Financial Executives International – 5th Best in Class Competition

On Saturday, a Rotman team composed of myself, Shree, Fei and Matt Literovich competed in the Financial Executives International 5th annual Best in Class Competition. The case company was HudBay Minerals. Unfortunately, we placed second, behind Alberta School of Business.

The competition was intense, as many of the teams worked late into the night on Friday to put together our decks and get a few rehearsals in before scrambling to get a few hours of shut eye. The next morning, our names were drawn for presentation order and we found ourselves in the seventh spot.

Matt Literovich was phenomenal understanding potential legal issues related to mining and commanded the attention of the room when he spoke of precedent case law.

Fei gave a detailed account of all the organizational issues we could expect as HudBay Minerals grew and followed our acquisition strategy.

And Shree’s knowledge of mining and dissection of potential target companies gave us an exceptionally high level of credibility.

All three were exceptionally strong in both the presentation and the question and answer period and this short description does not do justice to the quality of our presentation.

While we were very disappointed that we didn’t take the top spot, the event itself was challenging and very entertaining. Judges from the competition included top executives from HudBay Minerals, USGold, OTPP, Mercator, a justice and many other top professionals. Definitely a great experience, I would recommend any MBA student to attend this competition.

Revenue Recognition for Large Projects

I apologize for not really discussing Financial Accounting. At the risk of sounding a bit arrogant, a lot of this material (but certainly not all of it - liability recognition percentages for GAAP (80%) versus IFRS (50%) ) has been covered in the CFA level I (for the question that most people ask, should I do an MBA or CFA, this is part of the answer... I should post more on this sometime and why I decided to do both). Plus, as my colleague Megan so eloquently puts it:

"... it is an important and necessary subject, so I may as well learn to love it
because I can't escape it."

Currently, we are discussing different revenue (and cost and profit) recognition techniques for larger projects who span more than one reporting period. The question is how should we recognize these items in financial statements? There are two methods we are looking at: the percentage of completion method and the completed contract method.

The completed contract method is quite simple, where (intuitively) all the revenues are accounted for once the contract is completed. It is more appropriate in scenarios where the contract involves extremely high risks (and may not be completed).

Another method not yet mentioned is the cost recovery method, where revenues match costs until the last period where gross profits are recognized all at once.

[Case] Same as the case in the percentage of completion post:

Assume a construction project with the following construction cost structure:

Year 1: $5M
Year 2: $15M
Year 3: $10M

The overall contract price is $46M.How much profit should be recognized in each of the given years under different methods?

[Solution]
Case 1 - Completed contract method revenue:
Year 1: $0
Year 2: $0
Year 3: $46M

Profit:
Year 1: $0
Year 2: $0
Year 3: $46M - $30M = $16M

Case 2 - Cost recovery method PROFIT:
Year 1: $0M
Year 2: $0M
Year 3: $16M

(Although I don't know what the cost schedule looks like, the revenue recognition will be such that revenues will match and equal costs, until the last year). Note that while the profit schedules are identical in both methods, the revenue and cost recognition schedules are different in these two methods.

Continuing the class after the break, we discussed COGS and Inventory as an extention of the above concepts. Our professor is starting to do a primer (and enter into) the topic of LIFO versus FIFO, one of my top (most popular) posts. And as mentioned before, there are interesting concerns when it comes to accurately measuring performance versus position. Another major issue we are discussing is accounting for inventory costs when they haven't yet been sold, but their value moves with what happens in the market and LOCOM, the lower of cost or market as an accounting standard for both US GAAP and IFRS.

Informal Case Study Preparation Team

As I had mentioned before, we have a small but growing group of people preparing for case interviews at this early stage. While many people are focusing on the academic component of the MBA, those who are ahead are looking for opportunities to prepare for upcoming interviews. While I've often been critical of colleagues who need to "chill out" (sometimes doing work in advance is 'doubling work' rather than 'front loading', such as reading cases too far in advance), I think that those who are aware of the need to understand case preparation earlier rather than later are getting a distinct advantage. For those with little experience in this area, there is always the initial shock value when they realize that case interviews can become very complicated very quickly.

I've been nominated to 'chair' our little informal group as I've had the good fortune of doing case preparation over the recent past and I've been building a list of skills which most people are not aware of as being important for case interviews.

There will be a meeting with the Management Consulting Association (MCA) today to talk about what the club can offer us. They are one of the most expensive clubs on campus, second only to the Rotman Finance Association (I am a member of both). As I have a keen interest in Private Equity and Advisory services (such as M&A or restructuring), I have to decide if I will take the investment banking route or the management consulting route to get to where I want to go.

Rotman Management Consulting Association - 2nd Year Case Comp

Yesterday, there was a second year case comp was organized by the Rotman Management Consulting Association (MCA). I've already paid the fees, so I didn't feel too guilty eating their lunch. It was good to see our second year colleagues in action and get a preview of what case competitions are all about.

There were industry judges from some of the major consulting firms in Toronto: BCG, Monitor, Accenture, Deloitte, etc. I even met a good friend of mine who was judging, now an Associate for Monitor and had a chance to speak with his boss. We had a great chat about consulting and life beyond the MBA.

The actual case was quite interesting, involving the analysis of a product. There were some great insights provided by the groups and I learned a lot about the process of developing a case as well as where to look for opportunities and challenges.

I'm building a team with some colleagues: Neesha Patel and Fei Yu (the only two other first years to show up). Neesha and I had previously arranged to meet up at this competition to start discussing building a team and I had met Fei earlier (we share the same Rotman buddy, another good friend of mine). Neesha was an analyst for McKinsey in India and Fei is from the University of Toronto Skoll Program (like Engineering and Management at McMaster). Both are smart cookies and clearly go getters. We'll meet regularly to practice cases and probably enter into competitions together. Neesha has hinted that she might know two more people to fill the last few spots, and I'm looking forward to working with this crack team.

Chapters Indigo - Model with LBO Module

I've been learning a lot in my courses, but I haven't had a chance to post any good lessons lately because I've been so busy.

However, last night, I took some time off to complete a model using everything we've learned so far. Although the model isn't "complete" (synergies from the LBO are not currently included), this model includes projections, debt schedules, working capital schedules, depreciation schedules, and even a model for leveraged buyouts and valuation.

There are plenty of comments outlining major assumptions in how these numbers were derived. I would encourage you to play with the numbers to understand the relationships in the model work for valuation purposes.

[DISCLAIMER]
While the numbers look "good" (valuations are in the 20's and IDG:Indigo is trading at around $19) this information is provided without warranty as a strictly academic exercise only. Trading on this information is risky (beyond the standard business risk) as well as foolish and reckless.

I am not responsible for you using the model for the purposes of trading or other investment decisions. Consult a qualified financial adviser before making any investment decisions.

