Finally we want to think about inference tools.

Ways in which we can manipulate data to get further insights.

In many ways, the strategist's toolkit is filled with inference tools here.

Five forces, capabilities, analysis, all of these are to increase inference.

There are some others that are list here that also are more commonly used across

different fields of business and can be useful in strategy analysis.

Break even analysis.

Given capital expenditures how much

sales do we need to break even from that initial capital expenditure.

Decision trees highly related to our discussion of game theory.

This the notion of giving two strategic options what are the pay

offs associated with them.

Sensitivity now is also important no matter what type of analysis you're doing.

This is looking at,

if we vary the parameters in a model, what happens to the outcomes?

A variety of approaches for doing that, that I list tornado charts,

Monte Carlo simulation or Monte Carlo analysis.

Very critical that no matter what data we bring to bear, what analysis we bring to

bear, we look at the sensitivity to the results to that data.

We mentioned regression analysis briefly before.

It's beyond our scope to really go into depth about regression analysis, but

it's a way of looking for relationships between sets of data.

Finally I mentioned before data visualization, and again,

there's a growing number of techniques and tools out there to help you visualize data

to once again make inferences and ultimately make good recommendations.