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In modeling, assumptions on what you think will come

to for the inputs or metrics in the model.

It can be assumptions about the circumstances that affect the metrics in the model.

To build your assumptions out,

you start with information available to you based on historical data.

For example, we can assume we will continue to gain

market share at the same rate as we have for the last six months,

or we assume that we will continue to see spikes and

sales around holidays or on certain days of the week.

As you make assumptions,

pay attention to your forecasts about metrics you have less control over.

Costs are usually harder to change drastically.

So, when you make your assumptions about reducing the future costs,

make sure you're being realistic.

For instance, when estimating the cost of delivery,

the cost of gas is typically harder to predict since gas prices are fairly volatile.

So, in general, be careful about the assumptions you make about changes in costs,

and check to see if those assumptions are reasonable and make sense.