Wargaming. Simulation methods: pretend you\'re in the new business, and try to imagine what your competitors might do. Fully automated: SimCity, with business modeling software instead of teenage games. Manual: groups of people role-playing.
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Simulation methods: pretend you\'re in the new business, and try to imagine what your competitors might do.
Fully automated: SimCity, with business modeling software instead of teenage games.
Manual: groups of people role-playing.
Value: lets you think about what your competitors might do.
Risk: somewhat disconnected from reality.
Invented by von Reisswitz (Prussia) in 1824 (Kriegspiel).
Below is a picture of a US wargame from 1895.
Before the Battle of Midway, a Japanese participant in one of their wargames suggested a counterstrike; Admiral Ugaki overruled the result.
Strangely enough, H. G. Wells, later a pacifist, invented a game he called "Little War" in 1913, based on toy soldiers.
This is, by some accounts, the origin of all the shoot-em-up computer games now popular.
One of Wells\' colleagues, F. W. Lanchester, invented a set of mathematical rules for deciding the winners of wargames. These rules regulated the ratio of your soldiers to enemy deaths, for example. (He also built the first four-wheeled car in Britain and invented disk brakes).
In Japan Lanchester\'s equations are used in marketing (doubling your effort increases sales four times).
Most wargames are decided by umpires, not equations. In Germany the Kaiser insisted that he would always win.
On February 7, 1932, the US Navy had a fleet exercise in which two carriers commanded by Admiral Harry Yarnell launched planes for a dawn raid on Pearl Harbor. They dumped 20 tons of dummy explosives on the naval base, without seeing a single fighter in opposition.
The umpires ruled that 1/3 of the attacking planes would have been shot down by antiaircraft fire and concluded that "it is doubtful if air attacks can be launched against Oahu".
Over the next few years, Yarnell was regularly ignored in his calls for more airpower and more opposition to Japan; he retired, disappointed in 1939.
Companies use wargames to plot out marketing strategy. To quote the Fuld-Gilad-Herring Academy of Competitive Intelligence, "War games, the hottest strategic tool, enable management to examine strategies and initiatives in light of external competitive conditions.“
Realistically, what they do, if run honestly, is to recognize some of the risks of a new venture. In companies where there is a tendency to be overly optimistic, they can be a counterweight. (And, unfortunately, if your company is too conservative, they can add to the tendency to do nothing).
Two days, with a couple of weeks preparation.
Teams do data collection.
They spend one day working on the rules, and then one day trying scenarios and writing the final recommendations.
(At least according to Fuld-Gilad-Herring.)
Whether you use a simulation program is probably less important than whether you look at the results honestly.
Some people take this much too seriously: “About 40 mid level managers from the Latin American division of SmithKline Beecham PLC, the $9 billion pharmaceutical giant, are gathered around an elegant mahogany table. They are outfitted in combat fatigues, although more than a few also sport tasseled shoes.”
“Cruz has spent more than $100,000 on a computer-based simulation to help his executives think through plans to introduce a new consumer product in the rapidly growing Mexican market. The product, which leverages off an existing SmithKline brand, makes great strategic sense -- at least on paper. This two-day simulation, developed and run by Advanced Competitive Strategies (ACS) of Portland, Oregon, is designed to help the team convert ideas into action -- and hopefully create a sense of urgency and esprit de corps.”
(Fast Company, http://blackbox.fastcompany.com/online/06/sidebar.html)
A mathematical model is made of the market, showing how much people will buy at what price, how much advertising affects the market, how much brand loyalty there is, and so on.
A model is also made of production costs, investment, and the like.
Then different teams present their strategies, the consultants put all of them into a modeling program, and the computer reports an answer.
The consultants may also present surprises: a new competitor enters, a currency is devalued, interest rates change, …
The parts for a bicycle cost $50. Our company currently pays $50 to have them assembled and sells the result to retailers at $150 who sell to the public at $250. We have 10% of the market. So our profit is $50/bicycle.
A competitor is assembling the bicycle parts in Mexico for $25 each, advertising the same amount and thus making $75/bicycle.
What if we propose a $25 rebate for each purchase? It would reduce our profit per bicycle to $25, but if it doubled the sales, we’d still have just as much total profit.