Chapters Model with LBO Module

Information for this model is based on the 2009 Chapters / Indigo Annual Report.

[Note] This spreadsheet contains circular references in order to calculate exact interest expense iteratively (using real cash gains from reduced interest expense to further reduce interest expense). Excel is usually configured to allow you to do this, however, you may have to change your settings to allow circular references.

Being Irreplaceable - The Good and The Bad

In my work with career development, I often hear stories of professionals who are quite happy with the fact that they are irreplaceable. They take it as a sure sign that they have job security. While in this economy, there are few who would look a horse in the mouth with regards to that view, in the long run, being too irreplaceable has it's downfalls to.

For those who are upwardly mobile, being irreplaceable should have an upward bias. That is to say that if you are looking for a promotion, you should be looking to add value outside of your position which apply to broader scopes.

Being irreplaceable at lower levels is not healthy for individuals or organizations. To have a foundation which rests on one point is extremely unstable and does no one any good. Also, if you are irreplaceable, there is a strong bias NOT to promote you. Not only is it detrimental but also selfish, as it prevents those below you from organic and professional growth as well.

[Case Study] An administrator for NPO was promoted for her work with a one of the organization's leading programs where she was the program head. She moved into an acting director position for all similar programs while continuing to act as program head for her previous team. She had always been proud of her work and the team celebrated the fact that there was no one people in her staff who could replace her. She had years of experience and knew all the in's and out's of past and running projects, fund raising and soliciting contributions from members.

However, after she received her promotion and new responsibilities across a broader field, her previous program began to suffer. She was repeatedly called back to deal with issues and ended up spending more time at her old position than the new to the detriment of both. After much effort, she finally trained a junior team lead to take the position of program head and was finally able to focus on her new position.

[Case Study] A software programmer was developing a module for communication infrastructure. He was absolutely indispensable as he was the only one who was able to do maintenance on the code due to legacy technology issues. As a result, he was a talented programmer whose skills could be transferred to another bigger more profitable project, however because he could not be replaced, he was passed over.

Finally, when he understood the situation, he went to his manager and put forth a proposal: "If I can find a suitable replacement, will you authorize a transfer?" Upon approval from the manager, and mentoring a junior developer, the programmer was able to successfully transition to a new position.

Profitability Analysis Framework, pt 4 - Sales: Volume, Brand Equity and Positioning

Profitability Analysis Framework Series
[ 1. Overview, 2. Fixed Costs, 3. Variable Costs, 4. Sales, 5. Price ]

A rather important theme that has reoccurred in the last few posts about fixed and variable costs is the idea of quantity sold (sales volume).

At any given price, quantity sold is directly proportional to the total revenue stream for any given product or service.
What are potential explanations for movement in your sales volume? If you find yourself losing market share it could be either because of substitution to another product (entry by a new competitor) or general decline of the industry (less use of buggy whips). Cross elasticity of substitutes can result in lost sales if you are being undercut by a competitor. Another explanation is it could be a change in the social trend (less hamburger consumption and more salads).

Positioning based on the questions above are of the utmost importance and are often based on the following dimensions:

• Price as explained above
  
• Quality - With different dimensions as defined by the specific product (style for clothing, processing power for computers, horse power for cars etc)
  
• Availability accessibility (consumption of cola generally goes up the more convenient it is, hence more vending machines)
• Consumption of complementary and paired products (consuming more cola with an increase in consumption of pizza slices)
  

In growth opportunities, an important consideration is the geographic distribution channels and opportunistic sales. Are your customers able to get your product or service when they need it? Or are they going to your competitors? Do you have adequate point of sales to service your customers needs? What are the hottest geographic areas to locate more sales capacity?

[Case Study] Malcolm Gladwell talks about Airwalk as being a company which became famous for being unconventional and targeted directly towards skateboarding subculture of Southern California. Their advertising reflected a lifestyle which was uniquely different and had a special perceived brand equity. This allowed Airwalk to sell their shoes in boutique stores at prices that were much higher than their "competitors".

However, upon growth and expansion, when Airwalk started putting their shoes in more conventional locations (department stores, etc), their brand quickly became diluted as being too "common" and they lost their luster of being unconventional. What had originally been ironic and trendy and had become rather blasé.

Suddenly, by diluting their brand equity customers became disinterested, and their sales numbers suffered.

Profitability Analysis Framework Series
[ 1. Overview, 2. Fixed Costs, 3. Variable Costs, 4. Sales, 5. Price ]

Using the Right Metrics: Time and Dollar Weighted Returns

When benchmarking the performance of financial consultants and portfolio managers, the realities of life such as demanding withdrawals from financial portfolios and uneven cash flows can make understanding the performance rather murky.

For instance, you may have a need for cash between years or maybe an unexpected windfall which changes how your cash flows from investing affect your current position as well as your investment portfolios overall performance. Understanding this, we should look more closely at time-weighted versus dollar weighted returns.

Time-weighted return is the easiest and is the fairest measure for understanding a portfolio manager's performance. Looking at any 3 given years, assume the following annual returns:

Year 1: 8%
Year 2: 10%
Year 3: -4%

The annual time weighted return is the cube root of the combined returns or:

(1.08 x 1.10 x 0.96)^(1/3) = 1.14^(1/3) = 1.0448 or 4.47% gain

However, if assessing performance becomes more difficult for dollar-weighted return if there is cash flows happening between years not directly related to investment gains or losses (adding or taking capital from the investment portfolio). For example, assuming the same percentage gains, assume the following cash flows:

Year 1: $10M initial investment inflow
Year 2: $3M withdrawal outflow
Year 3: $5M investment inflow
(assume cash flows happen at the beginning of the year)

What happens? What model can we use do understand the dollar-weighted gains? By using a cash flow model (which incorporates gains and losses from portfolio management) looking at what happens between each year:

1. Year 1 Starting Balance:
   $10M
2. Year 1 Ending Balance:
   ($10M x 1.08) = $10.8M
3. Year 2 Starting Balance:
   $10.8M - $3M = $7.08M
   
4. Year 2 Ending Balance:
   ($7.08 x 1.10) = $7.788M
5. Year 3 Starting Balance:
   $7.788M + $5M = $12.788M
   
6. Year 3 Ending Balance:
   ($12.788 x .96) = $12.276M
   

Now you have a more detailed description of the cash flows (including a final terminal cash flow value), you can use DCF in order to determine the dollar-weighted rate of return (IRR @ NPV = 0):

Recall that:

NPV = CF0 + [CF1 / (1 + IRR)] + [CF2 / (1 + IRR)^2] + + [CF3 / (1 + IRR)^3] + ...
0 = $10M + [-$3M / (1 + IRR)] + [$5M / (1 + IRR)^2] + [-$12.276 / (1 + IRR)^3]

Also recall that for accurate reporting, the terminal year is assume to be withdrawn in full. Using Excel or a Financial calculator to solve for IRR, the dollar weighted return. In this example, the result is calculated as 0.943%. Why is this value so low compared to a time weighted return? As it turns out, the investor in this scenario made a few unlucky mistakes:

1. Took money out after an ok year ($3M withdrawal after a year gaining 8%) and didn't capitalize on the upcoming year with 10% gains. The investor didn't gain $3M x 10%. In otherwords, they missed out on $300k in gains.
   
