In the rebellion of the business users, in which top-down gets tipped over, even stodgy old project management is coming alive.

“Most of the decisions made in project management,” says Liquid Planner CEO Charles Seybold, “happen under the surface.” He’s now trying to win over the people who work on projects but haven’t run many of them. He’s using transparency and collaboration.

Liquid Planner, the cloud-based insurgent — “a Wikipedia for projects” — has its roots in Seybold’s experience organizing Expedia’s first project management office. Every time the 40 or so projects under his watch got rolled up, he says, there was “a new distortion of reality.” He had become frustrated with the usual tools. Finally, he and his team decided they had to start over.

Today, Liquid Planner discards a lot of project management fixtures, such as fixed start and finish dates. In their place, it uses ranges and “probabilistic scheduling.” That’s actually how people think, isn’t it? Other old habits are “percent complete” and “earned value,” both of which I’ve found laughable.

The tool also doesn’t allow overloading, by which team members are booked for more than 100 percent of their time. And the tool forces decisions on priority, making just one thing a first priority and not several.

Liquid Planner fights cynicism and standoffs with transparency. In a typical project, team members provide data — such as estimates, actual hours worked, re-estimates, and risk assessments — to a project manager, who a week or two later issues a schedule that can’t be traced back to the raw data. Hidden within that opaque but official schedule are broad assumptions about risk and uncertainty.

Team members have lost control but are still held responsible. So they respond however they can, he says, typically with covert adjustments within each one’s area. Team members and project managers then get locked in a hostile negotiation in which neither side can safely share information.

Seybold often hears from project managers who really don’t think team members should have a say. “Way too many [project managers] act like keeping team members in the dark is the right thing,” he says. “We hear this when people ask us to obscure and lock down information that, as far as we can tell, can only benefit team members.”

He’s busy now working on an iPad app, which he wants to make as functional as the cloud-based application. He’d like to see project managers be “100 percent mobile.”

Search all the business literature you can and you’ll never find data analysis compared to romantic love. But, hey, why not? Love’s trajectories might hint at what the business world’s newly enabled generation of data analysts can expect.

These data analysts tend to be independent, are often creative and at least partly self-trained. They’re strapped to rockets from Tableau, Lyzasoft, Predixion, and others, tools that are at first deceptively toy-like. Aren’t they analogous to the garden variety teenager? Bothg groups revel in newly discovered tools, while both pursuits are fundamentally social — as Lyzasoft CEO Scott Davis observes about data analysis. His blog post got me thinking about this.

Everyone shows up ready to rumble. They’re fascinated with the possibilities, they experiment in private, later they have a blush of quick results followed by a long trail of self-training on finer points.

Each group’s toolset is potent and designed for early success but never early mastery. They make lots of mistakes. In love and analysis, people fall for the wrong data, mess up good data and dates, do all kinds of things they wish they hadn’t.

Without realizing, they face danger. I’ve noticed that behind most good trends comes a rotten sibling right behind it. Think of the history of other social events: Hippies begat the Summer of Love and then came Altamont. We celebrated “free love” and then came a surge of sexually transmitted diseases. Baseball begat the World Series and then came batters on steroids. PageMaker begat self-publishing but then came the ugliest lost-cat posters ever tacked on a telephone pole.

You may already wish that bad analysis would go away. Pete Warden, for one, warns of some fabulous ways people trip over new data. We could easily call this stuff “data porn” and ignore it.

But there are even more treacherous pitfalls. These potent tools can change everything in a flash (at the “speed of thought”). One minute you’re in orbit, and the next minute you wish you were dead. With sex comes the hazard of a painful breakup, and with data analysis comes the danger of unwanted speech that’s too hot for any public platform. Oops!

We have ways to deal with all that, but it’s never pleasant. The rejected lover picks up and leaves, and the analyst just finds his creative viz zapped off the cloud — by those who are themselves learning a new role.

The lover and the analyst both feel hurt, perhaps betrayed. Wasn’t each playing by the rules? Wasn’t each part of the group? Suddenly each one feels rejected for reasons that a hasty explanation doesn’t quite calm the hurt feelings.

In hindsight, we realize we shouldn’t have been surprised. Social pursuits can be like this.

