Doug Short has an excellent post up today Household Net Worth: The "Real" Story.  Check it out.  It provides an easy to follow example of some of the principles that we hold most strongly:

• The post identifies a key metric (Household Net Worth) that has not received a lot of attention and really looks at that metric all by itself using several alternative views to aid in understanding.
• It includes a long time perspective as well as zoomed in views thereby revealing patterns that would have remained invisible if only a single time span had been chosen.  
• The post provides a clear storyline -- sharing with us what Doug was thinking while he looked at these charts and selected them for our edification.

Providing some Context for looking at CPI charts

We have posted many charts this past week looking at CPI behavior through a variety of angles and lenses.  Our sources have been light on providing context and we have not filled in this area either.

So here is a first cut at the context that we were holding loosely in mind as we evaluated the incoming collection of charts and created a few of our own using the St. Louis Federal Reserves' FRED software.

To begin, CPI stands for Consumer Price Index.  In our view, the emphasis is on the Consumer (real people living out their lives) and the ways in which changes in Prices (specifically price inflation) might impact the standard of living for those people.

Central Questions:  The question we would like to be able to answer more fully is:

How does the cumulative change in prices affect the buying power of a range of different classes of consumers over time?

In particular, we want to be able to figure out to what degree the Cumulative Impact of Price Inflation changes each different class of consumer's standard of living over time.

Principles.   The underlying principle that we believe to be at work here is that: if cumulative CPI goes up relative to the wage trend for households representing a given class of consumers, then the Standard of Living for that class would go down in proportion.  We are interested in looking at the cumulative change over a variety of longer periods: 2 years, 3 years, 5 years, 10 years, 15 years, 20 years

A second key principle for us is that CPI Inflation is like Compound Interest; and so longer term cumulative views of the data should predominate.


Weaknesses of Traditional Reporting:  To us, the commonly used month over month results represent little more than noise since our focus is on cumulative results.

Even the very widely used year over year reporting is not particularly useful in this regard and is usually distracting at best (1 year effects are interesting but surely not the whole story) and misleading at worst as to the important long term inflation changes that are underway and the implications of those changes on real people's standards of living and quality of life.

A long standing general purpose admonition of ours is to Look at All the Data.   The traditional reporting on CPI violates this rule in spades with the focus on only headline CPI and core CPI .  CPI is an aggregate of aggregates of aggregates which averages out a huge degree of variation that is present in its sub-components.  To begin to understand the impact that cumulative price inflation has on Consumers (real people) we surely need to disaggregate the average CPI values and look individually at a good number of the key sub-components (e.g.  Food, Energy, Health Care, Rent, Transportation, Tuition) to see their cumulative price inflation over longer periods of time.   With few exceptions such as the excellent chart we posted earlier (A Unique View of CPI from Doug Short), almost all reportage we have found on CPI focuses on headline or core cpi.

Now it is true that the official report from the BLS (BLS August 2011 CPI news release)  does provide an exceptionally high degree of disaggregation in its tables by sub-categories and sub-sub-categories.  But there are no sub-component charts accompanying the BLS report, so looking at sub-component increases in cpi is left as a time-consuming exercise for the reader - an option that few have likely taken.    Furthermore, the data presented only covers the most recent 1 year period, so if you want to explore sub-category cumulative changes over periods of 2 to 20 years, you have to look somewhere else (e.g FRED or the BLS data base).

There is a lot of fruitful potential in this disaggregation, but I have not been able to find anyone so far other than Doug Short and our recent post (Drilling down into CPI 20 year trends)  tapping into this for more insights into understanding the cumulative impact of inflation on real people.  We will keep on looking and would love to hear about other work in progress studying the sub-components.

Core CPI interferes with clear thinking.  Finally, looking at widely discussed Core CPI and its many variants,  we see Core CPI as a serious impediment keeping us from thinking more clearly about the cumulative impact of price inflation on real people who all must eat and consume energy.  Rather than stripping food and energy out of the totals to create so-called CORE CPI, it would be much more useful in our estimation to include Food and include Energy as individual sub-categories - to look at the cumulative impact of Food price inflation and the cumulative impact of Energy price inflation as we have started to in our Drilling down into CPI 20 year trends  post.  And rather than lump all the rest of the categories together to create the "core", we would prefer to disaggregate these as well and look at them individually so we can discover patterns currently hidden..

