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Data served direct-to-exec with Napkyn

We’ve heard about shortage of data-analysis help, and about senior execs who pooh-pooh the influence of analysis in decision-making, and about the “dead” self-service analysis. So when a vendor tells me about a direct-to-exec service, featuring a sort of concierge of analytics, I pull up a chair to listen.

Napkyn, five years old last month and major brands under its belt, assigns a senior analyst to lead a long-term relationship with one executive. Behind the analyst stands a 13-person team that collaborates on the exec’s behalf, putting forward experts as needed. One team member, for example, has 15 years’ experience in multi-variate testing. The CEO and founder, Jim Cain, comes with 15 years in marketing-data alignment.

Cain explains that it all began as a response to a gap he saw: execs’ inability to find answers in the data analysis tools they had, and their inability to hire people who could help. “It’s impossible,” he said, “to hire people in a discipline that’s no older than a first grader.”

He sketched his idea on a napkin and capitalized Napkyn with a $10,000 severance check, and then spent the first five years “aggressively bootstrapping.” It has served 40 major brands, he says, and now has 15 current clients.

The service runs on a flat fee with no overages — which made me wonder how they protect themselves from unreasonable demands? He says it took time to learn how. In the first few years, they worked with anyone who wanted the service, which apparently attracted some who just weren’t ready. “It’s hard to keep the interest of someone who wears too many hats,” he says. That sounds like some people I know, but that’s a long dark hallway I’ll look into another time.

Now Napkyn concentrates on “tier-one brands,” $10 million-plus organizations and only vice president and up. “They have the experience to know what they want and what to do with it.”

Napkyn also protects itself, he says, by “earning the right” to say no. “We earn the right with senior stakeholders. ‘You’ve asked for five things and we only have time for two.'” Deferring to later is usually a better option.

From the start, the lead analyst wants to know what the exec cares about most. The first question is, “What do you care about? What answers can’t you get and complain about to someone close to you?” From there, the Napkyn analyst plugs in with people below to find the data and the answers. He described the role as “half bartender and half mathematician.”

I suppose the lead analyst is something like what Wayne Eckerson, author of Secrets of Analytical Leaders: Insights from Information Insiders, would call a “purple person.” This is the person in the middle, the non-specialist who’s neither business blue nor IT red and who empathizes with both sides.

I’ve always liked those roles, but not many others seem to. Napkyn analysts get more training in asking questions, Cain says, than in running analysis tools or in complex implementation.

At first, the reaction within the organization is a little bit “Sharks and Jets,” he says, referring to the “West Side Story” street-gang drama. But sooner or later people realize that Napkyn is an asset. Their presence tends to change ways people use information and agreeing what things mean. He says, “Getting organizations to align is surprisingly disruptive. We don’t do it with technology.”

“We’re kind of the KPMG of measurement,” says Cain. When the organization uses Napkyn, “everybody can assume that the information the exec gets is accurate and not biased.” Cain says it’s one of the benefits of a direct path to the top stakeholder mediated by senior analytics people.

Wait, does the analyst have a pistol under the napkin? Does he really exude such adult presence?

Pistol or not, it’s a service to watch.

Men in the middle see both sides of the IT-business split

The in-between people see it all from their position between IT and business users. Wayne Eckerson calls them the “purple people” because they’re half IT red and half business blue, and others might call them just con artists. By either name, they see more than the purebreds.

Today at the sixth Tableau Customer Conference, just upwind from Washington D.C, I ran into two men in such roles.

They appear in one set of clothes when facing the information technology people. Then in an instant they turn around to appear in other clothes to business people. They win the confidence of both. Read more

BI’s “promised land”: bigger than tech

At first glance, this pair of tweets last week sounds like a version of BI’s traditional campfire song:

I’ve seen the promised (BI) land, and we are there: databases that fly and process any data; BI tools that are easy to use and fast. Wow! I’d retire but mainstream firms will take 10 years to capitalize on all the new technology & overcome dirty data & politics.

The refrain might go, “When tools fly, they will fly by themselves!” Other lines would caution us to update often, eliminate “politics,” and eat our carrots.

Read more

The future of BI in two words

What’s the future of BI? Last fall, one sharp source of mine answered, “Two words: Tableau and QlikView. You didn’t hear it here.”

Those are startling words coming from that source, a well-regarded BI consultant known for big-name clients and their big deployments.

At about the same time, a column of mine appeared in Information Management titled “Don’t call it BI” — in which I mentioned Tableau and a few smaller tools. A reader emailed, “You should also become familiar with QlikView.”

My many Tableau-using friends say QlikView is hardly worth a look. Poor visualization! Control panels! Scripting! “It’s so — yesterday,” one emails.

It’s “yesterday” to some yet it’s the future to others. It’s time for a look.