By the way, who said good tools were the end of the story? Well, most vendors did. Some teenagers think so, too. But even slightly more advanced users know that technical proficiency is only the price of entry. We do the real work in many long conversations and collaborations with words, data, gestures, misunderstandings and reconciliations, and on and on.

Here the analogy breaks. The tools will keep getting better while the bodies fall apart. But the lesson’s the same: Tools enable, but conversation — better known in the business world as collaboration — is really at the heart of our work.

Lyzasoft wasn’t among the 38 exhibitors in TDWI’s Las Vegas exhibit hall. Lyzasoft sponsored no part of the lunch, and they hired no stage magician. But their buzz was the loudest I heard over the event’s five days.

Others may have heard different buzz because buzz varies. Business intelligence elites gather every year at TDWI’s big Las Vegas event to teach, and they end up schmoozing, too. Over beer, food, and sometimes playing cards, they compare notes.

Is anyone seeking a consensus? I suppose someone might, but the interesting ones just play with ideas, reflect on what others say, make a joke, and think about it. If there’s any “truth,” it develops during a lot of talk and thought, whether it’s about politics, tofu, the future of passenger rail in America, or business. That goes for any kind of conversation, whether the medium is words or data.

In business, the conversation is somehow forgotten in favor of the data. But to Scott Davis, CEO of Lyzasoft, the conversation is critical to understanding the data. “A chart has no context at all,” he said in mid February. “The conversation is what’s really valuable.”

The conversation-free, top-down “single version of the truth” isn’t always useful for those who need to manage data for specific uses and contexts. Its “truth” may in fact be no better than Soviet planners’ forecasts of market demand for women’s lingerie. “A single version of the truth,” said Third Nature research director Mark Madsen in Las Vegas, “is true for a single beat of the corporate heart.”

Enter Lyza 2, Lyzasoft’s new version of its data-wrangling and collaboration tool made for data analysts determined to create truth for specific uses and context. The first edition of Lyza offered Excel-like personalization. In the new edition, collaboration seems to have been the guide.

You could see this year’s improvements coming in last year’s email from Lyzasoft CEO Scott Davis: “Even though they are quants, their world is personal,” he wrote. “Relationships are vital. They think in terms of ‘who do I know who knows X type of information sources?’” He could have also been talking about journalists, artists, and anyone else who has to hear signals within noise.

In the new edition, Lyza encourages fluid interactions with a variety of social-media tools: email, Twitter-like messaging, SMS messaging, bookmark collections with annotations, and other tools track and fortify discussion. Lyza lets people work easily with other smart people they trust. If “Steve” believes that “Brian’s” work is good and “George’s” work is not, he can work with only Brian’s data. It also publishes to the new tool, Lyza Commons, for even greater collaboration while retaining users’ ability to interact with data. Lyza 2 loves a good conversation.

The data and everything that happens to it gets tracked automatically. Unlike in Excel worksheets, changes are transparent. Automatic documenting allows any change to be dug up and fixed. If only the data-free conversations in politics and other parts of business had such a tool.

I was surprised to hear spontaneous praise for Lyza’s new version. eLearningCurve education director Dave Wells and Third Nature principal and one of the event’s keynote speakers Mark Madsen both did. I heard the same from several other BI experts, too. Madsen even gave a brief look at Lyza in his Executive Summit presentation on the future of BI.

I harmonize with people who appreciate Lyza at least partly because I think it’s smart to let people work the way they want to work — the way people have always worked. They prefer working with people they trust and with tools that respond. Everything else is static.

I’m sorry to tell you serious types out there, but visual analysis is often a game — in fact, one of the best games in town with Tableau Software’s visual analysis tool. Now Tableau Public is going to bring it to the masses.

In the same way that YouTube spawned a surge of new filmmakers, Tableau Public — free, running the same engine as its desktop sibling, and embedable — will bring on a new generation of data players and spectators.

I was a spectator at a data visualization conference one afternoon two years ago. Tableau Software director of visual analysis Jock Mackinlay had finished his presentation and another person had started his. Yet someone at the control board forgot to flip a switch, and Jock’s live screen remained on one of the room’s big screens. Jock assumed his screen had been hidden, and he kept playing with the data. I don’t have to tell you who seemed to have the audience’s attention until someone pointed out the problem.

