Why? What? When? Where? Who? How?
These are the basic questions to answer about Community Analytics (CA). They are typical journalistic questions ... and the answers are quite simple.
The prevailing system of metrics ... financial accountancy, market indexes, economic indicators, etc. ...
has become deeply flawed at the the organizational level, the capital market level and the macroeconomic
level. The flaws have compounded over time with disastrous consequences, and by 2008 the capital
markets became paralyzed and the economic system froze like an automobile engine without oil. CA is
needed because there has been a complete breakdown in the system used for analysis of organizational
performance and the economic performance of society.
The measurement of economic growth is one important metric for the capital markets ... but
the metric has become quite meaningless. GNP is Gross National Product ... and product
would normally be an outcome. In modern GNP speak, however, anything and everything
goes into the product ... including profits with no value and costs with no product. It is little
wonder that economic incentives encourage unsustainable behavior!
For example ... GNP
Capital market performance and money wealth have been used as a proxy for socio-economic
performance. Profit and stock price growth has been the primary goal of private and corporate enterprise
with little attention paid to the impact on society as a whole. Excessive reliance on computer models,
simulation and statistics with too little validation is a formula for catastrophe. A good part of economic
data is based on small surveys and a lot of statistics. This system gives good results at low cost in a stable
environment, but falls apart whenever there are changes, and especially disruptive changes. Modern
financial accounting has failed to get money capital allocated efficiently to solve the world's critical issues
... endemic poverty ... poor health ... lack of education ... basic services ... etc.
What gets measured gets done
The system of metrics must measure what is needed so that good decisions get made and resources are
allocated in the best possible manner.
Socio-economic performance can be improved materially as soon as bad practices are stopped. Scams,
rip-offs, shoddy goods and services, thievery, corruption are bad practices that CA can help stop. Socioeconomic performance can be improved when there are good, reliable on time data that decision makers can use. Taken together socio-economic productivity can be improved by an order of magnitude ... with
everyone a beneficiary ... and with the planet more sustainable.
A paradigm shift to CA puts the socio-economic performance of everyone on the same playing field and
using the same system of keeping score. The progress of 3 billion people who are poor can have the same
visibility as the 3 billion who are economically middle class or the economic elite.
Under the CA paradigm, information is used not only to do score-keeping ... but also to guide decisions
and the deployment of scarce resources. CA embraces the idea that what gets measured gets done as well
as the idea that management information is the least amount of information that gets the best possible
decisions made reliably.
Information that makes it possible for 3 billion people to improve their productivity by $300 a year ...
about $1 a day ... is an improvement in the 33% to 100% range. This is huge. A similar absolute
improvement at the top of the economic pyramid would be hardly noticed. But with unemployment in this
demographic increasing exponentially ... it is now time to address the critical metrics of society so that
wealth is not accumulated in one segment of the population merely by scamming the other segments of
CA has two roles:
CA is a structured system of data collection and analysis to enable a paradigm shift in the way socio-economic performance is measured. CA is score-keeping for the game is life ... and the pursuit of happiness ... and the playing field is the community.
- score-keeping; and,
- data for management information that facilitates improved performance.
But CA is only score-keeping and statistics ... and is neutral. It is not a rule making authority like the
National Basketball Association. It is not a referee that ensures the game is played by the rules. It is not a
coach that gets the team ready for a game and calls the plays. It is not a player. It is not a spectator merely
getting entertainment. It is not an owner that benefits from the outcome of the game ... or a gambler trying
to profit from a wager on the outcome of the game. CA is independent and its score-keeping and data are
to be trusted. Score-keeping is more than determining the game winner ... there are also a whole range of
Examples of scoring systems
CA score-keeping and statistics builds on many of the concepts already developed for corporate
accountancy and management information and for economic indicators. Accountancy has great power
when used well to organize data for financial and operational analysis ... and with CA the reporting entity
becomes the community and not the organization and the critical key stakeholder are the residents of a
community rather than the stockholders and management of an organization. CA aims to have no
opinion ... its goal is merely to collect data and analyze data so that better decisions can be made about the
use of resources for socio-economic progress.
- Golf: The number of strokes used for the round. Lowest number wins.
- Cricket: Number of runs. Largest number of runs wins.