2. Put more money ($5M) in after a good year (10% gains) just in time for a bad year (4% loss or 96% retention). This action lost $5M x 4% or $200k.

It becomes painfully obvious that timing is everything, as someone with a small amount of bad luck recieves a disporportional cut in their investment performance as a result.

A few assumptions / extensions:

• The portfolio doesn't have to be "managed". The time-weighted returns can simply be based on market indicies such as S&P 500 or a portfolio constructed against the DJIA.
• Good timing can reward as much as bad timing punishes.
• There is a liquidty premium in the form of economic opportunity cost (in the case of the $3M being withdrawn for "investor needs", that was unavailble to participate in the 10% increase that year).
  

Profitability Analysis Framework, pt 3 - Variable Costs, Cost of Goods Sold

Profitability Analysis Framework Series
[ 1. Overview, 2. Fixed Costs, 3. Variable Costs, 4. Sales, 5. Price ]

Continuing the Profitability Analysis - Framework and Practice series, part 3 will look at variable costs.
Now our graph gets a little more interesting. Variable costs increase with the quantity sold (more resources such as raw material and labour are necessary for each additional unit). Also, we now have the two pieces required to put together a total cost curve (fixed cost + variable cost). Notice now that the fixed cost is the y-intercept and that the derivative (slope) of the variable cost curve (marginal cost) is the same as that of the total cost curve. These are two critical concepts in understanding how to graph and model cost curves.

Variable costs are directly related to costs of goods sold (COGS) including factors such as labour and raw materials. For any individual product line and for any given factor of production, the total product curve takes an S shape. This also implies that the variable cost curve doesn't have to be (and often isn't) perfectly linear (which also emphasizes the points made above about the slope of variable cost being identical to the slope of total cost).

Assuming managers can select the workers for the job from highest margin to lowest (most useful to least), there is an accelerated growth pattern due to economies of scale. However, eventually, the law of diminishing returns is such that marginal utility approaches zero for each additional dollar of value put into the system. If you flip the x and y axis, you now have a basis for adding your variable costs against your fixed costs.

Regarding specific details for variable costs, this includes many factors of production such as materials, resources and labour. Common themes that affect this area include:

• Cost of materials. If there is a change in the price of raw materials required for production or if there are inventory management issues which cause loses in the form of lost productivity. Also, if numbers are too high, this could be an indication of wastage, theft or some other form of inefficiency.
  
• Cost of resources such as computing power, electricity or oil. Consumption of resources at peak demand often results in inefficient and expensive hidden costs. Any ability to offset or time shift demand could dramatically cut costs and reduce systematic stress and dependency. Also if costs are seasonal or otherwise predictable, financial hedges such as oil futures can insulate the company from short term volatility (although not long term changes).
  
• Increased costs for overtime pay. This could be an indication that labour capacity is too low and that there needs to be more hires. This is directly related to the seasonality of your organization and could require you to outsource or hire more workers.

[Case Study] A factory is manufacturing cars and has a policy to pay it's workers 1.5 x for overtime worked above 40 hours. With it's current workforce and equipment, a particular factory line is able to produce a maximum of 20 cars per day. However, with a recent spike in the car model produced by this factory line, the demand requires production to increase to 25 cars per day.

While the automated equipment does not need to be augmented to meet demand (lines can simply run longer), there needs to be more human labour to satisfy demand. Should the factory authorize overtime or hire more staff?

[Solution] Looking at the solution, authorizing overtime would increase the labour component of cost of goods sold by 50% (1.5x pay for overtime). For 5 additional cars (or an increase of 25%), this would result in an increase of 37.5% of the total cost of labour (25% increase @ 1.5x labour cost).

In order to get the same increase in labour from hiring, they would simply need to hire 25% more labour (assuming no diminishing returns) would cost 25% more.

Using this logic, it's obvious that it would be better to hire more people and pay them at the stated rate than pay 1.5x for overtime.

So why not just always hire more people rather than pay 'expensive' overtime? If this demand is seasonal rather than permanent, having extra capacity will be detrimental if the demand doesn't last (if the demand for these cars evaporates). In this case, you are left with having to pay the salary for employees who are idle.

The premium for overtime is justified if 1. the incremental revenue is higher than the marginal cost of overtime labour (profitability of marginal units is positive) 2. the demand is temporary and doesn't justify increasing the permanent labour force.

Profitability Analysis Framework Series
[ 1. Overview, 2. Fixed Costs, 3. Variable Costs, 4. Sales, 5. Price ]

Recursion: Boot Strapping Forward Rates Extended

In the CFA curriculum, one topic which is covered is a method of boot strapping in order to find forward yield rates based on Treasury (risk free) securities. While the CFA level I text looks at how to boot strap between years to determine basic 1 year forward rates between different years (based on posted rates), let's have a look at what else we can do with the same concept but more applied math. First the basics:

Assume that the following stated yields and horizons:

[y]f[r] --> Notation
I can't remember if this is the official CFA notation, but I'll use this:
y - year (0 is current year)
r - rate for r years into the future

0f1: Current 1 year bond rate: 3.5%
0f2: Current 2 year bond rate: 4.6%
0f3: Current 3 year bond rate: 3.8%
0f4: Current 4 year bond rate: 4.2%

(I've deliberately put rates all over the place to illustrate some points. Plus these rates are rather high given the current economic conditions, but for the purpose of illustrating the math that won't matter). The CFA points out that it is possible to find out the forward rates between any two years by doing "boot strapping":

For instance, at the two year rate, the gain is compounded over two years (4.6% compounded twice over the two years or (104.6%)^2 = 9.4% gain).

At the three year rate, the gain is compounded over three years (3.8% compounded three times over three years or (103.8%) ^3 = 11.8% gain)

To determine (by approximating an arbitrage free value that shows expected interest yield increases) what the forward one year rate would be between the second and third year, you would take

(1+0f3)^3 / (1+0f2)^2 = (1+2f1)

Now let's extend our notation and math. Notice that there is a recursive element involved here:

For any given year and rate:

(1+yf1) = (1+0f[y+1])^(y+1) / (1+0fy)^y

That is to say that the 1 year forward rate for any given year, y, can be approximated by the total return from the current year to year [y+1] compounded (y+1) times divided by the total return from the current year to year [y] compounded y times. Notice in this case, we have deliberately selected a difference of 1 year (a 1 year forward rate) to keep the math simple.