Both Tableau and QlikView promise the same magic: Listen to one pitch and you might think that you’re listening to the other. Each sets itself up against traditional, big-iron BI. Each claims to empower business users by giving them all the data and control they need for free discovery. Each is easy to use. Go inside each tent, though, and you see how different they are.

Metaphorically speaking, Tableau is West Coast. It’s built for discovery by the individual. Just show up and ride on the breeze, the demos seem to say, free as a seed fairy on a meadow. The inevitable mistakes of discovery are quickly undone and forgotten. Create the most dazzling visualizations — “vizzes” — thanks to built-in best practices that nudge you toward beauty and punch.

One of the most attractive aspects is users’ effervescence. They seem to be riding on the wind and solving business problems all at once. Their rapture sweeps me away every time I’m near it.

If Tableau is West Coast, QlikView is East Coast. Its community is bigger, the third-party add-ons are more plentiful, support seems more available, and overall workflow feels more structured. It too is built for discovery, but it’s discovery rooted in community. The “associative experience” reveals relevant data, and you can create your own views and in quick succession ask any questions, anticipated or not. But unless you’re working alone, someone else probably defined the data and its structure for you. This is QlikView’s counterpart to Tableau’s meadow, though it’s more like a manicured garden than Tableau’s unfenced field of daisies.

QlikView’s boundaries may be more apparent than Tableau’s, but I suspect that there’s at least as much power there. I just haven’t yet been able to judge it for myself well enough.

The trouble for me is that I’ve used it alone, as if stuck in a remote cabin. Though even Thoreau might have liked the “associative experience,” QlikView really comes alive only when you link to others.

As in Tableau, any QlikView user can create or modify a workspace, a document linked to one or more sets of data with any number of displays. Unlike Tableau, QlikView isn’t so finicky about data; for one thing, linking to Excel spreadsheets is easier.

I can’t speak with assurance just yet on the differences between QlikView and Tableau Server — more on that later — though I think I see a QlikView edge there.

One other advantage for QlikView is clear: built-in collaboration. True, Tableau workbooks can be passed around in a variety of ways forever. But as with our atomized life on the West Coast, such a community would be for me, the hypothetical manager of a group, too loose for comfort.

Tableau users will shudder, as if about to be extradited back to Maine. “Great, central authority all over again,” they would say. Yet when I imagine myself managing a group, I would feel disabled without a tight, integrated social structure.

“It’s the soft stuff that matters,” TechTarget research director Wayne Eckerson likes to say. Such stuff is what interests me more than anything: Who are these people and how did they choose what they did?

Have most Qlik or Tableau users chosen their tool the way most of us choose spouses, religion, and politics — guided by our relationships? How many software shoppers qualified their candidates with lists of requirements and features and followed through based on evidence? Did they do what a veteran sales person at a large BI vendor sees?: “They gather requirements, they issue RFPs, they visit trade shows, they talk to vendors, and ultimately they pick one because they like its color.”

I think it’s usually about “color,” color being the cover story for something most people can’t quite describe. For now, though, I’m happy to say that at least my first question has been answered: Yes, QlikView belonged on that list in “Don’t call it BI.”

Big BI and the ladder man to come calling at the Tableau conference

Howard Dresner is a celebrity in the business intelligence industry, but most people at last year’s Tableau conference didn’t even recognize him when he showed up there.

Who needs BI? Tableau Software liked to think it had left BI behind. BI people, after all, were the control freaks who denied access to data. They sneered at Tableau’s “pretty pictures.” They cared more about data hygiene than data analysis.

But there he was. Stephen Few spotted him in the audience a few minutes into his keynote and paused to wonder if it was really him. Tableau vice president of marketing Elissa Fink welcomed him. I and some others said hello. Mostly he wandered alone.

But he’s coming back this year — to speak. He’ll be among 10 on the “experts track” at the Tableau Customer Conference in Las Vegas. Others include BI veteran Claudia Imhoff, Cindi Howson of “BI Scorecard,” and Performance Dashboards author Wayne Eckerson.

They’re all worth listening to. But the one most Tableau people would feel at home with is Paul Kedrosky. Unlike the others, he’s not from the BI world at all. He’s an “investor, speaker, writer, media guy, and entrepreneur,” according to his blog’s “about” page. But I know him as the man who counts ladders.

At last fall’s Defrag conference in Boulder, he told about using the California Highway Patrol’s count of fallen ladders on freeways as a leading economic indicator. Who says data must come from conventional sources? He’s serious and creative, a mix Tableau people appreciate.

He’s written that we live in a “golden age of data visualization,” but I’ve found no elaboration. I’ll be listening for that.

As for the other nine “experts,” the first thing I’ll look for is the size of their audiences.