If you wargame it, you ask what the competitor would do. Assume they would cut their price, too. Then we’ll keep the 10% market share, and lose half our profit; they’ll only lose 1/3 of their profit. What if they try a $50 rebate? They will still make $25/bicycle, but we’ll be out of business.
You can’t win at price-cutting against somebody who has lower costs. (You really should have known that ahead of time).
You might win by doubling the advertising budget and emphasizing that your bicycles are higher quality or let you ride faster or something.
Or by investing in machinery that will assemble the bicycles more efficiently.
But it’s not likely that you’ll get this kind of information OUT of a wargame because you have to know in going IN to the game.
And the assumptions in the simulation (about people’s reaction to price changes, etc) make all the difference.
Elasticity is the ratio of the change in sales as a result of some other change.
Thus, if a 10% increase in advertising yields a 5% increase in sales, advertising elasticity would be 0.5; typically it is only about 0.1
If a 10% increase in price led to a 2% decrease in sales, that would be a price elasticity of -0.2; note the minus sign. This number is typical.
Horrible problem. There’s no agreement on the effects of advertising, for example. You can find a few studies eg
But really judging how much you can expect to gain from running ads is very difficult.
Price elasticity is easier to understand than advertising elasticity.
“Inelastic” commodities have sales that aren’t affected much by price; “elastic” commodities have sales which are affected by price.
Inelastic commodities are commodities that are basic necessities; people will not stop buying them if they get more expensive (e.g. gas for your stove).
Elastic commodities are items where it’s easier to cut back, such as restaurant meals.
Price elasticity can be short-run or long-run; for example, in any given week the amount of gasoline bought may not change much, but over a few years people can buy cars with better mileage or rearrange their commuting.
Price elasticity for a variety of commodities, sign reversed (increased price means decreased sales).
“I conducted an analysis of the RIAA\'s market data from 1992 through 2001. After adjusting their market figures for inflation using the Consumer Price Index, I found that the industry has experienced an average price elasticity of 6.3 (CDs taken alone have an average price elasticity over the period of 2.8). 2001\'s price elasticity was broadly in line with historical norms.
What is the real issue? Perhaps it\'s that in 1998, the recording industry was able to eke out both a small inflation-adjusted price increase and an increase in unit shipments, and desperately wants to believe that the return to historic norms was due to illicit file sharing rather than the market returning to historical norms of the past decade.”
(ps again the sign of price elasticity is reversed: he says so.)
These studies were done to refute claims that advertising had no effect on the level of smoking.
It clearly has some, but less than you would think.
“For the U.S. beef market, one of the smaller advertising elasticities is that of 0.0005 reported by Altson, Freebairn, and James. This suggest that a 10 percent increase in beef advertising expenditures increases retail beef demand by only 0.005 percent (10.0 x 0.0005). Coulibaly and Brorsen obtained even smaller elasticities (i.e., such as 0.0003). The
relatively larger advertising elasticity is that of 0.025 reported by Ward and Lambert.”
From http://www.ampc.montana.edu/publications/ briefings/Briefing32.pdf
Viability of the Advertising Expenditure
A breakeven of 54,167 kg is a 15.8% increase
over the existing 343,563 kg volume
This is a 54.8 ton increase, requiring an increase
in market share from 4.3% to 4.9% in a relatively
flat Belgian market
Increase in advertising expenditure is 42%
Therefore, the advertising-sales elasticity is 0.376
(15.8% / 42%)
If the actual advertising-sales elasticity is less
than 0.376, Godiva will not recoup its incremental
[NOTE: typical advertising elasticity is 0.1]
Note some confusing things here: the price elasticity is positive, which means that although egg prices were going DOWN, egg sales went DOWN as well.
Take current sales and add:
Sales = Current +
(PE*price change)*(AE*advertising change)*(available customers by loyalty)*randomness
Don’t believe too much of this math
(AE, PE are advertising and price elasticities)
If you currently have a 5% market share, and the advertising elasticity is 0.1 while the price elasticity is -0.5
If you raise the ad budget 50% and cut the price 10%, you might see an increase of 10% (5% from the ad increase, 5% from the price decrease).
But if you think that brand loyalty for your competitors is 50%; then you’ll only see a 5% increase.
And if you think that random chance is deciding 50% of purchases, then you’ll only see 2.5%.