A lot has been made about why Energy and Food are so volatile as the reason for going with Core CPI.  Our investigation shows that the mostly irrelevant month to month variations smooth out incredibly well for FOOD once we look at cumulative totals.  For ENERGY, there is clear volatility, but rather than hiding it, it's better to bring it out into the open.  And when we look at energy using a cumulative long term 5, 10, 15, 20 year approach, there is a lot less volatility than you might expect.  We'll have more on this later.

And the headline CPI number shows very low variability in trend when plotted using a long term cumulative view as we have shown in our early post ( Drilling down into CPI 20 year trends ).

There are further weaknesses we see in traditional CPI reporting regarding the limited number of different classes of consumers currently available) but we will save these for another day.

Now that we have some context on why we want to look at CPI, our plan is to revisit the CPI posts from earlier this past week.  We plan to update them by showing our thinking regarding what we see as the story that might be told for each chart in the context of the ideas we have explored in this post - real people, cumulative impact over longer time spans, disaggregation.  . 

Update 20 September 2011:  We have now updated all previous CPI posts with our further thoughts on what each chart is telling us.  Please check them out.

Reviewing the Situation

It's been a while since we formulated the Trend Visualization Principles displayed in our blog's right hand panel. So we thought it was a good time to revisit them and update them to reflect both on what we have learned and on the rapid pace of change in the intersecting domains of data gathering, analysis, visualization, story telling, sharing, and collaboration.

Our revised seven principles are:

1. Context comes first
2. Create a history
3. Look at ALL the data
4. Share ALL your data
5. Explain your calculations
6. Show your thinking
7. Insure readability

Please check out the full statement in the right hand panel and let us know what you think.

These principles when put into practice can serve as antidotes to some of the weaknesses highlighted in the most recent post. (Common Weaknesses in Online Visualization & Storytelling)

We plan on posting some longer explanations of our thinking on these principles in coming days starting with two that are oft neglected in practice (self included) . Our experience has been that these two can reap substantial rewards when we make the time, when we take the time to remember to put them into action

• Look at ALL the data
• Show your thinking

What are your most useful principles that you keep in mind while gathering analyzing, visualizing, story telling, sharing, and collaborating about important trend data?

Ten Trend Charts from the DoD Quarterly Report

The Dept of Defense has just published its mandated quarterly report to Congress on the situation in Iraq - Measuring Stability and Security in Iraq, June 2007 (51 pages). As they state in the Executive Summary, the "report includes specific performance indicators and measures of progress toward political, economic, and security stability in Iraq"

Included as part of the report are 10 static trend graphs which I have reproduced in this post. You can click on each for a full size image. If you would like all 10 JPG images so you can look at full size with your favorite slide viewer, you can download this zip file.

Most of the important performance indicators mentioned in the report did not rate their own static trend graph chart. As we did with the UN document and our scan of recent news articles, we plan to comb through the document and come up with a list of indicators that complement the ones we have already highlighted so as to get a sense of the breadth of important indicators that are already on our radar screen.

Chart 01 - Oil Production - too short a time span. Also missing data for May 2007.


Chart 02 Electricity - Missing data for April and May 2007.



Chart 03 - Sectarian Murders and Incidents . Missing data from May 2007. Weekly data might be important to look at.


Chart 04 - Weapons Caches Found - This is looking promising. Access to weekly and daily data could be even more revealing of ongoing trends. Missing data for May 2007.



Chart 05 - Average Weekly Attacks - Missing last 5 weeks of data. This is the source for the charts that appeared in WaPo and NYT as reported earlier today.

Chart 06 - Average Daily Casualties - Missing last 5 weeks. Bar chart format with three trends makes reading trends for Iraqi Security Forces and Coalition more difficult.


Chart 07 - Hotline Tips - Interesting new performance metric. Looks positive. Missing past month of data. Weekly or daily data reporting could be even more revealing.


Chart 08 - Confidence in Iraqi Government to Improve the Situation. This looks surprisingly to me for its stability over time. I will need to read the text about this in detail. Missing most recent month's data.


Chart 09 - Assessed Capabilities of Police - Difficult to interpret trends when only two data points per item. Stacked bars make interpretation more difficult and time consuming. This is an interesting new metric and it could benefit from higher resolution, near real time reporting.


Chart 10 - Ministry of Defense Forces Assessed Capabilities. This chart also presents some important data but suffers from same failings as previous chart - only 2 data points per indicator, stacked bars are hard to read.