Extending the formula to solve to generalize for yfr (any case):

(1+yfr)^r = (1+0f[y+r])^(y+r) / (1+0fy)^y

Now we have a formula which can approximate for any given year and any given period of time (assuming that you have all the current rates available). This formula says that the total gains achieved using the rth year forward rate for any given year, y, can be approximated by the total return from the current year to year [y+r] compounded (y+r) times divided by the total return from the current year to year [y] compounded y times. This is the ultimate case, flexible to encompass any starting point and any duration.

Let's try this for 2f2 (this should be the two year forward rate in two years):

(1+2f2)^2 = (1+0f[4])^(4) / (1+0f2)^2
= (1.042)^4 / (1.046)^2
= 1.179 / 1.094
= 1.078

The total gain over the two years between years 2 and 4 is expected to be 7.8% (or 3.8% compounded each year). Note that this seems to be in the ball park as the rate is lower and that the further into the future the larger the effect of the compounding is reduced for the 4 year rate versus the higher rate at 2 years.

Profitability Analysis Framework, pt 2 - Fixed Costs: Capacity and Investment Decisions

Profitability Analysis Framework Series
[ 1. Overview, 2. Fixed Costs, 3. Variable Costs, 4. Sales, 5. Price ]

Total costs are composed of fixed costs and variable costs. In this post, we will decompose total costs and focus on fixed costs. Fixed costs are composed of assets for whom increased production does not influenced total costs and includes items such as administration, sales and marketing, land and equipment. Fixed costs usually involve some form of previous investment decision (having financed the purchase of a factory). Or other costs such as management and administrative costs as well as sales and marketing for building brand equity.
While the diagram above is probably the most boring graph you have ever seen, we will use it as a foundation for building the rest of our framework. Note that the fixed cost is constant regardless of quantity. Investment decisions will affect how this line moves up or down on the graph.

However, looking at the individual performance of fixed costs as it's own class of expenditure, the key metric with regards to fixed costs is actually not total fixed cost, but rather average fixed cost.

Average Fixed Cost = Total Fixed Cost / Quantity Produced

Since fixed cost does not change with quantity produced / sold, the only way to improve the operational advantage of a fixed cost outlay is to ensure that the resource cost (and benefit) is spread over as much of the good or service produced.

The following are specific examples of how this applies to different classes of fixed cost allocations.

Land and Equipment
Usually looking at this area is a result of cost cutting measures.

• The company is thinking of opening another plant or reducing capacity.
  
• Analyzing these performance metrics (such as output versus equipment) should tell a story regarding the operational capacity of equipment. If your relative cost of equipment is too high, you might have too much capacity and you can consider divesting equipment, or leasing your capacity.

Sales and Marketing
Investigating this area is usually a result of discovering a weak profit margin or product line. Cost savings from reducing sales and marketing budgets is generally a bad idea (you can't shrink yourself to greatness).

• Sales and marketing might be a place to focus as brand equity is dramatically inter-related to many other interesting aspects of products (such as pricing and service).
• A high sales and marketing budget might allow for higher sales margins (or sales numbers) in the revenue side of the equation.

Management and Administration

• If a company has a very high cost in this area versus competitors, it might be a sign of operational inefficiencies (bloated management layers, practices or compensation).

Now that we have taken a quick peek at fixed cost, tomorrow we will look at variable costs.

[Case Study] One prime example of fighting fixed costs is in the semi-conductor fabrication industry where there are only a few major players (Intel, AMD, Texas Instruments etc). Fabrication facilities have exorbitant and prohibitive capital requirements.

They also have incredibly low variable cost (the individual products of these fabrication plants are relatively worthless). In order to keep a good profit margin, the capacity of the plants must be running at near 99%.

While each of these three major players has high demand, they cannot fully satisfy the demand requirements themselves (resulting an a high average fixed cost per product).

However, by outsourcing their facilities to other semi-conductor designers, they are able to increase the volume and quantity coming out of their facilities (lowering their average fixed cost). They also have a schedule of production queuing to ensure that the facilities always have work to do (to ensure 99+% of the capacity is always utilized).

Profitability Analysis Framework Series
[ 1. Overview, 2. Fixed Costs, 3. Variable Costs, 4. Sales, 5. Price ]

Profitability Analysis Framework, pt 1 - High Level Overview

Profitability Analysis Framework Series
[ 1. Overview, 2. Fixed Costs, 3. Variable Costs, 4. Sales, 5. Price ]

As public corporations are profit seeking entities, one of the most common frameworks in use is the profitability analysis. Over the next week, I'll be posting about the different components that make up this analysis as well as some of the common challenges that arise and some solutions based on case studies of previous companies.

While the underlying math and mechanics of this discussion will usually be quite simple, what is more intriguing is the surprising relationships that surface as a result of an integrated and systematic analysis of the case studies. Most companies are unique (providing them with their own competitive advantages and challenges) however there are some common themes to learn from the cases which are applicable to any business environment.

We will review them as follows:

Part 1 - High Level Overview (This post)
Part 2 - Fixed Costs: Capacity and Investment Decisions
Part 3 - Variable Costs: Cost of Goods Sold
Part 4 - Sales: Volume, Brand Equity and Positioning
Part 5 - Price: Elasticity and Differentiation
Everyone is familiar with the basic formula for profit:

Profit = Revenue - Costs
(individual product lines)

Shareholders Equity = Assets - Liabilities
(symmetrical for companies at large)

Costs can be further subdivided into two categories:

Total Costs = Fixed Costs + Variable Costs

And similarly for revenue:

Revenue = Price x Quantity Demanded

While we have hardly made any ground breaking discoveries here, what should be highlighted at this point is the ability to ask the right questions when confronted with a declining profit scenario. It is important to understand what is happening in the competitive landscape such that profits are declining. By quickly identifying which area should receive attention we can systematically analyze the company's fundamentals to determine where changes are needed).

In Part 2, we will look at fixed costs and how they affect profitability as the need for more investment or more efficiently allocating capacity.

Profitability Analysis Framework Series
[ 1. Overview, 2. Fixed Costs, 3. Variable Costs, 4. Sales, 5. Price ]

Urban Planning and the Irony of Mass Transit

With the focus on how Obama's administration wants to stimulate the economy by starting shovel ready government projects with an emphasis on sustainability (combined with my experiences commuting by public transit) I thought it might be timely to look at urban planning, specifically as it relates to mass transit.

Particularly, with a mildly satirical tone, I wanted to look into the phenomenon of clustering. In other words, I wanted to answer two questions:

1. "Why do I always seem to miss buses in pairs?", and
2. "Every time I try to ride the bus, why do I always get the full one?"

It turns out that there are many circumstances in life for which starting earlier (Or being closer to the finish) doesn't necessarily meaning finishing earlier. Let's build a simple model to help us understand how fundamental mass transit capacity planning works:
To understand what I mean, let's assume:

• A bus route to a main station has five equally distanced stops A, B, C, D and E.
  
