Year to year comparison By measuring what is easy and useful, it is possible to keep costs down and get some material value.

Is there progress? Take any issue and ask the question “Is there progress in the last year?” ... and maybe also over the last ten years! If the answers are yes, then there is progress.

Time Series Information In addition to mapping that shows the simple spatial dimension of the data, there also needs to be an ability to understand the changes that occur over time about a specific place and a specific characteristic of the data.

Time series information is also critical in the measurement of progress. The goal is to have progress, and to do this as fast as possible, and in ways that are cost effective and with a minimum of undesirable side effects. All of this is best done in a data environment where there is good time series information.

Take any issue and ask the question “Is there progress in the last year?” ... and maybe also over the last ten years! If the answers are yes, then there is progress.

A comparative balance sheet is a simple example of time series ... two datapoints. Having datapoints associated with time makes it possible to do time series. Tine series show how things are progressing or regressing over time. The time interval should be a balance between very frequency and cost and the value of the associated results. Sometimes data needs to be daily, or even more frequent ... sometimes once a year is enough!

Changes over time are very informative. One bit of data is better than none ... but the same data over time starts to tell a story. Are the data telling us that the situation is getting better or worse? Are the data telling us that there is a seasonal characteristics? How do these data sets compare with data from other places? Do changes shown by these datasets show a causal relationship with actions or events that can be identified? These time series are immensely powerful ... and become even more powerful when they are used both in as simple a form as possible and also in ways that facilitate complex searches for correlation.

So much is driven by time series So much is driven by time series ... whole theories of capital market behavior have been developed around this ... scientific analysis ... economic analysis ... etc. But hardly anything has been done at the community level to understand poverty and progress. TVM is setting out to change this.

Time series trends are great indicators of progress ... or not. Time series are simple, clear and powerful. While it is possible to do advanced statistical manipulation ... simple and clear time series tables and charts work very powerfully as well.

There are many different time periods that may be used. The choice depends on the natural characteristic of what is being measured.

• By hour ... to show what happens at different times during a 24 hour period
• By day ... to show what happens from day to day
• By month ... to show changes month by month including seasonality
• Year on year ... to show how things progress over the longer period

Changes over time are very informative. One bit of data is better than none ... but the same data over time starts to tell a story. Are the data telling us that the situation is getting better or worse? Are the data telling us that there is a seasonal characteristics? How do these data sets compare with data from other places? Do changes shown by these datasets show a causal relationship with actions or events that can be identified?

These time series are immensely powerful ... and become even more powerful when they are used both in as simple a form as possible and also in ways that facilitate complex searches for correlation.

The Bloomberg System The Bloomberg organization made data about the capital markets easily accessible to uses of the Bloomberg system. For almost every possible metric about the capital market, the Bloomberg system contains a time series.

Time series trends are great indicators of progress ... or not. Time series are simple, clear and powerful. While it is possible to do advanced statistical manipulation ... simple and clear time series tables and charts work very powerfully as well.

Time series example

Experience from Kwa-Zulu Natal.

In this example the measure was low, then increased rapidly, and then decreased again. In this example the measure is the number of malaria cases in the area, which rapidly increased when the use of DDT was stopped, and then decreased again when DDT was reintroduced. There is no reference to cost. It is possible that DDT is not only very effective in reducing malaria, but might also be very cost effective as well.