PEST Analysis

In continuing with different analysis frameworks such as SWOT and Porter's Five Forces, another good framework to use is PEST (which stands for Political, Economic, Social and Technological factors). Using this framework helps identify macro-environmental factors which influence strategic management. Since PEST takes a higher level view, it can also provide a longer lead time for understanding the evolution and coming changes, however, that is counter balanced by the idea that the farther you look into the future, the fuzzier the picture gets.

Political factors examine how and to what degree a government participates and intervenes in the economy. Specifically, political factors include areas such as tax / subsidy policy, labour laws (minimum wage, safety regulations etc), environmental regulation, trade barriers and tariffs, and political stability. Furthermore, governments have great influence on the health, education, and infrastructure of a nation.

Economic factors include macro-level economic factors such as economic growth (GDP), interest rates, exchange rates, the inflation rate and unemployment rate. For example, interest rates affect a firm's cost of capital and therefore to what extent a business grows and expands. Exchange rates affect the costs of exporting goods and the supply and price of imported goods in an economy.

Social factors include the culture, education level, health, population growth rate, and age distribution. Trends in social factors affect both internal and external factors in the company including the demand for a company's products or services (what the public in that geography demand) and how that company operates (who is available to be hired from the pool of workers).

Technological factors include R&D activity, automation, the rate of technological change as well as the current state of technology (i.e. communications infrastructure). They can determine barriers to entry (patent law) or provide strategic leverage.

By looking at all these factors, an analyst can determine the relative attractiveness of looking at different geographies from a macro-perspective. From a top-down approach to strategic thinking, a PEST analysis is a rudimentary starting point for any decision making.

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 irregardless 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:

Michael E. Porter's Five Forces - Industry Competitive Analysis

While an index like the Herfindahl-Hirschman Index (HHI) might give you a nice quantitative number describing the level of competitiveness in a given industry, a framework such as Porter's Five Forces will start to explain why this is the case.

Porter's five forces analysis looks at:
Another way of looking at this is a 360 view around your company's position in an industry. This includes your supply chain (vertical view of suppliers and customers) as well as within your market (horizontal view of entrants and substitutes). Each of Porter's four mutually exclusive forces contribute to the over all competitive rivalry in an industry.

This helps you answer the question, "Should we start a new venture in this industry?"

Let's have a closer look at each category:

The threat of substitute products The greater the number and the closer substitute products imply an increase the propensity of customers to switch between alternatives (high elasticity of demand).

• buyer propensity to substitute
• relative price performance of substitutes
• buyer switching costs
• perceived level of product differentiation

Example: Coke and Pepsi are (propensity to substitute, "brand loyalty" aside) cost about the same. In a convenience store, there is no cost to switch from one to the other and there may be some small differentiation between brands. The threat of substitution is high. Test this by going into a restaurant that only serves Pepsi and ask for a Coke. Chances are your server will ask "Is Pepsi, ok?" (if they ask at all)

The threat of the entry of new competitors Inefficient or overly profitable markets will attract more firms and capacity investment. More capacity results (for under served markets) results in decreasing profitability. The markets will always seek equilibrium even if that equilibrium is artificially imposed by barriers.

• the existence of barriers to entry (patents, rights, etc.) - Note the expiry of patents can trigger new a equilibrium and competition rivalry movements in the industry
  
• size - capital requirements and economies of scope
• brand equity
• access to distribution
• learning curve advantages - required skill
  
• government policies, regulations and licensing requirements
  

Example: Although the mass production of juice might require specialized equipment for economies of scale, individual producers (lemonade stand) are not prevented from entering the market with smaller equipment investments. Threat of new competitors is high. Other than standard food and health regulations (FCC), there are no licenses required to produce juice.

The bargaining power of customers Also described as the market of outputs. The ability of customers to put the firm under pressure and it also affects the customer's sensitivity to price changes.

• buyer concentration to firm concentration ratio
• degree of dependency upon existing channels of distribution
• bargaining leverage, particularly in industries with high fixed costs
• buyer volume
• buyer switching costs relative to firm switching costs
• ability to backward integrate - can customers do this themselves?
  
• availability of existing substitute products
• buyer price sensitivity
• differential advantage (inimitable characteristics) of industry products

The bargaining power of suppliers Also described as market of inputs. Suppliers of raw materials, components, labor, and services (such as expertise) to the firm can be a source of power over the firm. Suppliers may refuse to work with the firm, or e.g. charge excessively high prices for unique resources.

• supplier switching costs relative to firm switching costs
• degree of differentiation of inputs
• presence of substitute inputs
• supplier concentration to firm concentration ratio
• employee solidarity (e.g. labor unions)
• threat of forward integration by suppliers relative to backward integration by firms
• cost of inputs relative to selling price of the product (profit margins)
  

Example: Bread inputs include flour, eggs, etc (highly fungible and cheap base commodities). Supplier concentrations of these inputs to firm is very high. Individual suppliers do not dominate the market and will probably not forward integrate (an egg distributor / farmer) will generally have no interest in making and selling bread.

The intensity of competitive rivalry For most industries, this is the major determinant of the competitiveness of the industry. Sometimes rivals compete aggressively and sometimes rivals compete in non-price dimensions such as innovation, marketing, etc.

• number of competitors
• rate of industry growth
• intermittent industry overcapacity (like the service industry)
  
• exit barriers
• diversity of competitors
• informational complexity and asymmetry
• fixed cost allocation per value added

Example: Cellular carrier companies (Canada: Rogers, Bell, Telus. US: Verison, Sprint, AT&T) requires large economies of scale for infrastructure. Industry suffers from over capacity at off peak hours. There also also high exit barriers (selling cellular infrastructure). Competitors are not particularly diverse and informational complexity is fairly low. Cellular billing (cost per minute) is fairly fixed. Competitiveness is generally high.

Each of these sections are scored and collectively analyzed to understand the competitive forces in any given industry. This framework highlights the key factors which determine any industry's overall competitive rivalry (and attractiveness). Industries which are not competitive may be attractive for other companies to enter (or increase investment), industries which are overly competitive may force out weaker companies and would generally be unattractive for new ventures.