We Need a Clean Slate Analysis of the Economy and a Road Map

I've just watched The Yes Men Fixed the World (P2P Edition). The synopsis:

THE YES MEN FIX THE WORLD is a screwball true story about two gonzo political activists who, posing as top executives of giant corporations, lie their way into big business conferences and pull off the world's most outrageous pranks. This peer-to-peer special edition of the film is unique: it is preceded by an EXCLUSIVE VIDEO of the Yes Men impersonating the United States Chamber of Commerce.

The fact that they are putting forth is things in their country (USA) can be done much better but there is absolutely no political will to do so. I surmise that this is due the socio-economic state being stuck in a "local-optima" of sorts. More specifically it is a point that looks like its on the Pareto front, but may not be on it. Look at the following indicative production possibilities (Black Region) for a given economy with a given set of resources.
Economies attempt to increase efficiency by progressing up and right within the production possibilities, where one group can be made better off without making anyone else worse off. It's not possible to stray out of the set of production possibilities (those are "possibilities" after all). Economies can only progress along a continuous curve. Therefore to get over the "Humps" in the Pareto frontier, considerable sacrifice may be necessary. This is not easy.

Free market advocates say that economic shock (disasters) are "useful" for producing economic progress. Economic progress, on the above diagram, entails helping getting us over the humps. Disaster based "shock" enables this by shaking the economy so far from the Pareto optimal frontier (into the production possibilities set) that it ends up to the left and below the hump, from which it can progress up and towards a more improved economy. But is "shock" truly the only way?

Future envisionings exist that show, in reasonable detail, how the options for a possible future, given the current state of technology, would be better than those that exist today. On the diagram, technologists in a world of Region 1 or 2 might be able to envision Region 3. The question is how to progress on a continuous trajectory towards it. (Let's not nitpick how the regions are depicted and whether they are the frontier or the area, I used MS Paint to draw it.)

The fact is, it is politically difficult to move towards it. Asking constituents to make sacrifices is difficult. However, it might be possible if there was a (public) road map with projected progress towards that future (over time) being charted.

We need a clean slate analysis of the economy, independent of where we are today, to show where we can go. Then we need a road map to show in detail how we might get there. Finally, we need to move in that direction with will and conviction.

The one political point I want to make: The situation with renewable energy (as brought up by the movie) falls squarely into this category. On 27 Jul 2010, the US House Majority Leader unveiled the "Clean Energy Jobs and Oil Company Accountability Act" with the two most powerful clean energy provisions missing: a cap on carbon emissions from the electric power sector and a national Renewable Electricity Standard, which would require utilities to generate at least 15 percent of their electricity from renewable sources by 2021. No doubt, this was influenced by the old economy energy firms (fossil fuels) that are now rich with the pickings of their full product life cycles and using these resources in a harmful attempt to extend these life cycles via lobbying. The Aug 2 - Aug 8 2010 edition of Bloomberg Businessweek warn that this will result in USA losing out to China in the renewable energy race. (In the above framework, China's economy might be operating at a point left and below its hump, which its status as a "developing" power might support.)

In summary, a clean slate analysis reveals the possibility and what we must sacrifice, over some time horizon, to get there. A road map is a plan to get there. Political will and awareness of where we are going will get us there. Visibility of where we at all times in the process are will help maintain that will.

Road Congestion: Physical Limits vs Information-based Orchestration

On 1 July, the Straits Times published a report titled "ERP system: From gantries to satellites" describing LTA's intent to invite technology firms to test such a system next year.

The article notes that the new system "will allow LTA to extend its ERP coverage to congested roads anywhere on the island, without having to install more gantries, which cost about $1.5 million each" and that "the system can be adjusted so that motorists pay only if they are approaching a section of congested road. The in-vehicle unit can also be used to notify them that they are about to enter a stretch of road that attracts a charge".

