modeling

Mel Duval wrote a nice piece in Information Management about enterprise architecture (EA) and our book - http://www.information-management.com/news/-10016459-1.html – It’s entitled “Averting Disaster Through Enterprise Architecture.”  Mel writes, " In all the debates about what drove the world economy into its worst recession in decades, rarely does the concept of enterprise architecture come into the discussion. Yet, perhaps it should."

Although there may be some truth in claiming "too big to fail" applies in the case of the still-standing among Bear, Fannie, Freddie, AIG, Merril, Citi, BofA, GM, Chrysler, and the rest of the cast of bankrupt characters, the greater truth is that they are too big to manage without enterprise-wide, integrated, and detailed models.  The truth is that just about every part, as well as the whole, of these enterprises was profitable and management of every part and the whole were getting their incentive bonuses for a job well done.  All were regulated too.  Yet no one saw the risks to the whole enterprise, let alone the whole US and global economies, that were right in front of them, more or less plain as day. 

Why was that?  Short answer is "All we will ever know is our models."  And our models did not take those connections or all those systemic risks into account.  They were effectively invisible to all but a few.  Among the blinded was economics professor and Nobel laureate Paul Krugman, but now at least he recognizes the problem too and in his's 6-Sept-09 New York Times piece "How Did Economists Get It So Wrong?" opines about the models and theories of "the economics profession went astray because economists, as a group, mistook beauty, clad in impressive-looking mathematics, for truth."

EA is about modeling the whole enterprise, knowing all there is to know about it, its parts, and their interactions, whatever the goals or objectives of the enterprise may be.  Yet our research (as reported in the SIM Guide to Enterprise Architecture - http://eawg.simnet.org/) indicates that only about 1/3 of IT people agree with that statement.  Probably to be expected at this early stage in the adoption of EA concepts to managing enterprises and their technologies.

So what is EA and what is its purpose?  Over the years we've come up with sound bites such as:

The purpose of EA is to provide the holistic set of descriptive representations about the enterprise over time. -- SIMEAWG (http://simeawg.simnet.org).

The purpose of EA is to “model” the enterprise. -- Leon Kappelman

The purpose of EA is to bridge the chasm between strategy and implementations -- Leon Kappelman

The purpose of EA is the creation of a shared language (of words and pictures) to communicate about, think about, and manage the enterprise. -- Leon Kappelman

Lately, though, I've been thinking that the greater "purpose of enterprise architecture is to bring all the IT people together, so they can bring all the rest of the people in the enterprise together."  Getting "everyone on the same page" might be another way to say it, and certainly there are other ways too, but I think I'll stick with "bring ... together" for now. 

But if the IT people can't even agree that EA is about the whole enterprise and not just its ITs, how will they ever come together, let alone help the rest of the people in the enterprise come together?  I don't know the answer to that question, but I'm pretty sure it's going to take some time, happen incrementally, and that this article by Mel Duval will help.  The SIM Guide to EA will help too.  I'm glad we've gone to a second printing already.  But non-IT enterprise management needs to get the message too.  Because it’s the decisions of non-IT people that brought the economy to the brink, and many organizations far past it.  I certainly hope some of them are listening, and reading up on using enterprise models to manage too, whether they call EA or something else.

Human currently use nearly 7000 spoken languages on the planet earth.  The encyclopaedic inventory of them is called the Ethnologue and it is written and published by the not-for-profit, faith-based, linguistics organization SIL International (all quotes in this paragraph are from their website http://sil.org).  SIL is in many ways a remarkable organisation and SIL's Ethnologue: Languages of the World, "is a comprehensive catalog of the world’s more than 6,900 living languages."  But language, and the sounds, words, meanings, and rules that comprise it, are part of, as well as a reflection of, the culture that created and uses that language.  And so the Ethnologue is "a veritable guide to the world's … languages and cultures, providing a bounty of sociolinguistic and demographic data in addition to linguistic information (ACRL, C&RL News, March 2005)."  In short, SIL has found that "studying these languages results in practical help for local people and contributes to the broader knowledge of linguistics, anthropology, and ethnomusicology." 

Language and culture are intimately linked.  Language is a reflection of how a culture "sees" and "experiences" the world.  I grew up in Ohio and we basically had two words for "snow" -- "snow" and "slush".  But Eskimos, who live in a world where snow is a predominant feature, have more than 100 words for snow (http://www.mendosa.com/snow.html).  Language enables creativity and communications, yet it does so by enforcing constraints manifested through those sounds, words, meanings, and rules that comprise it.  And those creativity unleashing constraints also constrain our perception of reality.  In other words, word and language comprise a "model" of the world that we use to comprehend and communicate our experience of reality.  But the words are not reality any more than the map is the highway or the word "water" is wet.  Stephen Hawking, the astrophysicist, summed it up beautifully when he said "All we ever know is our models, but never the reality that may or may not exist behind the models ….  Our models may get closer and closer, but we will never reach direct perception of reality." (Nature, Dec 2000, 775.)

