchers of the data-driven world — the business analysts, creative analysts, or even cowboy analysts — probably run on a different schedule from their managers. Paul Graham’s latest essay compares “manager’s schedule” and “maker’s schedule.”

I’m no analyst, just a writer. But the more analysts I meet, the more I find that analysts and journalists share a surprising number of characteristics. One of them, I think, is the tendency to run on “maker’s schedule,” as explained by Graham:

When you’re operating on the maker’s schedule, meetings are a disaster. A single meeting can blow a whole afternoon, by breaking it into two pieces each too small to do anything hard in. Plus you have to remember to go to the meeting.

Meetings are interruptions. They mess up any breadcrumb trail of thoughts that has not yet been laid down in permanent memory. That’s why I’m writing this at 11:39 at night, when I can let a ghost of an idea hang unattended without fear of new email or a phone call dissolving it. Graham writes about once keeping a dinner-to-3 a.m. workday.

Now he wears a VC hat, and he can’t avoid meetings. So he schedules “office hours” at the end of the day.

He hopes that pointing out the two kinds of schedule will make it easier for the “makers.” Their schedule tends to offend managers.

I hope this insight spreads.

What do you think? Do analysts you know work this way? Post a comment.

Magic number

Establishing trust is the key for one analyst I talked today at the Tableau conference. Two years ago his career took him to a small, private university where he had to win over a few well-established administrators. They were to provide him data and be his clients.

The key to trust for them was what he now calls “the magic number.” Sure, they gave him some of their data. But they didn’t tell him they were testing him. When he came back with his analysis, they looked for that magic number. If it turned up — that is, if his data showed what they had learned from experience — they relaxed a little.

It fits somehow that he has a Ph.D in psychology.

Two analysts’ paths

Yesterday I asked business analysts at the Tableau conference in Seattle about their work. Here are two quick sketches.

• One of the two arrived at her present employer six years ago to do the company’s first analysis of its website sales. She used several years of accumulated data to show which content was making money and which wasn’t. When she had organized the job into a routine, she handed it off to someone else and moved to the next question: What parts of the marketing was working? Again, she worked it into a routine and gave the task away. Next: what were visitors doing on the site? And now she has begun to answer similar questions for the company’s new site.

Not long ago, she was put into the IT group, among a bunch of guys coding in Java and doing other work she knows little about. She flashes a grimace at the mention.

She worries about her career. “How would I market this?” she asks.

• Another analyst was practically a librarian 15 years ago. People from other departments told him what reports they wanted — for example, SEC filings — and he delivered. Then some people asked for summaries, which made him think about other ways he could add value.

At some point, the value-adding incorporated data analysis, which grew. For years, he was the only analyst, but now he manages four others.

He’s the bridge between the data-generating IT department and the data-craving marketing department. He seems unconcerned about his career.

Complete versions may come next week.

Blog for the times: on high-value, low-cost BI

Dan Murray expects to take another step this week in his thrilling rebellion, spreading the word on high value, low cost BI.

Though it’s a rebellion and may burn with Che Guevara-type zeal, Dan’s methods actually lean way over toward Darwinian evolution. Revolution is expensive and risky, he writes, while evolution is intelligent and incremental. He also likes to point out that Che died brutally at 39 and Darwin died at 73 in bed with family around him.

First, people have to learn the basics, that tough work to create a data warehouse. His rebellion does it with Tableau, spreadsheets and a little guidance.

He’s a busy guy. This week, he’s also speaking at the Tableau Customer Conference in Seattle. He is also COO of Interworks, Inc.

I’ll post the address when I get it.