However, a rudimentary analysis of our transportation system would lead one to conclude that given its current characteristics (that is to say: road network, vehicles on the road, etc), road congestion is highly insensitive to information-based methods of congestion reduction such as ERP.

There are physical limitations to the level of throughput a given infrastructure can provide. Even if we were capable of optimally orchestrating traffic (centrally routing all vehicles to ensure optimal performance for the transportation system), a network of heavily jammed roads would be better ameliorated by, for instance, widening a few major roads or reducing the number of vehicles on the road.

In fact, a study of the major means of transportation (bus, train, private vehicle) would clearly show that the current transport infrastructure is operating at or close to its limits. The promotion of information-based systems in tune with building an "information economy", but we should not lose track of reality, bearing in mind that it is the physical system providing the service. When a system is operating near its limits, its capacity should be increased or its load decreased. Only where an information system can be shown to provide a clear improvement in throughput should any investment be made. Currently, both satallite and land-based ERP fail this test.

Contrary to the claims of the July 1 report, it is not the gantries that have hit their limits, it is the road network.

On Simulations and the Future

Simulations are interesting things. They are the business world's stock tool for understanding and conducting dry dry runs of proposed operational plans. They have little of the analytical beauty of the analytical trajectory of a dynamical system, but businessmen do not bother about matters like that.

The question is whether simulation is a tool that will be able to cope with future demands of it, in view of the future. This little note seeks to highlight some thoughts I had while discussing the matter on the MIT alumni Linkedin discussion board.

Computational Workload
Computational complexity is always a problem. Even when simulating rational human decision making, let's say where a simulated agent has to "make a choice" the simulation solves a convex optimization problem (may be a linear program), solves a dynamic programming problem, or perhaps uses some search algorithm to arrive at a decision. This can be computationally taxing.

Where things are probabilistic, you need about 26500 monte carlo samples to ensure that the probability that the empirical distribution resulting from the simulation is more than 1% off is at most 1%. That is painful.

I recall that on one of the evenings when I was heading home from campus on the "Big Silver Van" one of my housemates quipped that it was interesting how things deemed to be interesting were usually at least in the NP complexity class. This probably would summarize much of the difficulties in embedding decision making into simulations.

Complexity issues hurt and linear speedups and improvements do not look to help as the demand is for growing sophistication. A successful simulation study requires discipline in modeling to avoid being swamped by complexity and ending in failure.

Business Matters
In the business world, simulations make sense of the effects of a proposed set of operations under some dynamics and under uncertainty. Indeed, projects these days tend to phrase requirements to the tone of "... shall report the service level with 99% accuracy" which is an appeal to the use of monte carlo algorithms rather than simulations of the single run deterministic variety.

Of course the bulk of simulations in engineering remain the "this is my structure, here are my loads, will it break?" type, but to a very large extent, problems in that regime tend to be of "low complexity" in terms of the rate at which workload scales with desired accuracy.

An interesting point was also raised on the board:

"When a sim can let me add and subtract new variables as quickly and easily as a spreadsheet, then I get interested."

To get customer buy-in for a simulation, it has to be easy enough to use in order for him/her to quickly and intuitively vary operational parameters that he/she should be familiar with (it's the customer's operation, after all). Interface complexity is another thing that has to be managed in view of increasing demands for sophistication in simulation.

The Customary Conclusion
Simulation has its work cut out for it, its future success requiring control of both computational complexity and human interface complexity. It will be interesting to see how things go.

On Education: KPIs and Human Behavior

In view of recent comments in the ST forum on education ("Remember the true value of schools", "Reward effort as much as results", etc), I'd like to make a proposal coming from a slightly less orthodox angle.

To cut a long story short, based on their observed actions, teacher KPIs appear to be based on a test score metric. Management often only sees numbers and assumes that all is well. However, proxy metrics are only proxies, and in extreme situations they may lose their association with the value they purport to represent.