• The distance between stops (described as time to traverse from one stop to another) is 2 minutes regardless of traffic and other factors.
  
• It takes 2 minutes to load a bus at each stop regardless of number of passengers, unless there are no passengers (or the bus is full) in which case the bus travels "express mode" and doesn't stop at all.
  
• A bus can hold 50 people maximum.
  
• That each stop has 15 people (total 75). It will take 2 buses to pick up all the passengers.

Scenario i The first bus will pick up 15 from A, 15 from B, 15 from C and 5 from D (50 total). The second bus will pick up 10 from D and the remaining 15 from E.

Notice that whatever the interval between buses (say 15 minutes) is the minimum wait time that the passengers at D and E have to wait for the second bus (on top of normal travel time if they could get one bus 1).

The travel time for each group is as follows:
Bus 1 (containing Passengers from A, B, C and 5 from D) arrives at the terminal after 18 minutes
Time = 2 min per stop x 4 stops
+ 2 min drive time between 5 stops

Bus 2 (containing the remaining passengers from from D and E) arrives at the terminal after 29 minutes
Time = 2 min per stop x 2 stops
+ 2 min drive time between 5 stops
+ 15 minute delay between Bus 1 and 2

Generally,

Travel time for any given bus = time spent picking up passengers (delay per stop x number of stops)
+ time spent driving between stops (travel time per stop x number of stops)
+ time delay between buses (anticipated wait time for a passenger who 'just missed the bus')

Notice that in this model, a bus that follows another will have a more "efficient route" excluding the delay time between the buses (currently set at 15 minutes) if the delay is less than 11 min, Bus 2 arrives before Bus 1! This is because Bus 1 (assumed to have "first dibs" on the passengers) will be held up in "transactions" picking up passengers.

Scenario ii What would happen in an incremented step by step analysis (if the two buses left at the same time) is as follows:

1. Bus 1 picks up all passengers at A (2 min) while at the same time
   Bus 2 travels to stop B (4 min).
2. Bus 2 picks up all passengers at B (2 min) while at the same time
   Bus 1 travels to stop C from A (4 min).
3. Bus 1 picks up all passengers at C (2 min) while at the same time
   Bus 2 travels to stop D from B (4 min).
4. Bus 2 picks up all passengers at D (2 min) while at the same time
   Bus 1 travels to stop E (4 min).
5. Both buses run "express" to the terminal

Both Buses 1 and 2 arrive after 12 min (they share the load equally). This is what happens during non-rush hours and I would describe as "clustering", the phenomenon where buses (even when they start at different times) start to travel together.

As you can tell, this is a horrible situation when it comes to urban planning. For most lines, this means that even if you deliberately stagger buses so that they are 15 minutes apart (assuming that this is also the minimum amount of time someone would have to wait between buses), the truth is that with clustering on non-rush hours it is more likely the wait will be double that (because one bus will naturally catch up with the other if there isn't enough traffic). Hence the answer to: "Why do I always seem to miss buses in pairs?" is because they have a natural tendency to cluster.

Also, implementing queuing and network traffic theory, you can use the analogy that each bus stop is a server node and each bus is a service arrival.

This shows, as in the first scenario (Scenario i), that buses that lead are full. Assuming that occasionally when a few people get off at later stops (rather than waiting for the terminal) this is the only circumstance when a bus frees up more capacity to take on more passengers (also why they ask people to leave from the rear and board from the front). Hence the answer to: "Every time I try to ride the bus, why do I always get the full one?" is because during rush hour, most buses are full to capacity and only buses with marginal capacity available (almost full) stop to pick up more passengers.

Now the system described here only describes an oversimplified one line system. Imagine multiple inter-related lines, time sensitive with daily cyclical traveler arrival patterns, complicated with traffic congestion, traffic lights, construction and other "features" interacting on the road. You certainly can't just throw more buses into the system if you want to improve performance. And we can certainly sympathize with both the Traffic Engineer as well as the person in the car in this xkcd comic:

Price to Sales - No nonsense double check

Continuing from my previous post about Price to Book as a valuation metric, I though I would also have a quick review of Price to Sales. Generally, Price to Sales ratios are sold to analysts as performance metric that is less subject to manipulation by management accounting practices.

While that may be true from an earnings perspective, it isn't necessarily true when it comes to revenue recognition (aggressive mark-to-market or accounts receivable practices are still in the realm of management discretion and can affect reports sales numbers). Sales are a fundamental driver of business performance. However, they are not immune to tampering or manipulation.

[Case Study] For instance, in the internet boom, many "revenue" streams were recorded between growing internet companies who were simply bartering services (usually advertising revenue). They reported incredibly high (and growing) revenue streams despite the fact that no money changed hands (and the actual value of services exchanged was highly questionable). This lead to the inflation of the price of their equity and P/S would not have detected this inflation. This compounds the error caused by the fact that sales revenue was a primary metric in valuing internet companies. Anyone who neglected this truth (almost everyone, except investors like Warren Buffet in his correct but unfortunate short position timing) eventually paid for it when the internet bubble burst.

Also, P/S is meaningless without understanding profit margins (what did it cost the company to get those sales). One disastrous application of P/S I've encountered is in valuing a growing company. In it's early stages, a company had great profit margins but weak sales. In it's growth, sales grew dramatically, making the P/S look incredibly attractive. However, the profit margins weren't stable and as a result the company was not profiting as much as the P/S would suggest.

[Case study] This was the case with Surebeam and their product of irradiated hamburgers and the position Roberto Mignone takes as explained in Hedge Hunters. Surebeam's product initially had strong sales, but upon further investigation by Roberto's team, it was discovered that they were using discounts of as much as 20% to attract customers (destroying their profit margins relative to other similar products). A P/S ratio would have indicated that Surebeam was a good buy (as many on Wallstreet believed) which turned out to be disastrously incorrect.

I would propose that P/S is a ratio that is generally useful only as a secondary check. It should be done in tandem with a PE and EPS analysis to identify if any profit smoothing techniques have been used by management as an indicator of future trouble brewing.

Case Study: Manufacturing Capacity, Opening a New Factory

Introduction: A company is looking to open a new factory location (or close an old one) and is looking for your assistance in determining a location. How do you go about selecting where to open a new plant (or which old plant to close)?

Salience: There are many factors which are important in making this decision. For instance, how much capacity is required after the proposed changes? What is the distribution network needs based on geography? What is the cost of the factors of production (land, labour, capital) associated with different locations?

Causality: With the goal of optimal operations to achieve maximum profitability, each of these factors will have a different effect on how you make your decision. In closing an old plant, you will have to do a cost / benefit analysis of each plant and determine which one makes the most sense to shut down. The following framework can be adapted to better understand the closing of one factory to the entire manufacturing load and network.