Summary. 10 Static charts covering a range of important indicators is more than almost anyone else except Michael O'Hanlon produces when it comes to highlighting the important trends evolving in Iraq.

So that's definite plus. Someone who spends a few minutes can examine all 10 of these (especially if they can scroll in slide show mode on full size images using this zip file).

On the minus side, the missing last month or last 5 weeks of data is a serious drawback. Many of the charts can be improved on and made more readily useful to ordinary viewers by applying some trend chart best practices principles. These include

• use of full time range
• use of near real time reporting for the most recent interval
  
• selection of best resolution or choice of several different reporting intervals (day, week, month)
• displaying each important indicator separately with appropriate Y axis scale
• having sufficient data points for trends to be discernible - 2 is way too few
  

And worst of all, most of the important indicators have no charts at all and are only discussed in text or in tables showing the current values.

The indicators in this report are important, but this method of presentation falls short of ideal and short of what is needed and what indeed is possible. With the high number of factors discussed in this report, the only method that will actually make this kind of trend data usable to its intended primary audience (Congress) and to the secondary audiences including the media and ordinary interested citizens would be to deliver this data via a 21st century Trend Visualization Appliance.

What's the Best Reporting Interval?

Why Wait for a Quarterly Report? Yesterday's DoD report to Congress is a mandated quarterly report. The executive summary begins with:

This report to Congress, Measuring Stability and Security in Iraq, is submitted pursuant to Section 9010 of the Department of Defense Appropriations Act 2007, Public Law 109-289. The report includes specific performance indicators and measures of progress toward political, economic, and security stability in Iraq, as directed in that legislation. [emphasis added]

My view: This report can do double duty. Quarterly reports are all well and good. They present us with specific performance indicators and measures of progress. They offer an opportunity to take a step back and look at the evolving patterns.

AND between reports, they can be even more helpful on a daily, weekly and monthly basis.

Just as we don't have to wait till July or September to find out how well the "surge" strategy is working, we don't have to hold our breath between quarterly reports. We can make double duty of the infrastructure already in place to produce these reports to create a mechanism that lets us keep track of the most important indicators and measures of progress as we go along.

Here's How.

1. Start where we are at. The quarterly report defines the currently understood list of the most important performance indicators and measures of progress.
   
2. High Frequency Measurement. For each of these important indicators we establish a measurement frequency that is as rapid as is practical at this time.
   
3. Near Real Time Reporting. For each of these important indicators we also establish a near time reporting interval that is as close as is practical to the time of the most recent measurement sample
4. 21st Century Visualization. We then make the full set of high resolution trend data for all the most important performance indicators and measures of progress available. We make it available in a continuously updated form in near real time using a 21st century Trend Visualization Appliance. This makes it possible and manageable to observe the trends of a large number of factors within the time and resource constraints of the intended audiences.
   
5. Improve Frequency. For any important factor where it proves impractical today to measure at the frequency that we think best, we set in motion a process to speed up that frequency as quickly as we can bring it on line.
6. Improve Freshness. For any important factor where it proves impractical today to deliver the most recent measurements in suitable near real time fashion that would meet our needs for fresh data, we set in motion a process to reduce the delay as quickly as we can.
7. Identify and Add Missing Indicators. Finally, as soon as we notice some new and important indicator that is vital to understanding progress in Iraq, we add it to the list of indicators to be included in the Quarterly report AND to be delivered to our Trend Visualization Appliance at high resolution and in near real-time for our consideration between these quarterly reports.

Shorter Version:
If there is a performance indicator that is important enough to be reported on quarterly, then it is even more important to make the underlying trends for that indicator available interactively and efficiently, at high resolution, and in near real time for all interested parties.

The current arrangement (infrequent reports, delayed reporting, lower frequency data) does not appear conducive to the most effective oversight by congress, the media or the general public. We can and must do better if we want to make sense of what is happening in Iraq.

Near Real Time Reporting

For most important situations in life where trend visualization is helpful, we are lucky that real time reporting is not required. However, collecting the data and reporting it within a reasonable time from the end of measurement is important and can deeply impact the value and usefulness of what we have collected.

An Unacceptable Delay. We noted earlier today in the post on the New York Times Iraq Progress Graphic how the underlying data from the DoD quarterly report to Congress only covered up through May 4th. So in effect we were looking at data that wasn't produced in a report till 5 and 1/2 weeks after the end of the most recently reported period.