- Tennis: Numbers of winning points wins a game. Most games won wins a set. Most sets won wins a match. Most matches won wins a tournament.
- Baseball: Number of runs. Largest number of runs wins. The system of runs is quite complicated, but simplifies to number of runs to determine the winner.
- Soccer: Number of goals scored.
- American football: Number of points scored ... with points assigned for different winning actions: touchdowns, conversions, field goals, etc.
CA is score-keeping. It is not the rule making authority like the National Basketball
Association. It is not a referee that ensures the game is played by the rules. It is not a coach
that gets the team ready for a game and calls the plays. It is not a player. It is not a spectator
merely getting entertainment. It is not an owner that benefits from the outcome of the
game ... or a gambler trying to profit from a wager on the outcome of the game. CA is
independent and its score-keeping is to be trusted.
CA, however, does more than just keeping score. CA also handles statistics. With the CA
data and analysis it becomes possible for everyone to know a lot more about socio-economic
performance than would be the case without. In sport, the score determines which team wins,
but the statistics of the game show which players contributed the most to the result.
CA is grounded in some very old basic concepts of accountancy and measurement ... but also embraces
21st century technical possibilities. In simple ... perhaps simplistic ... terms, CA is like Facebook except
that the central focus is a physical community rather than “me”. With CA, the connections are not “my”
friends and interests, but the people, organizations and issues that influence or impact the socio-economic
performance of the community. CA is structured so that the data about a community is organized in
useful ways, rather like the way corporate accounting information is organized into accounts and different
datasets that make it easy to understand corporate performance. CA uses some of constructs that make
corporate accountancy powerful ... but does not limit itself to just money transactions, but also embraces
activities and initiatives that affect socio-economic well-being.
CA is a timely system ... data are collected as quickly as reasonably possible and fast enough so that the
data still has high value. The value of data usually diminishes with time. Time matters. The very idea of
progress implies something about time. Are things better now than they were? The CA system helps
answer this in a simple but quite rigorous way.
Changes over time are a critical measure of progress. The history of change may be studied at leisure ...
but the data about changes that are taking place now is most valuable when available in a timely manner.
Management information needs timely data in order to be useful.
“When” is a data a element that helps to establish causality. Quite simple time series will often show
useful relationships without the need for complex sophisticated analysis. Without paying attention to
timing, analysis may suggest causality that is impossible. Without appreciation of changes that naturally
occur over time, such as seasonality, simple analysis can easily result in very incorrect conclusions.
Changes over time are very helpful to understanding what is going on.
Where conditions change from day to day the data should be collected daily. Where conditions change
more slowly, the data can be collected less frequently. The key is to collect data so that the results of data
analysis are “in time” for good decisions to be made when they are needed.
This story illustrates the vital importance of timely information. Most of my career I have been
associated with corporate accounting, consulting, planning and the analysis of performance. I have not
done many line management assignments ... but in this case some years back I was appointed VP
Manufacturing for Southern States Inc, a manufacturing company making air-break switches for the
electric utility industry during a reorganization to improve the company's results.
Production Reports at Southern States, Inc.
The company had orders, but the factory was a bottleneck ... and we had neither the time nor the
money to invest in expanded manufacturing facilities. We had to do better with what we had. For
years the factory production report had been written up and distributed every day around 10 am ...
informing everyone of the production numbers for the day before ... a fairly standard practice! I
changed this to give management a report at 8.30 am (the factory got started at 7.30 am) about the
anticipated production for the day ... today, not yesterday! By 9 am the support staff were deployed
fixing problems that would improve performance today! The factory always beat its anticipated
production ... and the factory production almost doubled without any major capital investment to
expand the capacity!
Having datapoints associated with time makes it possible to do time series. Tine series show how things
are progressing or regressing. 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!
CA is about a place ... any place ... anywhere ... everywhere! The good thing about a place is that it has
perpetual existence. A place never moves ... there is a basis for longitudinal comparison that is reliable.
Example: Okehampton in England
I grew up in Okehampton ... a small rural market town in the southwest of England. In 1935 it had a
population of around 3,500. In the 1950s the population was something around 4,200. Back in the 11th
century when the Doomsday Book was written up after the Norman conquest, Okehampton had a
population of around 600 and was an important frontier town. Things changed ... but the place has
kept on going.