In the scenario of opening a new plant, you technically have more flexibility in terms of which locations where you want to open (including even outsourcing capacity from others) so we can start to build a framework about how to decide what consitutes an optimal solution.

Architecture: There are many factors to consider in a holistic approach.

• Geographic capacity demand.
• Distribution of products.
  
• Local labour, material and transportation costs.
  
• Resource availability.

Geographic Center of Gravity First, let's simplify the model by assuming, cateris paribus, that the only thing that matters is geography. In this case, you can make an easy decision by taking mapping potential factories by using a center of gravity formula. "Gravity" in this case is capacity demand. Also, factories currently in operation would serve as negative "gravity". This is because they are already servicing demand in the area. The resulting "center of gravity" would be a reflection of an area with the highest capacity demand.

R = Σ [Vi x Qi] / n

Where:

• n is the number of current factories in operation
  
• R is the optimal vector of your new factory location
  
• Vi is the vector describing the locations of your relevant capacity factors.
  
• Qi is a weighting applied to the relative capacity impact of each location (a positive value implies a customer demand, a negative value implies a factory capacity supplied). This factor can also be scaled for other factors accordingly.
  
• i is a counter variable iterating from 1 to n (encompassing all elements affecting capacity)
  

This formula assumes that each factory has identical weight in terms of capacity, costs etc. However, instead of a straight forward calculation of an average, each factory can be weighted with these additional factors to provide a more reasonable measure. For instance, each factory can be weighted with it's relative capacity.

Now, what if you only have a limited number of possibilities because of such factors as labour and resources are limited to big city areas etc? You need to match the profiles of your possible solutions to your "optimal" solution. However, in looking at your optimal solution, perhaps it will provide you with a potential solution that you had not previously considered (locating in a different town for instance).

Resolution: Although this is a very reasonable methodology, it only provides a mechanical answer based on the inputs provided and requires the analysts to accurately gauge the weight and importance of each individual factor. There may be many other influences such as political pressure to locate in a particular area. However, it acts as a logical framework for identifying the value of different locations while considering the broadest and more relevent factors relating to the capacity management decision.

[Case Study] A consulting company has 5 equally skilled consultants in the same field. 2 are in New York, one lives in Boston, MA and one in Philadelphia, PA. Their business is as follows is divided geographically as follows:

• 20% Philadelphia
• 50% New York
• 30% in Boston
  

Assume that each consultant is equally effective and the work is divided evenly. Also, the last consultant is more flexible to travel (but all consultants generally want to travel as little as possible), where should the last consultant reside?

Using the formula above, what is the optimal location for the last consultant to reside?

[Answer: Hartford, Connecticut. Reasoning: Each consultant reflects 20% of the work load. This means that the consultant in Philadelphia can deal with the work load there. Two of the NY consultants reduce NY's capacity deficiency to 10% as does the consultant in Boston. Another way to look at the solution is that the only work left for this last consultant is equally split between New York and Boston.

The so in calculating the center of gravity, we learn that the optimal location solution is equidistant from New York and Boston (Hartford) - Note that Hartford was not a suggested location, but came up in the investigation.

Also note that the assumptions were just for simplicity in illustrating the solution, but the differences of the contributions, demands and travel costs of each individual component can be mathematically weighted against the whole - Philadelphia has more work demand than Boston, Senior Consultants do more work, costs for junior consultants is cheaper etc.]

Supply Chain Management - The Vertical Integration Decision

What are the scenarios where vertical integration of the supply chain is a good solution?

Well as it turns out, there are very heavy capacity implications when making acquisition decisions up the chain. Each layer of the supply chain adds value (and challenges) in unique ways. What are the key metrics for creating a compelling case for vertical integration? If your organization:

• needs more control over your supply chain management (planning, synchronization, JIT inventory practices)
  
• requires a greater degree of customization not currently available through third parties
• has the capacity demand to generate your own economies of scale (lower costs)
  
• can experience growth and efficiency and capture synergies in the new vertical integration
  

Conversely, in a scenario where an organization has too much capacity or cannot maximize the benefits of a division, rather than shut down it down, they can also sell of capacity to other organizations who can make more efficient use of those resources or spin it off.

Vertical integration can either be backwards (up the supply chain) to encompass inputs or forwards (down the supply chain) to encompass distribution channels.

What are the challenges to vertical integration? Each layer reflects a value added component and therefore is fraught with its unique challenges such as market sizing, competitiveness, industry regulations etc.

However, as a word of caution companies that do forward integrations (cutting out the "middle man") are often in danger of venturing into unknown territory as well as damaging relationships with other distributors (who can see this move by a company as repositioning from cooperative to competitive). This is exactly what happened between Harlequin and Simon & Schuster in the late 70's.

[Case Study] Today, Pepsi Co has put a set a $6 billion bid to acquire two of it's largest independent bottlers for Pepsi Bottling Group and Pepsi Americas. In this particular case, the decision for vertical acquisitions was driven by the need to gain a strategic advantage through controlling over 80% of their distribution. Each of the acquired companies shares are currently valued at 17% over their Friday closing price.

Story of Stuff - Sustainability and Statistics

I was recently introduced to this interesting video on the history of stuff (~21 min) and thought it might be helpful to do a quick review. I think there are some brilliant messages here, but at the same time, I think this is a prime example of having to look more closely at statistics and question what's presented. First let's look at some of the key points:

• Linear systems are not sustainable (and certainly cannot support exponential growth). You need a cyclic system in order even have a chance.
  
• Externalizing costs is a model which offsets the factors of production to keep costs low (and like over utilizing any resource is itself unsustainable).
• The three R's are Reduce, Reuse, Recycle (in that order). Recycling should actually be a last resort from a sustainable consumption perspective.

While I like the overall message, I find some of the points and use of statistics questionable. Or as xkcd puts it:


For instance, Anne Leonard states that 99% of everything we consume is disposed of in 6 months. That's a lot. I have a general heuristic for these types of scenarios. If your statistic produces a result of more than 90%, that generally means there is some selective data mining going on. To reach a number like 99%, it suddenly becomes more interesting as to define what is the 1% that we keep beyond 6 months. It seems pretty astronomical, yet something about this doesn't seem right. What could possibly justify this number?

• Why six months? Why not look at a quarter? A year?
  
• Is it measured by income dollars spent? Mass of goods? Volume occupied in a landfill versus in storage?
  
• What's included? Housing, food, gasoline, seasonal clothes, books, text books per semester, garbage?
• What would be a more appropriate number given the same metrics? What should we aim for?
  

Next, Anne mentions that the US has 5% of the worlds population but they are consuming 30% of the resources (implying a footprint of 6x of what is should be). She also mentions that we are consuming 2x as much as 50 years ago which I feel is like comparing our peek consumption with our valley (which upon further analysis is almost meaningless). 50 years ago is very close to the depression and WWII which are the lowest consumption rates in recent history.