No matter what people claim about the public-spirited virtue of educators, they are human — intelligent ones at that — and respond very keenly and creatively to incentives. The pursuit of rankings and test scores is a natural response to KPIs being set in that direction. The unintended fallout are, unfortunately, the well-established phenomena of forcing students to drop subjects they are less than excellent at, the trivialization of non-classroom activities and the subordination of such activities to those of a more test-relevant nature. It was almost as if educators were told: "This is the syllabus; and this is the rewards and remuneration structure. Now get to work." I understand these statements are blunt and unrefined, but they capture the gist of the situation.

While test scores and other KPI aligned measures have improved greatly, it is a fact that unintended consequences have cropped in due to the process of chasing incentives — a naturally arising optimization process. Here "optimization" is the process of making decisions so as to maximize some measure of performance and or minimize some measure of undesirability subject to certain constraints. As a practitioner of quantitative optimization techniques, I would like to state that optimization is an unintelligent process that has to be guided by an intelligent user. An example from the distant realm of finance may shed more light on the situation. When practiced naively, portfolio optimization performs poorly. This is because, incompletions in the data used to guide the process are maximally exploited. This results in a proposed portfolio that would have performed well in hindsight, but severely under estimates future risk. (The pure naive form is beautiful theoretically but needs to be embellished before it is roadworthy.)

Sociologists have proposed that when dealing in the "economic realm" (with rewards and remuneration, for instance), individuals have a tendency to make cold rational decisions. Analogous to the unintended consequences of our education system, the example from finance shows how omissions are exploited in a raw unfeeling optimization process.

Unintended consequences creep in to any well meaning statement of value. For instance, as much as I love the sentiment behind rewarding the hardworking, the execution of such a policy is literally fraught with (economic) peril. Effort should not be rewarded as much as results, as it gives students an incentive to put on a show instead of directing their efforts at improvement. I believe the well established term is "wayang". Promoting a culture of "wayang" would be counterproductive and harmful to our economy. We cannot give up the desire for a culture of performance, but it is important that the pursuit of a proxy to the abstract notion of "performance" does not retard the achievement of less quantifiable true goal. Scores alone are a poor measure of effectiveness; I'd like to suggest something a little more nuanced.

I'd like to propose using a type of metric that balances various factors such as (student) appraisal (as a proxy to "students feeling they got something out of the class"), captures the tradeoffs involved in working to achieve the various ends of education and promotes the centering of the actions of teachers to give students a more well rounded experience (which some theories of education tout as superior).

In the graphic below, effectiveness has been presented in the form of indifference curves. "Higher curves" indicate greater effectiveness. The green dotted lines indicate that for the "focused" teacher to progress in the assessment scale, there are minimal achievements in each attribute for each assessment level. This combats lopsidedness. The asymmetry in the minimal-effectiveness-for-progression boundaries captures the fact that we are a performance culture, and that must be foremost in the minds of teachers. In this manner, evaluation-optimizing teachers may straddle the green lines, but the evaluation structure limits the damage of their optimization. (In the diagram, only a (10,10) achieves effectiveness level 10, the true master teacher.)

Such a metric may be extended to multiple criteria. The curves here are of the form:

(Effectiveness)² = (Metric 1) x (Metric 2),

the natural generalization would be

(Effectiveness)ⁿ = (Metric 1) x (Metric 2) x ... x (Metric n).

Another practice in optimization has been to constrain solutions to take a particular form; at times to preclude undesirable behavior and at times with the explicit aim of making them robust to the slings and arrows of outrageous fortune. On the latter, it seems that "robustness" to the onslaughts of the real world is well correlated to "experience".

Less quantitatively, I'd also like to mention that there should be requirements for the education process that ensure that students have had a prior "experience set", leaving the system, as evidence of exposure to certain situations. This would increase the likelihood of a "robust response" to changing situations on the part of students. This would of course represent additional teaching workload and the question arises of the marginal benefit of this and whether it should displace something else. This is very much in line with the "Desired Outcomes of Education" expressed by MOE. This is considerably harder to design well.

