4. Machines only manipulate numbers;
people connect them to meaning.
Arno Penzias (Ideas and Information)
5.
6.
7.
8.
9. “Today’s non-technical people are
than most people on your staff.”
http://www.flickr.com/photos/erikrasmussen/3237904187/
Donald Feinberg, VP - Gartner
to an audience of CIOs
18. Behaviors of innovative thinking:
1. Searching for data
2. Visualizing data and process, to discover relationships
3. Consulting with peers
4. Thinking by free association, combining ideas
5. Exploring via what-ifs and simulations
6. Composing artifacts and performances step by step
7. Reviewing and replaying to support reflection
8. Evangelizing to encourage adoption
9. Allowing all of the above to happen iteratively
Ben Schneiderman (Leonardo’s Laptop)
19.
20. I think the Red
Bull air races
drove this
increase.
This analysis
omits Android
products.
fx = ARIMA 011
Source xyz, filters abc, fx pdq
7
21. Parting Shots
RDF, OWL, etc are just tools
Semantic web should be more than syntax
Enterprise search/3 = hard = $$$
If people can’t understand it,
machines can’t
Web3 needs so much metadata,
it must be crowd-sourced
Editor's Notes
No? Then, we have work to do.
And it’s not just about words. It’s actually even harder on numbers.
We have to attach narrative to numbers to (1) provide them context (2) imbue them with meaning and (3) make them memorable.
Typical conversation among BI program leaders: "how do we make BI pervasive?” YOU don't. Wrong pronoun.
Pervasive~Persuasive (ht donald farmer)
People connect with information that is engaging, memorable, and relevant. That requires narrative.
And, good narrative can only be created by people who understand the context about which they are writing. No centralized planning committee is going to write a single narrative that is compelling to everyone.
It’s not about the tech. It's about people and relationships and storytelling. It always has been.
That’s why we’ve always used stories to teach the timeless truths.
AND WHILE WE”RE ON THE TOPIC of MEANING…
Linked data, semantic web, Web3 and Enterprise Search ….cannot succeed without engaging masses of humanity in the task of attaching meaning to mountains of meaningless numbers
SEE NEXT SLIDE
It is not good for man to be alone.
Man is a social animal.
Computer scientists and information technology professionals have the highest degree of introversion of any profession studied.
Ben Schneiderman, Leonardo’s Laptop
Risk? Or Reward? Both.
Healthy organizations have behavioral norms for members, norms that guard the practices of the organization, which are really the understructure of the brand itself. As an organization grows, the founders cannot police the culture effectively; they have to rely on the culture to propagate itself if the brand is to thrive. Good gossip is an essential habit of any organization based upon social networking, teams, and trust
Gossip is the means by which trust networks communicate norms and enforce them.
Can you imagine us voting on the numbers we should announce as our 4Q financial results?
Symbology is hard.
We can deal with concepts and symbols which are representative abstractions of tangible reality -- but there's a lot of mental work, as the brain continually swaps back and forth between the symbology and the root reality. This swapping back and forth is our way of validating that our representations are true analogies, because we're all just a little uncomfortable dealing purely in the abstract.
Direct manipulation depends upon simpler brain function. Paradoxically, it requires less mental work/energy/activity despite involving more physical work/energy/activity. That's because there's less (or no) swapping-for-validation required. Solving the problem IS solving the problem.
In addition to requiring less power, direct manipulation is also stickier. Retailers have known for a long time that if you can get a prospect to handle your product, there is a much higher probability he will buy your product. There is similar qualitative evidence in our research which suggests that direct manipulation increases the solver's patience with the problem -- keeps them on-task longer than if they work on the same problem purely in the abstract.
If we get people playing with our information, it will cease to be OUR information…but it will become more influential.
Reality….
MYTH: social will create a mess of conflict and disagreement. Don’t we need SVOT? Yes, and no.
Interesting how in the 50’s we went around finding “the best view” and installing fixed viewing platforms. It fit with the modern era’s love of standardization.
But, really, is there a “right” or “best” view of the Golden Gate?
Man is a complex social creature. And groups of people are particularly complicated. You don’t just pick up a translation book and expect ….
…to walk into another culture and understand what’s going on. Customs are complex. Mental models and myths and frames of reference are, too. And they all pertain to meaning and relevancy.
For BI, customs pertain to rules for manipulation and derivation…and relate to physical realities
…..what we call LINEAGE….Where’d this number come from?
IDENTITY IS also KEY to meaning…and vice versa (MEANING we create in turn adds to our identity)
I asked my 17 year old son the other day "How do you use profile pages to understand things about people -- you know, to get a grip on their identity?" His answer: "I don't. Profiles are useless. I look at what they are saying, who's talking with them, and what those other people are saying about them.”
