Original subtitles

All right I want to take a minute and walk through a slightly more advanced demo.

We're going to use what's called a what if parameter to do some scenario testing.

And if you look at your modeling tab you'll see this new parameter button that launches a dialog box

that looks like this.

Now essentially these parameters are preset daks measures that produce values within a given range based

on user inputs the data type the minimum the maximum the increment and the default value.

And these can be really good tools to use for things like forecasting or scenario testing.

So the example you see here and the example that we're going to practice is creating something like

a price adjustment percentage captured within a parameter so that we can compare total revenue based

on actual information and actual prices against an adjusted revenue based on the parameter adjusted

price.

And I'm going to show you exactly how that works.

Now one interesting thing to note is that when you create a parameter using the dialog box power be-I

actually generates and creates a new table for you with daks calculations already in place for the parameter

and the parameter value.

So those generate series and selected value functions that you see at the bottom of the screen.

Those are automatically created behind the scenes although we could build them from scratch if we chose

to do so.

So let's head back to our report and try creating a scenario test of our own using these parameters.

All right.

We're going to head to the product detail tab and you're going to want to follow along closely with

this because there will be a number of steps and we're going to have to get back into our daks world

and write a few new measures to make this all work.

So first things first on the modeling tab Here's my new parameter option.

Let's go ahead and launch the dialog box.

Now the settings that I'm going to use given a name something like price adjustment with a percentage

and that's just part of the title it's just text because the values that we're going to use as you'll

see will eventually translate into percentages the data type is a decimal number.

And let's set the minimum to negative 1 maximum to 1 the increment at zero point 1.

And the default 2 0 and we can keep this add slicer to page activate it.

So to recap we've essentially created a scale of values defaulting to zero with a minimum of negative

1 maximum of 1 in point 1 or 10 percent increments.

So let's go ahead and press OK to create that parameter so few things have happened here.

It's dropped this slicer onto my page and I'm going to resize my trending profit to create some room

here.

It's got the slicer.

And as I drag it you'll see that it contains the values the minimum negative one the default center

point of 0 and the maximum of one and not only that but at the bottom of my field list it's created

a new table with two new fields.

One is the price adjustment percentage which is calculated as it generates series function.

You can see that the three arguments that the function takes are the minimum the maximum and the increment

and the second field an actual measure essentially uses the selected value function to capture or harvest

whatever value is currently represented by the slicer.

And that means that as we move this slice slicer left and right we are producing a value using a measure

that we can now reference.

In other measure formulas because if we don't do that then this is kind of just sitting here as an island.

And it's not really impacting anything around it.

So the first new measure that we need to create is an adjusted price.

And if we go into a product lookup table you'll recall that we've already created a measure for average

retail price when I'm going to do now is create a new measure in this product table and I'm going to

name this measure adjusted price and I'll define adjusted price as the average retail price times one

plus whatever the currently selected value in my parameter slicer is.

So I can search for price adjustment and you see how it gives me that measure that was automatically

created that price adjustment percent value measure.

Remember that's capturing the current value of that slicer.

So by multiplying my average retail price by one plus that slicer value I'm essentially defining an

adjusted price that modifies my average retail price in steps of 10 percent from zero which is essentially

dropping the retail price to nothing or up to 200 percent which is essentially doubling the actual retail

price so that's step one.

A press enter to create that measure.

And now just to see if this is working let's add a multi-role card and click off of our slicer and a

multi-role card and the two fields that I want to pull in are my average retail price and my adjusted

price.

So right now because my price adjustment in the slicers set to zero these two fields should reflect

the same thing.

And I'm noticing we need to format here some selected just price and why don't we format this as currency.

So now if we move this slicer you see the adjusted price changing all the way up to a maximum which

should be double the original or actual average retail price which it is other side of the spectrum

we can drop all the way to the point where the adjusted price is zero.

So this is working exactly as we'd expect.

Let's set it to zero.

Let's kind of resize create a little bit of room here.

Here we go and I'm going to drag my multi-role card right underneath the slider there.

So that's step 1 and to the next step is to actually take that adjusted price and feed that into some

of our other calculations in our sales table like our revenue measure and our profit measure because

at the end of the day those are the actual values that I'm scenario testing here.

We're really trying to see what impact this type of pricing adjustment will have to actual bottom line

revenue and profit.

So let's go to our sales table and let's drill into our total revenue measure and remind ourselves how

this original revenue measure was calculated used some X to multiply order quantity by the product price

and the related product lookup table.

So rather than reinvent the wheel and create a new adjusted revenue measure from scratch let's copy

this entire measure press Enter create a new measure within the sales table and press control B and

paste that.

And now instead of total revenue this version of it is going to be named adjusted revenue.

Okay.

And I'm still multiplying order quantity from the sales table.

The only difference now is that instead of multiplying quantity by actual product price going to multiply

order quantity

by that measure that we just created or adjusted price.

So we've removed the related function.

We're not pointing to a related price field in the product table.

We're multiplying order quantities by this new adjusted price measure instead.

So when you press enter measures created there it is just that revenue.

And now the final step from a daks standpoint is to create one more.

And if you recall we had defined profit as revenue minus cost therefore adjusted profit is simply going

to equal our adjusted revenue minus the total cost.

So same exact formula except instead of plugging in total revenue we're plugging in adjusted revenue.

No lock that one in as well.

And now we've got adjusted profit and adjusted revenue.

So let's take this thing to the finish line and visualize what this looks like.

To do that I'm going to copy this line chart that we've created Paiste second instance which we can

pull in right here.

It's going to kind of rearrange things a bit.

There we go.

Now I don't need my analytics tools here.

Get rid of my trend line get rid of my forecast we're going to go back to fields and instead of simply

showing total profit I'm going to show total profit right alongside adjusted profit.

Okay.

So now both are being visualized here.

And at the moment both values are exactly equal because my price adjustment is set to zero.

Now if I bump up that adjustment to point two or 20 percent look what happens.

Now we see that adjusted profit is $549 total profit or actual profit is 340 574.

So what that tells us is that with a 20 percent lift in the product price for the HWC logo cap we could

potentially increase weekly profit by about $200.

And then if we adjust in the other direction and if we reduce product prices you'll see that these kind

of reverse order right all the way down to a 50 percent reduction in price means that you're actually

losing money on that hat.

So you can see where the breakeven points are you can see how these different scenarios play out.

And remember this is still at the product level.

So everything we're looking at here is related to this logo cap remember we can go back we can drill

into a different product like the water bottle and we can see a completely different trend and test

completely new scenarios with each product individually.

So let's go ahead and just kind of tweak formatting get things to a good point here will default to

a price adjustment parameter value of 0 stretch this out a little bit.

So there you go.

Good example of how to use these parameter tools to create different types of interactive scenarios

inside of your power be reports.