Recently I came across a Zen master's way of expressing this same concept: "Suppose the mind consciousness is observing an elephant walking.  During the time of observation, the object of mind consciousness may not be the elephant in and of itself.  It may only be a mental construction of the elephant based on previous images of elephants that have been imprinted in store consciousness.  Inquiry means not using the mental creation, but allowing yourself to get in touch, and to try to see how things truly are.  We practice not to be influenced by the name, because when we are caught in the name we can't see reality." – Thich Nhat Hanhin (in “Zen Lessons in Market Analysis” by John P. Hussman, (http://www.hussmanfunds.com/wmc/wmc091011.htm).

The purpose of this blog is to help us all, myself included, rely a little less on those "mental creations" of words, models, maps, and the like, and thereby allow ourselves to experience life and each other a bit more fully so we can "get in touch, and to try to see how things truly are."  Often that results in merely modifying, enhancing, or expanding our repertoire of mental creations, and in so doing hopefully we get a little bit closer to reality and to each other.  Human communication is a strange, wonderful, and highly imperfect combination of science and art form.  It's not always easy, but generally very rewarding when I remember that words are models too, and as such are imperfect, imprecise, and yet very, very useful. 

All we will ever know is our models. 

What happened to global warming?

By Paul Hudson. Climate correspondent, BBC News

(Page last updated at 15:22 GMT, Friday, 9 October 2009 16:22 UK)

"This headline may come as a bit of a surprise, so too might that fact that the warmest year recorded globally was not in 2008 or 2007, but in 1998.

But it is true. For the last 11 years we have not observed any increase in global temperatures.

And our climate models did not forecast it, even though man-made carbon dioxide, the gas thought to be responsible for warming our planet, has continued to rise. ...

One thing is for sure. It seems the debate about what is causing global warming is far from over. Indeed some would say it is hotting up."

More precisely, the debate about whether there even is any such thing as "global warming" (or more accurately "anthropogenic climate change") is far from over.

Read the entire article at http://news.bbc.co.uk/2/hi/science/nature/8299079.stm.  Think for yourself.  Our brains are still the most powerful computers on the planet.  All the computer models, theories, and hypotheses are merely tools to help us think, not think for us.  Be aware of your biases too, we all have them.  Almost everyone believes that humans should (even must) be good stewards of the planet and its environment -- Regretably this can make almost everyone suceptible to manipulation in the name of doing good for the earth and its inhabitants.  Moreover, since this is a political debate as well as a scientific one, it may be revealing to follow the money.  And keep in mind that power, influence, and money are fairly fungible these days when it comes to political and business decisions; and sadly, scientific ones too (e.g., see http://chronicle.com/article/Medical-Journals-See-Cost-in/48393/?sid=at&utm_source=at&utm_medium=en, http://content.nejm.org/cgi/content/full/346/24/1901).

This report is probably indicative of the state of the art on climate models.  The good thing about this report (http://globalchange.mit.edu/files/document/MITJPSPGC_Rpt180.pdf) is that (1) they take a systems thinking approach and make a real effort to deal with the complexity of the question, (2) they disclose all the models they cobble together, all the assumptions they make, the parameters they estimate, the sources of their data and the component models, and (3) then run Monte Carlo simulations to develop probability estimates.  The bad news is that the media will probably never look the details and just report the headlines and the colorful graphic (http://web.mit.edu/newsoffice/2009/climate-change-1002.html). 

What astonishes me is how much time and money are going into this kind of work, how many government agencies and energy companies appear to be funding this, how complex the model is, and how many assumptions it requires.  In some ways this makes their findings appear to have high face validity and will limit serious examination of their work.  The fundamental underlying weaknesses of this work are (1) how suspect much of the underlying science is that they assume to be true before this research even begins, (2) that they appear to assume the component models and estimates are perfectly right before they begin the simulation, and (3) that they fail to disclose or include the probability or confidence intervals of any of the assumptions or component models (perhaps because this research assumes them all to be perfectly right before beginning).

Clint Eastwood's Dirty Harry line "Are you feeling lucky, punk?" comes to mind as I ponder to what extend the world's policy makers, in their desire to be good stewards of the environment, may bet their national economies on this model which is basically no more than a weather forecast on steroids and mega-vitamins.

• "All we ever know is our models, but never the reality that may or may not exist behind the models and casts its shadow upon us who are embedded inside it. We imagine and intuit, then point the finger and wait to see which suspect for truth turns and runs. Our models may get closer and closer, but we will never reach direct perception of reality's thing-in-itself." – Stephen Hawking

• “Any fool can make things bigger, more complex, and more violent.  It takes a touch of genius — and a lot of courage — to move in the opposite direction.” — Albert Einstein