In my opinion, this represents an unacceptable delay and that delay severely impacts the ability of any audience to gauge what the data means and to decide what to do next.

If the underlying data for attacks and for casualties were collected at the recommended rate of once per day, a near real time report on June 13th would be best if it covered everything that happened up through one, two or three days prior to June 13th.

Fresh Data. The combination of high frequency measurement and near real time reporting means that the data we are looking at is fresh - a vital quality in any rapidly changing situation. There are numerous examples in other aspects of our lives where near real time reporting and high resolution reporting are simply the norm (the stock market being a prime example).

There are sometimes situations that delay and interfere with our ability to roll up the most recent results of a particular indicator. In some cases, these are historical and can be overcome and minimized if we decide to put our minds to it and invest in the needed infrastructure to make it happen. In other cases, there are time lags that are mostly out of our control. The best we can do in these cases may be to put our energy towards devising ways to minimize the delay.

Bottom line: In a trend chart that is going to help us understand what is truly going on, timeliness is very important. When we get our measurement rate set appropriately and we make every effort to minimize the delay between collection and reporting, the trend work that we do will have the maximum value to all those who are interested.

Bridging Rep. Kingston and Michael O'Hanlon's Concerns

In the two previous posts, we have spoken to the concerns of Rep Kingston and Michael O'Hanlon as captured in the Sheryl Stolberg New York Times See You in September ... article.

To be successful in understanding what is happening in Iraq, we need to listen to both their voices.

A Sufficient Number of Factors. We need to pay heed to O'Hanlon and make sure we have looked at enough different factors.

Manageable Metrics. We have to hear Rep. Kingston's concern and worry about being overwhelmed with too much data or rendered ineffective by not having enough time by making whatever data we report on "Manageable" within the constraints of the time and resources that are available to us.

Eating our Cake. It is possible to meet both of these goals. We are not doing it today, but we are surrounded daily with visible proofs that equally difficult trending situations (see the St. Louis Fed Reserve FRED application as an example of what's possible) can be brought within our grasp and control by the judicious application of 21st century Trend Visualization methods.

Along the Way. Paying attention to our view of the best practices and principles of trend graphic excellence will provide the third ingredient that helps make our efforts in this arena more effective and more readily sharable with others. For a discussion of these, check out the Trend Visualization Principles displayed near the top of the right column of this blog or follow this link to trend principles for a review of some of our other thoughts on this subject.

Applying Trend Analysis Principles with Brilliant Effect

Buying a camera at a fair price is not particularly earth-shaking activity, especially compared to trying to figure out whether our actions in Iraq are helping or hurting.

Nevertheless, here is a simple and striking example of the power of applying the essential principles of trend analysis to the task.

Pricescan.com did a brilliant job on this in my opinion.

The red trend line represents the high price, the blue the average price, and the green the low price. Each tick mark on the X axis represents one week's time and the chart covers the period from 9/11/2006 through 6/4/2007

What did pricescan.com do right

1. they identified the most important factors (in this case the minimum, average, maximum price for the Canon PowerShot AS710 IS camera.
   
2. they collected the raw data each week of the price of this item from a range of sources
3. rather than showing the raw data, they created calculated values of High, Average, Low price for each period
4. They selected a reasonable reporting rate that fit with the data (1 week in this case) and the resulting trend lines are relatively smooth while still giving us enough data points to have confidence in our understanding of the trends we see developing. A total of approximately 38 data points are plotted for each factor.
5. their Y axis scaling fits the data and makes it possible to see the trends in all three indicators that they displayed. The scale values are also easy to read.
6. they are reporting their data in near real time. The most recent data point is only 5 days ago.
   
7. They showed the entire time period ( I am guessing from product introduction right up through last Monday)

And of course, they visualized this data for us rather than telling us about it or showing us a table of 100+ numbers.

Armed with this easy to read chart, anyone interested in purchasing the Canon PowerShot AS710 camera in the next week or so will know whether the offering price is within a reasonable range and can then get on to evaluating the other factors that might impact their buying decision.

This example stands in stark contrast to the most approaches to other important areas of our lives as exemplified in yesterday's Iraq Forecast post. There are no mushy metrics or imprecise quantification or flowery metaphors. There's no postponing the moment of truth cop-outs saying we don't know exactly what the future will bring. Of course we don't know exactly. We never do.

They don't say: "we can't really tell you whether the price of this item is going to become more affordable by September".