I am very opposed to peak to trough comparisons in behavioural studies because they represent extremes. I'd be more impressed with a normalized study over time with standard deviations rather than an opportunistic snapshot of a scenario 50 years earlier. This is because I'd expect that despite the growth of consumption, there is a corresponding diminishing utility that Anne hints at as a cause of decreased happiness since the 50s.

Her point on computers and planned obsolescence is both correct in many respects yet highly oversimplified and as a result (I would suggest) misleading. She implies that a computer upgrade is simply a CPU replacement and that companies intentionally design chips so that they cannot be easily substituted.

Upgrading a computer can *sometimes* be as simple as replacing a chip, but often with increases processing power come increases in bus speed and memory. A computer system is a much more complicated than simply replacing an old chip with a newer, better one. It's not just a matter of "shape" as suggested. Actually, the change in shape is deliberate to prevent people who don't understand how computers work from blindly substituting in parts (and destroying both).

Despite my negative tone regarding her use of statistics, I really think Anne has done something phenomenal. Her attempts to reach a broad audience are successful, but she does sacrifice a bit of credibility for accessibility. Some of her broad and extreme claims leave her work more vulnerable to criticism than it should be. I do like her proposed solutions, but I think the corresponding required change in consumer behaviour will be quite a challenge. I think that everyone should spend the just 21 minutes and watch this video.

Selfish Sustainability - Save or Starve pt 2

Selfish Sustainability - Save or Starve Series [ 1 - 2 - 3 ]

Now that we had a "new" mission, e were forced to help change. Not by governments nor regulations, but our own self interest as a profit loving entity. We had to take a new perspective on our goals and extended the scope. Now we were a force of change.

New Problem: Depletion of natural resources
We can't call ourselves a top luxury hotel with pristine nature if the sea bed has been bombed to smithereens. Our natural resources are being depleted in a decidedly unnatural rate. As mentioned in my previous post, we had to understand why.

Salience:
We need to increase the awareness of the damage that's being done to our natural resources with the public. Issues arise that quickly become apparent. This is an illegal activity. You can't just advertise a class for fish bombers and hope you get good attendance.

We also need to address the poverty and danger associated with this negative short term thinking and the negative economic externalities they impose on the local community.

Causality:
Fish bombing is driven by a combination of poverty which is a result of a lack of opportunity, education and awareness in the general local public. It also thrives because of lack of policing due to difficulty to coordinate naval operations with the community.

Architecture:
How should we model our action plan to solve these challenges?

• There is a need to work closely and communicate with the community to educate them and start a community dialogue. We need to educate our society to understand the value of this natural resource for everyone.
• We need to fight the root causes of this destruction and poverty by creating better, higher paying jobs and opportunities for local members of the community. Suddenly, instead of selling a pile of dead fish for a few RM each, you can have wealthy tourists pay you the same amount just to look at them. One of these you can do forever. The other guarantees your children a worse future than what you have now.
  
• The community needs to be connected to the relevant policing agencies to actively protect our natural resources.

Resolution:
A higher quality resort demanded higher quality service. We had to introduce language classes, service training to give our staff an opportunity to develop into new more fulfilling roles. It was nice to see local hires who saw the resort as a family. No longer simply "changing sheets", they became part of the hotel experience and fellow nature lovers.

Our staff numbers more than doubled from the previous management (which excludes the second island resort), wages and benefits also increased (caused by the increased demand for labour). In one of the arguably best applications of supply side economic theory working in the real world, we demanded more from our team, compensated them better to keep them and they stepped up to the task.


Also, we developed incredible programs such as the Marine Ecology Research Center (MERC) based on leading edge research to restore marine life in the water. We increased the number of PADI certified divers in our resort, making diving equipment and training accessible to our locally based general employees so that they could experience and understand what they were protecting.

We started our own sustainable fish farms and water treatment and recycling systems. As an island resort, we couldn't just hook up to the city mains. Plus our treatment systems were more advanced that those provided by the city. We made an effort to have our values and behaviours reflect our over arching philosophy. We are profiting from nature, so we have to protect our interests.

Long Term Outlook and Lessons Learned:
If you want to use capitalism as a force for good, how can you redirect 'greed and the drive for profits' into a solution for sustainability? Align the corporation with the values of society. Our situation was unique. There was a direct correlation between the health of our environment and our profits. Our environment: Save or starve.

Anyone who is a cynic of corporations will immediately raise their hand and ask "Uh... Shouldn't governments be looking after the natural resources and interests?" Absolutely. But some governments are not as wealthy as others. The unfortunate truth is that many wealthy countries have exploited their natural resources. The remaining ones that are naturally beautiful usually remain that way because they haven't been industrialized (and tend to be poorer). While this isn't strictly always the case, often governments often can't afford to police and protect their resources. Malaysia is hardly unique in this area. They know they have a valuable resource and are working hard to try to find more effective ways of protecting it.


This was a topic of the Asia Pacific Ecotourism Conference (APECO). While corporations may not be the best solution in all cases, it certainly beats the solution of no awareness and no responsibility. There were countless examples of beautiful areas that were ruined because they were neglected. These areas were notorious for exploitation by seemingly less scrupulous individuals who (it turns out) were just looking to feed their families.

There are certainly a lot more issues and complexity that arise from the discussions and further study regarding ecotourism policies, corporate social responsibility and sustainability. This series of posts is intended only as a starting point to illuminate another path for more enlightened discussion:

1. Corporations, if used appropriately, can actually be a force for good rather than stereotypical greed,
   
2. Corporations can contribute funds to develop positive programs, real opportunities and supply good jobs, rather than simply act as a source of tax shelter based charitable donations, and that
   
3. Integrative thinking can help you find the surprising nugget of gold in a case where there is a lot of chaotic data and relationships

Selfish Sustainability - Save or Starve Series [ 1 - 2 - 3 ]

Selfish Sustainability - Save or Starve pt 1

Selfish Sustainability - Save or Starve Series [ 1 - 2 - 3 ]

Corporations are based on greed right? Is there any way to use the drive for profits to enforce ecological sustainability? Turns out there is. One of the reasons I love this case (derived from my experience in Malaysia) was that it started out as a standard vanilla business problem and evolved into something wonderful. Suddenly, evil corporations could be on the side of angels.

If there was ever a case where integrative thinking would lead a corporation to pursue success while preserving the environment, my work with hotel developers in Malaysia would certainly fit the bill. It's a great case study for looking at a problem through the framework, coming up with more interesting questions and reaching a surprising conclusion. Another reason why I like this case is that when you use integrative thinking to look at the broad perspective of what's going on, you can often find surprising answers to your original questions.