This conversation was brought back to my mind recently by the new Dan Ariely book The Upside of Irrationality, in which he makes a good case (among others) that using a profile to understand a person's identity is like "trying to understand how a cookie will taste by reading its nutrition label.”
Identity is the central datum of the human co-operating system.
Identity helps me interpret things from you. Identity helps me filter the things I send to you. And, Identity is shaped by all those interactions, too.
No? Then, we have work to do.
It's important to understand that there is a reason why we all started our web/sharing work with documents and words: they are easier.
Documents have intrinsic meaning. The fact that we can disagree about what "bonnet" (head covering vs. auto cowling vs. whatever) is a simple proof of intrinsic meaning. Numbers are different. Can we disagree about "7"? Not really; it has no intrinsic meaning -- other than, the rather useless "the integer between 6 and 8". No, numbers take their meaning SOLELY from context, and context is hard to communicate. Very, very hard.
So, context sharing is the killer app for enabling the next stage of information webs, those which will revolve around numbers. And, this I think is a very big idea.
Given that businesses are usually "run by the numbers" to a large degree, I believe that the only way Enterprise 2 will make significant inroads is by solving this "numeric context sharing" problem.
Sharing necessitates that people imbue numbers with meaning. And, that will open the possibility of linkeddata and…..
Imagine that you can see the information flowing through your organization. See who is transforming and enriching it. See how they are doing it. Gauge the popularity and applicability of those feeds.
If you’re an information architect, this is the holy grail. Social Enterprise promises to expose these flows for you.
Web2 is focused on the individual, and it provides a wonderful model of how individuals’ intelligence development (BI) can be incubated when they are provided a seamless environment that embraces, feeds, supports, and tempts them to try something new at every stage in the involvement continuum. This is precisely the deep missing link in BI today, and it is WHY there is much for BI to adopt from web2/ent2.
The centrality of Collaborate is key to explaining why social is the killer app for BI.
1.) collaboration is an evolutionary step between consuming and creating.
2.) collaborators provide the context that makes consuming easier.
We have to start the prescription with an accurate diagnosis.
Back before the term Business Intelligence was shoved upon us, analysts called it Decision Support. Seemed like a reasonable name: someone needs to make a decision between alternatives, and so we want to evaluate the situation to figure out which one is best. It was active, not passive. It was a discovery process that proceeded (non-linearly and recursively) from "I am not sure" to "I know." In other words, it was clear that the term Analyst means "One who proceeds from not knowing to knowing."
Then along comes BI, and suddenly the word Analyst is supposed to mean "One who has the answers." (Newsflash: that’s called an oracle, as in the one at Delphi.) Because these expensive, new, complicated tools don’t allow for much true analysis, the vendors work to shape our language. Instead of analysis as an active process of discovery, they try to reduce it to a process of regurgitating pre-processed answers.
Spreadsheets remain the tool of choice for analysts because analysis proceeds TO knowing FROM not knowing. Uncertainty and discovery and trial-and-error and experimentation cannot be assumed away, despite the wishful thinking of the BI vendors.
Social is about experimentation. How do we create a safe zone for analytical experimentation?
First, a confession: I hate formal requirements documentation. So, I’m sure my bias makes me more attuned to certain arguments. My favorite argument is this: asking someone to write down a precise recipe for a new cake they’d like to eat, without first allowing them in the kitchen to experiment with ingredients/order/heat/time, is not likely to produce a very reliable recipe document. Ditto requirements documents.
But, the interesting question is WHY is it that the formal requirements process is such a failure? I believe one of the chief reasons is that this process assumes Tacit Knowledge is inconsequential, that Explicit Knowledge is the whole ballgame. Anyone who’s ever done any cooking or woodworking or basic research or medical care knows this simply is not true; there is a huge role for feel and intuition and the rest of the subconscious. As a dear MD friend of mine says, there is a reason why they call it "the medical arts." Susan Courtney, an associate professor of psychology at Johns Hopkins, wrote an excellent article on the power of Tacit Knowledge recently in Scientific American Mind. Link to it here.
Given the non-research-esque nature of business, given it’s imperative on results above methods, I find it not terribly surprising that a tremendously large percentage of corporate knowledge is Tacit rather than Explicit. There is so much locked up in the subconscious of SMEs (subject matter experts). Sally does the best XYZ analyses, but she cannot explain why. John somehow always spots the real root issue in a long list of red herrings, but there is no consistent rationale.
Given the modest role of Explicit Knowledge, how can formal requirements documentation -- with its total reliance on Explicit Knowledge -- how can it harness/replicate/extend/improve Sally and John’s work?
Here is my prediction: Tacit Knowledge is the next great gold mine. Fortunes will be made by technology entrepreneurs who figure out how to unlock it. Careers will be made by IT professionals bold enough to equip their non-technical community with TK-extracting tools.
Oh, and by the way, the answer will NOT involve asking users to write down an inventory of all their Tacit Knowledge!
