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Date: 2022-07-05 Page is: DBtxt001.php bk0003050-v2019
Burgess Book Manuscript
Basic Concepts for TrueValueMetrics
Version of 2010 by Section
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Chapter 3 ... Data Types and Attributes
3-5 Qualitative Information
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More of This Than Anything Else

And not much of great utility ... These data not easy to use

In the last decade there has been an explosive growth in the quantity of information … most of it qualitative information, and almost none organized for easy analysis. The pace of increase in qualitative data has accelerated in the last five years as more and more still images and video join the simple text explosion.

Qualitative information is important … but it is not easy to manage and use. Rather qualitative information works well to clog the system and create information overload.

The academic community with the support of the ICT industry is researching to find ways to take advantage of this huge stock of information … and to profit from it.

There has been modest progress in getting more qualitative data organized, but these initiatives are puny relative to the disorganized text, image and video information that is now swirling around the society.

One of the keys to making effective use of qualitative information is to get it “organized” in an appropriate way. A starting point is for individual data elements to be associated with key attributes like the time, place and source of the information.


TVM is not journalism

Journalists are taught that they need to tell stories … create human interest … make believable with numbers … and so on. TVM is not journalism, but is a simple data system that aims to have data that are right, are useful and are reliable. In TVM, boring is OK … stories and numbers that result in misinformation are not!

Qualitative data often includes some numbers, but these are rarely reliable especially if the text had its origin as journalism where numbers are often added for effect without doing much validation of the veracity of the number.

Qualitative data do not have great utility and contribute to data overload. The bad news is that there are more and more data communicating less and less. The good news is that there is technology that is able to handle data at a lower and lower cost.



Getting Qualitative Data Organized

This basic organization is needed

Qualitative data must be organized in some way … such as pulling similar sets of data together to make it possible to sense what the complete profile of something looks like. The first cut at organization is to pull together data that relate to a specific place … and within these data organize the data around subjects … and then organize into time sequence.

Where best to coordinate?

High level planners and evaluation experts fall back on lack of coordination as the reason initiative fail to achieve their goals … especially around the World Bank and United Nations, and the official relief and development assistance (ORDA) community. This leads to the conclusion and recommendation that there should be a coordination mechanism … and soon there is another overhead organization doing “coordination”. TVM has a different conclusion … that there should be more specific expertise at the “top” with little “coordination” and heavy coordination at the community level where different sectors, organizations and activities have all got to work together in order to get anything done.

Qualitative data organized in time sequence, within sector, within community is a good foundation for coordination … and the start of analysis that will help to coordinate priority initiatives in the community. Data organized in this manner has the potential to be able guide the focus of effort and resource allocation so what needs to be done can get done.


Data have more utility when related to time and place

Any sort of data has more utility when related to time and place. Stories without time and place are potentially dangerous … potential misinformation that encourages wrong behavior. It is widely practiced in fund raising for not-for-profit organizations and discredits the sector.

Descriptive data that related so something at a specific place and time is a starting point for the analysis of change. Another description at the same place at a different time allows for comparison and something of interest may be learned about any change that has taken place … whether or not there is progress or not … whether or not there has been any change!


Getting utility from qualitative information

When there is numerical information it is possible to get the data easily organized and summarized … but it is also possible to have qualitative information that is also very useful without having much in a numerical form
Cholera in Haiti
When the news media reported the presence of a deadly cholera outbreak in Haiti … it was interesting bad news, and not immediately apparent that it had management utility. The news becomes more useful when it was related to the cholera situation in the past. A few months before there was no cholera and no news. There was a change for the worse … and there must be a reason.

We know that the sanitation situation in Haiti has been totally unacceptable for a long time and was likely to result in a bad health impact … much more should have been done to avoid cholera getting into the transitional camps … and we now know that whatever was done was insufficient. We do not know explicitly who is responsible … but we do know enough to be able to stir-up the parties who should have been responsible.
The purpose of information is to get better decisions made … not merely to have intellectual and academically rigorous data that has huge cost but little utility.

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