Let's look at what happened:

*Initial* Problem Definition: Let's Make Money
Our holding company held several properties. Two key properties were beautiful island resort properties which had unfortunately been left in disrepair. Our Managing Director had seen some great potential for these new island properties to be acquired and developed into boutique luxury hotels to service the affluent Asian and Australian market.

Salience:
Metrics of a hotel are pretty standard. You want to charge good rates and have lots of people come. As I mentioned in my previous post about hotel capacity management, the raw math for making money in a hotel is pretty straight forward.

Causality:
As I also alluded in my previous post, average room rate (ARR) is dramatically effected by quality (real and perceived). Also occupancy (OCC) was greatly affected by market presence. Both of these qualities are strongly correlated to brand equity. Certainly no surprises here.

Architecture:
(Where new problems and interesting challenges start to surface)
One of the reasons I was brought on the team was to bring in an international perspective. Most of the senior staff was composed of local managers who (although talented) had trouble perceiving (and therefore developing and selling) the differences in the international market. Many of our sales agents had a legacy two-star rating of our old services and facilities. So we set up a framework for dealing with those issues:

• Upgrade facilities to match a 5+ star boutique quality with a luxury brand network (such as Small Luxury Hotels or Prestige)
• Leverage network to attract high quality clientele (from outside of local markets - average spend of a visitor to our part of the world was RM2000 (Ringgit Malaysia) or ~$700USD for an entire week long vacation. We were charging $300 USD per night). Relying on the average and status quo wasn't going to work.
  
• Renew brand equity and highlight natural beauty and proximity to nature as inimitable point of differentiation against other leading international hotels in the luxury space (in the luxury space you have to be exceptionally unique to attract guests)
• Have world class operations to support your brand equity promise of a peaceful, serene resort experience

While all of this may seem rather obvious (even those of us who haven't yet finished our fancy MBA school degrees), I deliberately emphasize the importance of natural beauty *and* proximity to nature because without it, we were a resort like any other.


While services like jungle trekking and scuba diving were available in beautiful places like Sipadan (World class diving site) or jungle trekking in the depths of the Sabah's jungles, we were the only location that was located only a 15 minute boat ride from main ferry terminal in the heart of the capital city and offered both.

Every other hot destination required a minimum 3 hour bus ride. Sipadan also required a flight to Tawau on the other side of Sabah followed by a lengthy boat ride. While they are worth it for those who are "hardcore" (I myself have done these trips) they are hardly easily accessible and require additional days travel. We were isolated, pristine and accessible.

Resolution:
Exploit natural resources, build hotel, make money. Right? Well that would seem to be the natural answer. But if you're livelihood depends on the pristine condition of your surroundings you have to make sure that you look after your natural resources.

There was a problem in Sabah. While rich in natural beauty, like many developing nations, the majority of the population was poor. By Malaysian standards. This resulted in some extremely negative short term behaviour.

New problem: Destructive Fishing
One such example is fish bombing. As an outsider, I thought it was an over exaggerated myth until I experienced it on a trip during a day off.

I was taking some time off with the diving staff so we decided to scuba dive in a reclusive area of the island. With our proximity to the city, we often see fishing vessels of locals. Pump boats, notorious for being illegal vessels (because they can outrun police boats in shallow shoals), are still incredibly common. On our search for a dive site, we passed by one and in my good natured naivety, I waved as we passed by. Unamused, the two fishermen, sharing what is essentially a canoe with a lawnmower engine, eyed me suspiciously before returning to their work. I though nothing of it at the time (whereas my two diving companions apparently knew better).


Our dive was nice, but fairly uneventful, until towards the end, just before we decided to surface, I heard a rather forceful explosion and felt as if someone has punched me in the chest. It was incredibly unsettling. At first I thought someone's tank exploded, looking at my two companions they were fine. I checked my equipment and everything seemed to be in order. When we returned to the surface I was shaken: "Did you hear that? What was that?"

"Fish bombing" came the reply, "probably from those guys we passed earlier." Although the explosion was a good distance away (judging by the position we last left the two fishermen in the pump boat) I had temporarily forgotten the physics of propagating waves in water (water is an exceptionally good transmitter of waves and pressure). The force felt so close, I thought it had to be nearby.

It turns out this "urban myth" is all too real. What happens is that poor fish farmers will create homemade grenades, toss them in the water and cause large vibrations which immediately kill the fish in a large area by rupturing their organs and they immediately float up to the top for a catch which will supply the fisher man with as much as a reported RM4000 for a days work (average salary for Malaysian workers ranges from RM300 to RM1000 per month for skilled or semi-skilled labourers) so that translates into a great deal of money.


The obvious problem is that this indiscriminate form of destruction also destroys corals that took years to grow. Besides being beautiful in it's own right, coral also acts as a home and food supply for many forms of aquatic life and is therefore a critical part of the ecosystem in the water. In recursively applying the integrative thinking framework (Salience, Causality, Architecture and Resolution) the less obvious "secondary" problem that surfaces becomes the primary one. Fishermen are poor and have an good financial incentive to take more aggressive measures to ensure their livelihood (exploiting their future for the present).

Suddenly, not only is a matter of developing the resort facilities, but also the society that the resort exists in. Our problem definition has suddenly become more complicated (and enriching) than "build hotel, make money".

[cont'd on pt 2]

Selfish Sustainability - Save or Starve Series [ 1 - 2 - 3 ]

Zeller's New CEO Overly Ambitious

Zeller's new CEO, Mark Foote, is trying to pitch the public the idea that Zeller's is in a position to profit from the recession in the same way Walmart is, as the discount retailer in the HBC brand. If you read my post about why Canadian's can't seem to compete at the same levels of our American cousins, you would be (and should be) a bit skeptical.

While Mark has his direction and focus in the right area, "supplier relations" and "productivity" (as measured by sales per square inch) will hardly be easy challenges to surmount.

As far as supplier relations go, if Zeller's wants to compete with Walmart, they have a long way to go in terms of cut throat relationships to drastically cut prices that characterize successful discount retailers. Walmart has also had a good head start with "supplier relations" (notoriously so that they've constantly been targeted by activists for having "bullied" suppliers). But worst of all, Zeller's won't have the strategic leverage they can apply against their suppliers for better conditions as their parent company is having financial troubles of it's own. Also their distribution channels are not particularly noteworthy versus other retailers. It's hard to be the school yard bully if you're the skinny and sickly nerd.

In terms of "productivity", it isn't a cause of their woes, it's a symptom of their diluted brand equity. This is the consequence of their brand swaying back and forth and not entirely owning the discount space. Been to a Zeller's recently? In peak hours, there's no one there. Walmart's continue to be constantly packed. The Zeller's brand isn't even bringing people through the door.

Mr. Foote's "sanguine" attitude is encompassing and descriptive: Win or lose, The future looks both hopeful and bloody.