Set up a well thought-out optimization problem, and make sure your solutions are robust.

Fertility: Just Mine the Data

People have been talking about fertility in Singapore. Raising issues like how the "Baby bonus has had little impact so far" and how the economy discourages working women to have children.

The fertility problem of may well be causally structural in an economic sense, and a solution like the baby bonus may or may not be the solution to the structural issues, depending on whether the incentive addresses fundamental underlying issues.

The Economist recently published an article titled "The best of all possible worlds?" (Economist, Aug 6th 2009). The article contained a section relating the Human Development Index (HDI) to total fertility rate (TFR). The HDI, taking values from 0 to 1, is a measure used by the United Nations. It has three components: life expectancy; average income per person; and level of education. The TFR is the expected number of births per woman over a lifetime.

Graphically, the data appears well fitted by a J-shaped curve that bottoms out in a trough of a less than 1.5 TFR at HDIs between about 0.85 to 0.92. (Based on 2006 data, Singapore had a HDI of 0.918. This corresponds to a total fertility rate of under 1.5 on the fitted curve. In 2006, Singapore had an actual total fertility rate of 1.06.) Let me just plop the image here.


The excellent fit suggests (and may be said to validate the statement) that structural issues strongly dictate fertility levels. This makes sense as the structural conditions of an economy have a major impact, in aggregate, on the decisions that individuals make.

In so far as encouraging parenthood is important to Singapore as a nation, it is necessary to understand what really drives decisions to or not to have children. While one may explain the strong trend as a shift in attitudes due to changes in the economic environment, details are needed in order to craft economic policy. This suggests the need for more detailed study. This would mean, at the very least, de-aggregating the HDI to pinpoint how each factor (education, income, life expectancy) affect fertility and going beyond that.

Public policy relating to parenthood is largely within the purview of MCYS. Unfortunately, it is not staffed sufficiently with economists or statisticians who have the necessary training to mine the data. I would suppose the government's Economist Service would be better placed to lend a hand.

This would at least put more quantitative substance from the real world into the policy discussion. While anecdotal evidence has the most heartstring-tugging appeal, it is statistics that we need, and soon. Alternatively, we could do whatever it takes to increase our HDI and hope for the best.

On Intent

In organizations, we have people supporting projects wherein some people do bit parts under the direction of more senior people. That is by and large the case. Many a times, junior team members feel disconnected from the project, not engaged at all to their work. In most instances, this boils down to one thing, one thing that took me a long time to learn to ask.

What is the intent? What is this project intended to achieve? This section my team is working on, how does it serve the intent? This sub-section I am working on, how is it helping? Only if one sees and takes in interest in the larger objectives of a project can one be engaged. Only if one understands the aims of his task can one truly be effective.

It is interesting how long it takes to learn a simple lesson. I've observed that the public sector, from a broad historical perspective, acted very much in line with WW2 Germany's Auftragstaktik (which was cited as the reason for the superiority of the German's warfighting ability to that of the allied forces). Subordinate commanders were given a clear picture of the intent at a higher level (i suppose sometimes 2 levels higher) and were given leave to act independently, given that clear understanding of the intent of each engagement or campaign.

Before I entered the public service, and at a time where it looked like I would join a ministry, it was hinted to me that I should look into past policies to understand their intent before crafting reports and policy papers. It took a while and some observation to realize how things worked in the public sector.

Today, at lunch, it was pointed out that junior engineers feel disengaged. And anecdotes arose as to how things fail to work. They boiled down to ineffective transmission of intent. The Singapore public service is huge, yet it is far more effective than those of other countries. Yet, as the anecdotes suggest, there is room for improvement.

The question then is, what measures can be taken so intent can be effectively transmitted? This is very much doable, but takes will. A tougher question relates to the transmission of intent where security and secrecy is a concern.