There's just the relevant facts that help deal with the specific situation.

My two cents: the better we learn how to apply this kind of approach to the most important problems in our lives, the quicker we will begin to gain control of what's happening.

Are we there yet?

How well does the current set of Iraq trend charts & tables serve our needs?

Answer: I think we are a little better off than we were 10 days ago when I began this series of posts on Iraq, but we certainly are not where we need to be. We can look at the charts that are currently available from multiple sources much more quickly now than we could before by skimming these two pdf files: Combine-Iraq-Trends and vizualizing-trends-ohanlon-testimony.pdf. But each of these documents has it's own and weaknesses as discussed below. And there are a growing number of important missing metrics that as yet have no publicly available trend chart or trend table.

What are the weaknesses of the Combine-Iraq-Trends document?

Answer: This combined report consisting of trend charts drawn from 4 different sources covers a lot of important ground and shares the trend behavior of many factors that appear quite important. On the downside, the big weaknesses of this set of trend charts are numerous:

1. There is a wide variation in formats - This reduces overall understandability and slows down the process of viewing the entire set of charts. Each chart must be examined individually with careful checks to make sure that the range of the X and Y axes are are clear and to locate the legend information that tells you what kind of factor you are looking at. This is in clear violation of the Edward Tufte's idea of small multiples that we discussed in a previous post. Applying small multiple thinking to a set of trend charts means that for the viewer, once understanding is reached regarding how a single chart in a series is laid out and what graphing conventions have been used, succeeding charts can be grasped with much reduced time and effort.
   
2. Time frames of the individual charts are widely different. Some cover the period from the start of the War in 2003 right up to the present moment. Others, cover much shorter periods. For example, the IED chart covers only from January 2006-June 2006. Some charts show monthly data, others show weekly data. This is another violation of the small multiple idea and the consequence for the viewer is that it is more difficult and more time-consuming to make any comparisons between different factors.
   
3. Stale Data: Violation of the "Near Real Time" Principle In many charts such as the IED chart mentioned above, the most recent sample is many, many months ago. If something is rated as an important factor, then it won't do us any good unless we measure and report on it often and that we make the most recent sample data available as quickly as possible. A 7 month old data point of a key trend factor can substantially frustrate our ability to understand what's going on, to determine whether interventions we have taken are working, or to decide what to do next.
4. Overly short time frames. Charts such as the State Dept's Crude Oil Production chart cover an amazingly short time frame - in this case from October 30th, 2006 to January 7th, 2007. While this chart is both interesting, useful, and clear, the viewer is seriously short-changed by not being able to look at what has happened to this key trend factor for the entire period since the war began.
   
5. Unavailability of the Underlying Data. In many cases with these charts, the underlying trend data is unavailable for further review or analysis. This means that the viewer of the chart is sharply impeded from discovering different angles to examine the data (e.g. by combining several factors together in a single chart, or calculating new previously invisible factors as a combination of an original set of factors.) If the original analyst who selected the chart for presentation did not create one chart for each important view, then without the data, these new views are simply unattainable. And of course, it's never possible for the original analyst to provide all the views.
   
6. Data that is provided is Not Readily Reusable (RR). In the relatively small number of cases where the raw trend data is provided, it is painful and time-consuming to transform these data into an RR format. This slows down the effort of understanding and because of the time involved, only a small percentage of potentially interested parties ever actually make these transformations.
7. Missing Metrics, Quality of Metrics. Many of these sources mention other metrics specifically (presumably because they are considered important) but do not provide trend tables or charts. And all metrics, those that are charted and those that are not, must be evaluated against the quality criteria outlined by Anthony Cordesman as noted in

The Quarterly Report on “Measuring Stability and Security in Iraq:” Fact, Fallacy, and an Overall Grade of “F”

What are the weaknesses of the Combine-Iraq-Trends document?

Answer:

1. Stale Data: Violation of the "Near Real Time" Principle - the most recent data point in all of these charts is November 2006 so the trend series displayed is not as up to date (on January 10th when this data was presented) as one might wish.
   