CA has a focus on community. CA recognizes that there are big differences between places ... and even
similar places have a myriad of subtle differences. Focus on the place ... gives clarity at the community
level. At the national level, it is, perhaps, possible to understand something about the “state” of the
national economy, but rather little about how and why the economy is in this state.
It is possible to do management by walking around at the community level ... and there is no need to rely
on sophisticated survey techniques and statistics that have been popularized in academia and research
institutes and provide surprisingly unreliable management information. Community level data start to tell
something or real importance ... and it becomes possible to see what are the factors that have resulted in
the state of the community. If something in the data is surprising ... data at the community level helps to
pin-point what caused this and why and how this came about.
Some communities are too big and complex to be easy to understand ... in which case the neighborhood
may be a better level for detailed data. Common sense applies. In some cases it may be appropriate to get
data at the block level. In high density urban settings, the block may still be quite a large population, and
the economic activities quite complex.
Community is a place ... and all communities should “add up” to a larger place, that my be a district, or a
state, or a country. In this perspective of community there is no spatial overlap. Within a community there
may also be neighborhoods ... and within neighborhoods also blocks.
Community may also be based on a group interest ... an affinity group. This may overlap the community
defined by geographic area. A note of caution ... the “roll-up” or aggregation of affinity groups is
complex and should be done carefully and rarely used as a national or global aggregate.
The mosquito has a short life span ... but the malaria population grows fast when conditions
are favorable. Killing mosquito larva is an effective way to limit the mosquito population,
but larvacides are expensive. The cost of source control is minimized without reducing
effectiveness when larvaciding is done in the right place and at the right time.
When and where example: Malaria ... Vector Control
Killing adult mosquitoes can be done using ultra low volume (ULV) spraying ... but it is
most cost effective when spraying is done only where and when it is needed. Data that shows
the stage of larva development ... and the size and location of emerging mosquito
populations collected today ... determines what should be done and where in the next 24
hours. The is a spatial element and a time element. Today's data determines what we do
CA is for everyone ... and CA is facilitated by everyone. CA may be implemented through an
organization or not ... but the data still reflects a community perspective, and the data are neutral and aim
to merely reflect community reality.
While the family is one of the key units of society ... and within the family the well-being and happiness
of every individual is important, for the development and management of public policy, the community ...
or neighborhood or block ... is easier to use as an indicator of progress and the effectiveness of
interventions. There are some datasets that are best compiled using the family as the unit because this is
the best place to identify impact ... as for example, the case of public health, where interventions are
undertaken in the community as a whole, and the impact is best observed within the individual families.
There is a critical need for the data to be credible and for this there has to be a component of
independence, but it is still possible for those with an interest in the outcome to be a part of the process of
data accumulation, but they must never be the sole source of data. The data may be contributed by anyone
... and data may be validated by anyone. The data may be used by anyone who is working to improve
community progress. There is a “weighting” of the data based on the credibility of the contributors ... and
access to data is also controlled to reduce the use of the data for inappropriate purposes.
CA is best when the results are independent of the participants ... when the data are neutral. So while
anyone may contribute to the CA dataflows, there is a set of internal checks to ensure that the data and
analysis are NEUTRAL, objective and independent.
CA is both a comprehensive framework and a modular framework. As a comprehensive system,
everything is included. As a modular system, important matters can be addressed with limited resources
and high impact benefit realized at a modest cost.
While there are many initiatives to improve the reporting of organizations, and an established framework
of macro-economic indicators ... there are few initiatives that address socio-economic performance from
the perspective of the community.
CA becomes possible because of many low cost ways there are now for collecting and storing data, and
for its analysis. The structure of social networks is supported by an IT infrastructure that could also be
used for CA data. Social networks make it possible for people to interact in ways previously impossible ...
CA and social network infrastructure makes it possible for everything of any relevance to a community to
be on the record and in place where it may be used usefully.
There was a time when data collection was a very costly exercise, but much less so in recent years with
better and better technology. Modern web based IT and cellular phone based text messages make it
possible to have data collection that is timely and very low cost. Massive amounts of data can be stored
and mined for critical information rapidly and at low cost. Cost effective technologies are being used to
the greatest extent possible to make CA not only effective but also affordable.