Force Structure Amid Transformation

We are in the process of a massive transition. We are moving to a 3G SAF, with this and that and this capability. Of late, we have seen the addition of new equipment to our arsenal which promises that we will be able to deliver more hurt with greater precision and with a lower prospect of getting hurt ourselves.

Old equipment is being phased out, nearing the ends of their system life cycles. As we progressively undergo greater and more rapid change, the issue of training and knowledge retention arises starkly. This is particularly true if the pace of technology dictates that system life cycles have to be re-examined (in particular, shortened).

The NS Man, may have to learn to operate a number of different weapons systems as his old expertise becomes obsolete in the face of rapid technological change. Instruction is a problem, do we have the manpower with the expertise to conduct instruction. I propose a modification of our force structure to accommodate this need.

Consider forming some battalions consisting an evergreen crop of NSFs and rotating NS Men, lasting the lifetime of the NSFs liability. In those battalions, NSFs aid in the training of their NS Man colleagues in newer weapon systems where needed. Teaching another is perhaps one of the most effective means of reinforcing and understanding what one has learnt. The training workload will be effectively shared. Furthermore, we accrue a further benefit. Younger NSFs will become more connected to the pulse of the country through interactions with NS Men who have been working and have seen more of life in Singapore. They will benefit from the experience that their older colleagues share. This mixing of young and old may have other social benefits such as bringing younger Singaporeans closer to opportunities such as jobs, and opening them up to possibilities that otherwise may only be observed with the benefit of personal experience.

In addition to this, hardcore expertise is needed to effectively harness the potential of equipment. We have often heard the phrase, "it's not how big or long it is, it is how you use it". Similarly, long range weaponry is only as good as the operator (and can only be as good as its specs, but we'll buy or develop something better if we're in danger of saturation). Centres of excellence/knowledge which give back to the entire organization are important to have for systems that are widely used. I believe in the need for regular battalions to act as centres of knowledge from which master trainers and leaders can arise. These individuals are to be the catalysts for competency development within non-regular units. There already is a movement towards this, but it's value bears reiteration.

Naturally, if this is to work, processes have to be worked out and studied in order to strike a balance between component and integrated training. I successfully pulling this off will be a boost to our overall competency, improve our force multiplier and hence contribute to greater security.

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Update & Clarification (8 May 2009):
I've been told that currently, NS Men are sometimes deployed to work alongside regulars to understand the mind of the regular and doctrinal issues. I envisioned more of some units with NSFs being present for their liability with NS Men entering and leaving (with ICTs remaining short). At times, there would be training, at others, exercises proper. Training in exercising leadership and initiative is something experienced NS Men have to offer, NSFs in turn are in touch with state of the art technology.

Perhaps the greatest benefit I see is not so much operational as social. A connected mindset, where young NSFs are able to "grow up" faster through contact with people who have been in the world. Operationally, this social benefit will create a more engaged NSF population so they see the intended social function of NS. It doesn't matter that most will not see NS as a machine for defending the nation so much as a vehicle for transforming boys to men and an immersion into real society (by meeting people). The fact of the matter is an engaged soldier is a more effective soldier. This is what has been termed a "head fake". Making someone think he is doing something useful to him, while the real intention is for him to pick up skills. This is the idea behind some software for storyboarding (ALICE) where users (kids) think they are making a movie, but are actually learning principles of computer science.

Operationally, the effectiveness of the army is no longer how many can be fielded, as is reflected in the intent of MM Lee when he advocated a conscript system. (Being able to field a huge number of troops after a few years of running the NS system.) Also, technical obsolescence is no longer something the systems architect and master planner can really control. Speculatively, a new coating could render obsolete every radar (advanced or otherwise) in the world, while being developed in secret and deployed throughout an airforce within a matter of a day (or a few days). The cliche that "the rules have changed" is continually in effect at each break through of the arms race that sits in the background of business and commerce.

From this perspective, having a parallel system whereby all NS Men can be brought up to speed rapidly to the state of the art (perhaps at the expense of some aspect of the training of some NSFs) has value.