2. Overly long time frame between samples. Way too few samples. Having a total four samples, one year apart creates a trend table that is quite readable on an 8 by 11 sheet of paper. The price is dramatic loss of vital detail and can lead to seriously misleading conclusions.
3. Data that was originally provided was Not Readily Reusable (RR). We were able to work our way around this barrier and create trend charts from the data, but it was costly in time and will serve as an impediment to further analysis of the data for most people most of the time.
4. Missing Metrics, As we noted in an earlier post, there were many Iraq trend factors that Michael O'Hanlon considered important enough to include is his verbal testimony and in the logic of thinking through what those factors meant, but which did not appear in the attached table of 30 factors. Our view is that if a metric is important enough to mention and use for logical argument, it is imperative that the details of how that factor varies over time are provided for further review and analysis by interested parties.
   
5. Quality of Metrics. As for the case of evaluating the Combine-Iraq-Trends document, all metrics, those that are in the table (and therefore charted) and those that are in the text must be evaluated against the quality criteria outlined by Anthony Cordesman as noted in:

   The Quarterly Report on “Measuring Stability and Security in Iraq:” Fact, Fallacy, and an Overall Grade of “F”How
   

What next steps could help things along and help us move closer to our goal of helping both ordinary citizens and decision makers gain a better understanding of the trends at work on the ground in Iraq?

Answer: We've made some progress, but in many ways we have only just begun. Below, I outline some steps I am planning to take with the goal of taking this up to the next level. If you can assist in any way, I would be pleased to hear from you.

1. Continue to harvest and grow our list of missing metrics and invisible indicators, for example by close examination of Dept of Defense quarterly report or the many writings of Anthony Cordesman on the subject.
2. Create a single composite list of all the factors for which we do not yet have trend data or trend charts but which we think would further aid our understanding if they were to be made available.
3. Make inquiries to the original sources to see if the raw trend data for the key factors that have been identified can be made available for further use, ideally in a readily-reusable form to begin with.
   

The Iraq Situation and Readily-Reusable Data

One of the difficulties I have encountered so far is that the data I would really like to examine first hand is not readily reusable and in some cases is completely unavailable in any form.

The first timeline collaboration principle that you will find on the right hand column of our blog template is:

1. Share the data series with the chart. Make sure it is readily reausable

To the best of my knowledge, not one of the 4 sources we have consulted so far (Brookings Iraq Index, The State Dept's Iraq Weekly Status, GlobalSeccurity, or the Iraq Casualty Coalition) has made the data that they used for their own analysis and charting both available and readily reusable as a spreadsheet or CSV file.

Admittedly some of these sources have shared their trend data series, but the method they selected means that they are not easy or ready for reuse without investing a lot of time and effort.

For example,

• Brookings Iraq Index does include some trend data tables with important metrics and frequently labels the data values on their charts. Not all of the interesting trend data that appears in the tables is translated into a chart in the report. For example, see the table on page 5 of the January 8th report that shows details of the trends in cause of death for US Troops.
  
• The Iraq Weekly Status Report from the State Department does not include any trend data at all beyond what they show in their charts. And the time period covered by the charts they have selected is rather short in most cases. For example the crude oil production chart only covers the last 10 weeks and other charts cover less than a year. Only the electricity chart stretches back to the beginning of 2004
• Global Security includes a lot of detailed trend data in tabular form in addition to and complementing the charts they provide. The range of the data presented tabularly tends to cover the entire period from the start of the war until the present.
  
• The Iraq Casualty Coalition also provides substantial amounts of tabular trend data in addition to their charts and their data covers the entire period from the beginning of the war.

Here's the problem.
Most people (both decision makers and ordinary citizens) are not particularly good or particularly thrilled by the idea of trying to make sense of trend data contained in a printed or online table.

My experience indicates that almost all adults (I would estimate the number at 90% or more) can make good sense of trend data presented in line graphs or bar graphs). On the other hand, I estimate that fewer than 10% of the people have the skills, interest or time to extract basic information from a trend table like the one on page 5 of the Brookings Iraq Index, or the many tables you can find at GlobalSecurity or at the Iraq Casualty Coalition.

What impact does this lack -- this lack of data / lack of readily reusable data / lack of easily viewable trend data for all key factors -- have on our ability to understand what's going on?

The way this plays out is that for 99% of the population, they will get their understanding of the trends from their most trusted source.

For a small percentage of people (I am guessing under 5% of the population), that trusted source might be one of the ones we have mentioned so far in this series on Iraq Trends or a similar detailed view of the situation that provides some depth and breadth and doesn't rely on just one or two metrics.