The mere visual distraction was minor. Even without narration, I got caught up in the apparent drama as he tried one look at the data after another.

Not long after that, I wondered aloud to someone at Tableau about data hobbyists. I imagined people who foraged for data to analyze then publicize it to start conversations, collaboration, or duels. Data would be their raw material of choice just as scrap metal is to some sculptors or overheard conversations is to some fiction writers.

There was no such community visible then. But I realized this week that I know one now: Dan Murray, a skilled, dedicated Tableau user. He jokes that he’s a “freak” because he analyzes data from the federal budget and posts his often provocative analyses. He’s already been answered by at least one who disagrees with him.

In beta and since its February 11 launch, Tableau Public has hosted a flurry of visualizations, including these: a map of top venture capital firms investments by U.S. region; a chart showing how long it takes to build a technology empire; a history of earthquakes in Haiti; a neighborhood breakdown of housing supply in Seattle; trends in U.S. high school graduation; and studies of deprivation and marginalization in education. In most cases, spectators can become players by selecting subsets of the data to find answers to their own questions.

With popularity comes some misuse. Many of the charts will break rules, such as what happens in another kind of game, YouTube. A New York film editor I know complains that many YouTube-acculturated film editors have neglected basic editing principles. She writes that they rely so much on special effects that they “can’t put two shots together and have them work as an unembellished edit.” On Tableau Public, there will be pie charts, chart junk, and even baselines that do not start at zero. We’ll survive it.

But what’s all this got to do with the very serious practice of business intelligence?

Like monks must have done when printing presses began producing books for the masses, many priests of business intelligence will stand aside, arms folded in the aspe chapel. But I predict that before long even they will appreciate a wider, deeper pool of analytical talent ripening for training and employment.

I suspect that the new bunch will have been sharpened by the give and take of public exposition. They’ll also learn from playing in a huge community the way artists and craftspeople of all kinds improve their skills when they bump into peers every day.

This is a new clue for the future of BI. It can’t help but improve data analysis in business. So let the games begin.

With all the talk about technology, let’s pause to refresh with three basics — culture, conversation, and collaboration. These basics will take center stage in BI’s future, and they’ll help decide which tools dominate.

Lyzasoft CEO Scott Davis and I have been reading the same book, The Culture of Cities by Lewis Mumford. The great thing about Mumford, said Scott, is his mastery of so many subjects, which lets him see relationships and meaning among facts that might otherwise seem irrelevant to each other.

The intelligence that soaks up through every paragraph makes the book a thoroughly enjoyable and insightful chew.

“Think of the most intelligent people you know,” he said. “Are they intelligent because they have an encyclopedic knowledge of facts? Or is it their ability to see relationships? I would say it’s door number two, right?”

Trouble is, we can’t all be Stephen Hawking or Lewis Mumford. That calls for linking of minds. That is, collaboration and conversation. We have to find a way for normal people to find a way to see relationships and offer them.

Train people?, I suggested. Maybe, he replied, but what would that say about the state of BI? It’s natural to have conversations and collaborate. Relevant knowledge and observations bubble up as people focus on something and make associations, gradually raising the group’s insight.

But today, BI platforms make contributing difficult. “BI designers decide what reports are going to be out there, and that’s the well you can drink from.” Instead, people should be as free as in any conversation to make new syntheses, to comment, to recommend — “all the things you’d expect at a dinner party. BI doesn’t feel like a dinner party, does it?”

“I suspect,” he said, “that even though we don’t see it within formal tools, it really is happening, such as through email, spreadmarts, the water cooler and such.”

First comes culture. “If you don’t have that culture that draws people into that practice [of collaboration],” said Scott, “you can have all the tools in the world and it isn’t going to help.”

Next come tools. “There are technological things we can do to make contributing more routine.” He mentioned two mashup tools he likes: JackBe and NetVibes.

The entrenched players are going to change, he predicts. Either Cognos and BO and the others will become a lot more like JackBe and NetVibes, or else companies like JackBe and NetVibes will become the dominant players.

He said, “Ultimately, open and relational are going to win.”