this paper is reprinted from Random Thoughts, XSI's newsletter dealing with major issues in information productivity.
There is today, among information providers and consumers alike, an almost frenzied rush to automation. Industries and publishers alike are buying new technology aimed at interactive delivery, CD-ROM, multi-media, access to the "information superhighway" and a dozen other impressive sounding titles. The trouble with this is that many of these organizations haven't stopped to think about where or why they're spending their money and time, or what they are likely to get for their efforts. Without such a reasoned analysis, they have scant hope of spending wisely or of ending up with the level of return they hope for.
Following is a thumbnail guide to productivity in the information process, from conception to consumption, and the underlying economics of producing, managing and delivering information products.
Information is a process, always made up of three major elements:
The relationships among these three factors, and how we are able to affect them, determine the success of everything we do in capturing data and selling information products made from them.
Once we accept this fact, we can cut through much of the techno-babble that passes for planning and development, and get down to the business of figuring out how to make our information-related activities truly productive.
Data, in modern society, is the only available medium for delivering the creator's wisdom to one or more consumers.
How efficiently the information process works is dependent on how well and completely a creator's knowledge is translated into data products and how easily the intended consumer can use those products to find and understand what he or she wants. We can pontificate all we want about capturing and managing information, but it is data that we are talking about, and the two are not synonymous.
The user "buys" a data product, then tries to create information through its use.
For paper pages, we understand this process reasonably well, but as we move toward new, electronic delivery media, it's a new ball game. If the data underlying a product isn't sufficiently well designed and constructed to support truly effective access, the users aren't going to get what they are paying for and they will find another source.
Many publishers, for example, think that a CD-ROM product is just a fancier version of their old paginated data and editorial thinking. They usually find, often the hard way, that their prospective buyers are looking for higher information value than they got with pages and aren't satisfied with mere electronic window dressing.
It took human society nearly twenty-five-hundred years of cultural negotiation to develop the formats used in recording data on pages. We would be monumentally arrogant to think that we can master new and radically different delivery media in less than a decade.
The productivity of an information process is determined by teh extent to which the total cost of designing, capturing and delivering the data product can be borne within the limits of the total value placed on the resulting information by its intended consumers
If it cannot, the effort becomes philanthropic. If it can, then the effort is productive and becomes more so as the cost is reduced or the products are enhanced. This is the critical variable that should guide any effort to implement or upgrade technology at any point along the path between information provider and consumer.
Anything we do in data automation must have at least one of three effects to be justified:
Somehow, most information providers proceed as if buying a bunch of new computer equipment, will automatically lower their costs. In fact, most technology upgrades, even successful ones, have precious little positive impact on overall cost. Indeed, they are usually not even aimed at where most of the money is being spent.
Consider this:
Most technology acquisitions, hardware and software, focus their spending on the phases of the data creation and delivery process in the following descending order:
Yet, if we rank these factors in terms of their ongoing contribution to overall data cost, they fall almost precisely inREVERSE order to the above. WE ARE PLACING MOST OF OUR EMPHASIS AND MONEY WHERE IT WILL DO THE LEAST GOOD!
Until this trend is reversed, information productivity simply will not keep pace with demand, and the billions of dollars dumped into technology will, at best, yield marginal results.
It's the people in our equation that cost the real money. Those experts who impart their unique knowledge to the data formats we design and on whose productivity we build our entire data world, are the engines of success and the most expensive and fragile resource we have. Until they become the PRIMARY focus of our automation planning, we are just leaving money on the table.
We are children of books, pages, columns and the like. We begin learning this method of receiving and using data so young that we scarcely know how steeped we are in its nearly two-thousand year old logical and visual devices. When we think about new ways to capture and deliver data, we start from this time-worn metaphor (Interactive Electronic Technical Manual is not only a mouthful, it's an oxymoron).
Perhaps the worst manifestation of this tunnel vision is the publisher who's convinced that merely reformatting paged data will feed the new electronic delivery his users are demanding. There is, in any data medium, a finite potential for information interchange and nothing we do by way of prettying up the display or traversal of page data will more than marginally increase its value. Users, even those initially impressed with the sheer glitz of electronic delivery, decide very quickly whether or not the new medium is really a better information tool.
We must rethink the questions to which pages were an answer so many centuries ago, and design new answers based on better data and more elegant delivery media. In the last edition of this newsletter, we discussed the rethinking of tabular data for electronic delivery. This level of thoughtful reanalysis must be applied to every part of our data and delivery structures. Anything short of it will put a new coat of paint on the old barn, but it won't increase its capacity.
The most implacable reality faced by information providers is the fact that, by the time they finish capturing and formatting the data needed to produce an information product, theyv'e spent nearly all the money they budgeted for the project. They've driven their stake in the ground long before the first dollar comes in the door and they can only hope and estimate that the income will justify the outgo. Historically, most of this cost was aimed at the production of a paper-based product by which the effort was justified and on which its success depended. When the printed page was the only widely accepted product vehicle, this worked reasonably well. Today, however, with the cost of data capture going up and the delivery media often changing radically even within the life-cycle of the individual data, it's getting harder to justify major expense on only a core product line and, hence, to accurately estimate the likely income.
Publishers must be able to design their data so that, while paying only once for creation, they can move with their markets, extracting new products from that data resource as the demand arises, and combining previously separate data resources for completely new information services. What's more, this level of flexibility must be possible without major additional expenditures to retrofit or upgrade the existing data resources, in either design or content. Information providers capable of this will keep up with cost and market expectations, leaving the others behind.
All of this flexibility is based on effective and farsighted data design, editorial automation and authoring productivity, not on delivery tools, infrastructure and technological toys.
This brings us back to where we started, the relationship between those who know and those who need or want to know. By focusing on making our creators and authors more productive and on producing data resources and products that can satisfy a broad range of user needs and demands, we begin to improve the fundamental processes by which society shares valuable knowledge. If we can then use these foundation improvements as the basis for the design and implementation of systems and technology (rather than the other way around,) we may finally see ourselves moving back toward a state in which our tools serve us rather than dictating the nature or our information world.
That time can't come too soon.
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