For this small group, if their source is Brookings, and they spend the time wading through the 30 page report, they will have a good chance of making good sense of the charts that Brookings selected. Similarly if their source is the State Department and if they wade through the Weekly Status report they will get a picture of the trends that the State Department selected but not the ones that Brookings was paying attention to. If their source is GlobalSecurity or the Iraq Casualty Coalition, they will get a good grasp of the charts presented at those sites.

Even in this small group that goes and gets their trend understanding from one of these useful and detailed sources (or other similar venues) a small percentage will dig any further into the tabular data that is available. The reason: primarily lack of time and secondarily lack of experience possibly combined with self conceived notions that reading tables is hard.

My reading is that few in this small group will consult and combine the trends from multiple sources like those mentioned above to get a broader perspective. Of course, if you have been reading this series of posts, we have done some of that lifting work for you and made it easier (still not easy in my opinion) to become more widely informed of the composite set of trends that are considered important drawn from a mix of analysts who may have vastly different axes to grind.

For a good portion of the rest of the population beyond this small group, the trusted source for trend data will turn out to be television and other mainstream media. Based on what I have seen from the MSM, this group of individuals will likely be exposed to quite limited trend information in any form and will often end up only being exposed to non-specific, non-numerical statements about the situation on the ground.


What to do? What to do?
Glad you asked. The answer for me is straightforward: ready reusability.

Ready reusability for the Iraq Trend data is easy to say and hard (time consuming, error prone) to do right now. In the next couple of posts, I will give you an example of what I mean by transforming some of the tabular data from expert sources into a readaily reusable form. Once the data is ready to go, I will provide some examples of why I think this is so important.

Timeline Collaboration Principles

The initial starting belief of this Change Over Time blog is that if you want to change the world, the best approach is to build better tools and then learn how to harness their power.

Peter Drucker tells us that FOCUS is the key to success and we follow his advice with a focus on timelines and trend data that tracks the areas of our lives that are most important to us. A key to unlocking the meaning of these data is a continuing search for the tools and methods and principles that best help us analyze, visualize, report and discuss our findings. We are on the lookout for tools that simplify, clarify, and especially those that save us time as we share our findings and collaborate with expert and non-expert alike. We wish to discover what the data means for us in our lives and what actional steps we might take for making the world a better place.

Why do we focus on trends and timelines?

First: Timeline data is often widely available for a substantical collection of key measures in every area of human interest. We are simply overflowing with such data. Where it is not available, it appears almost always possible to create a new data collector that will gather the missing metrics.

Second: Our observation is that most of the time, the available data is not put to its best use as key principles that would guarantee success are openly violated. Lots of opportunity appears within easy reach.

Third: In one domain after another, we have been establishing and documenting proof that substantial improvements in how we use trend data are already available or well within our reach by following a straightforward set of rules and principles and we can point to a growing number of examples on the web that show these approaches in action.

Fourth: In some cases, the existing work makes collaboration (especially between expert and non-expert) somewhat easier, but the collaboration aspect of making best use of trend data does not seem to have been actively explored. I believe that a handful of principles and standard practices can help us learn how to collaborate better by at least an order of magnitude. As we do so, we will advance towards having better and better control for shaping the future and achieving our fondest dreams.

Limited examples of how to use trend data more powerfully are popping up on the web. One of our goals on this blog is to find these examples of excellent practice. We want to use these best practices as models for what is possible if the underlying principles were applied to other domains and trend data collections. For example, we gave some examples drawn from the St Louis Federal Reserve Bank's interactive trending capabilitites named FRED. Other examples can be found at The Big Picture , the Bureau of Labor Statistics, Bureau of Justice Statistics , and Professor Pollkatz .

Here are the TimeLine Collaboration Principles that I believe are going to prove most important to the goal of this blog of making the best use of trend data. We have already discussed some of these in previous posts and will be preparing additional posts for these principles to explain the logic behind them in greater detail.

1. Share the data series with the chart. Make sure it is readily reausable
2. Multi-dimensionality is key
3. Data set includes entire time range even if chart doesn't
4. Explain how calculated quantities were obtained
5. Make sure the explanatory text is in close physical proximity to the trend chart
6. Data + Charts + Text creates a full package that encourages further conversation
7. Ask the expert in the subject matter domain: What are the most important factors?
8. Then, make sure you measure and record and create a timeline history of every one of these
9. If you have the most important factors, you'll find charts with but a single variable still tell a powerful story
10. Make sure the Axes and Titles and other text graphics are easily readable