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All right I want to take a minute and walk through a slightly more advanced demo.
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We're going to use what's called a what if parameter to do some scenario testing.
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And if you look at your modeling tab you'll see this new parameter button that launches a dialog box
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that looks like this.
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Now essentially these parameters are preset daks measures that produce values within a given range based
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on user inputs the data type the minimum the maximum the increment and the default value.
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And these can be really good tools to use for things like forecasting or scenario testing.
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So the example you see here and the example that we're going to practice is creating something like
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a price adjustment percentage captured within a parameter so that we can compare total revenue based
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on actual information and actual prices against an adjusted revenue based on the parameter adjusted
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price.
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And I'm going to show you exactly how that works.
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Now one interesting thing to note is that when you create a parameter using the dialog box power be-I
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actually generates and creates a new table for you with daks calculations already in place for the parameter
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and the parameter value.
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So those generate series and selected value functions that you see at the bottom of the screen.
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Those are automatically created behind the scenes although we could build them from scratch if we chose
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to do so.
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So let's head back to our report and try creating a scenario test of our own using these parameters.
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All right.
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We're going to head to the product detail tab and you're going to want to follow along closely with
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this because there will be a number of steps and we're going to have to get back into our daks world
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and write a few new measures to make this all work.
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So first things first on the modeling tab Here's my new parameter option.
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Let's go ahead and launch the dialog box.
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Now the settings that I'm going to use given a name something like price adjustment with a percentage
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and that's just part of the title it's just text because the values that we're going to use as you'll
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see will eventually translate into percentages the data type is a decimal number.
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And let's set the minimum to negative 1 maximum to 1 the increment at zero point 1.
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And the default 2 0 and we can keep this add slicer to page activate it.
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So to recap we've essentially created a scale of values defaulting to zero with a minimum of negative
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1 maximum of 1 in point 1 or 10 percent increments.
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So let's go ahead and press OK to create that parameter so few things have happened here.
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It's dropped this slicer onto my page and I'm going to resize my trending profit to create some room
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here.
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It's got the slicer.
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And as I drag it you'll see that it contains the values the minimum negative one the default center
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point of 0 and the maximum of one and not only that but at the bottom of my field list it's created
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a new table with two new fields.
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One is the price adjustment percentage which is calculated as it generates series function.
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You can see that the three arguments that the function takes are the minimum the maximum and the increment
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and the second field an actual measure essentially uses the selected value function to capture or harvest
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whatever value is currently represented by the slicer.
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And that means that as we move this slice slicer left and right we are producing a value using a measure
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that we can now reference.
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In other measure formulas because if we don't do that then this is kind of just sitting here as an island.
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And it's not really impacting anything around it.
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So the first new measure that we need to create is an adjusted price.
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And if we go into a product lookup table you'll recall that we've already created a measure for average
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retail price when I'm going to do now is create a new measure in this product table and I'm going to
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name this measure adjusted price and I'll define adjusted price as the average retail price times one
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plus whatever the currently selected value in my parameter slicer is.
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So I can search for price adjustment and you see how it gives me that measure that was automatically
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created that price adjustment percent value measure.
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Remember that's capturing the current value of that slicer.
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So by multiplying my average retail price by one plus that slicer value I'm essentially defining an
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adjusted price that modifies my average retail price in steps of 10 percent from zero which is essentially
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dropping the retail price to nothing or up to 200 percent which is essentially doubling the actual retail
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price so that's step one.
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A press enter to create that measure.
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And now just to see if this is working let's add a multi-role card and click off of our slicer and a
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multi-role card and the two fields that I want to pull in are my average retail price and my adjusted
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price.
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So right now because my price adjustment in the slicers set to zero these two fields should reflect
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the same thing.
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And I'm noticing we need to format here some selected just price and why don't we format this as currency.
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So now if we move this slicer you see the adjusted price changing all the way up to a maximum which
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should be double the original or actual average retail price which it is other side of the spectrum
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we can drop all the way to the point where the adjusted price is zero.
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So this is working exactly as we'd expect.
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Let's set it to zero.
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Let's kind of resize create a little bit of room here.
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Here we go and I'm going to drag my multi-role card right underneath the slider there.
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So that's step 1 and to the next step is to actually take that adjusted price and feed that into some
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of our other calculations in our sales table like our revenue measure and our profit measure because
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at the end of the day those are the actual values that I'm scenario testing here.
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We're really trying to see what impact this type of pricing adjustment will have to actual bottom line
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revenue and profit.
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So let's go to our sales table and let's drill into our total revenue measure and remind ourselves how
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this original revenue measure was calculated used some X to multiply order quantity by the product price
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and the related product lookup table.
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So rather than reinvent the wheel and create a new adjusted revenue measure from scratch let's copy
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this entire measure press Enter create a new measure within the sales table and press control B and
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paste that.
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And now instead of total revenue this version of it is going to be named adjusted revenue.
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Okay.
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And I'm still multiplying order quantity from the sales table.
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The only difference now is that instead of multiplying quantity by actual product price going to multiply
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order quantity
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by that measure that we just created or adjusted price.
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So we've removed the related function.
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We're not pointing to a related price field in the product table.
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We're multiplying order quantities by this new adjusted price measure instead.
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So when you press enter measures created there it is just that revenue.
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And now the final step from a daks standpoint is to create one more.
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And if you recall we had defined profit as revenue minus cost therefore adjusted profit is simply going
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to equal our adjusted revenue minus the total cost.
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So same exact formula except instead of plugging in total revenue we're plugging in adjusted revenue.
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No lock that one in as well.
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And now we've got adjusted profit and adjusted revenue.
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So let's take this thing to the finish line and visualize what this looks like.
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To do that I'm going to copy this line chart that we've created Paiste second instance which we can
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pull in right here.
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It's going to kind of rearrange things a bit.
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There we go.
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Now I don't need my analytics tools here.
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Get rid of my trend line get rid of my forecast we're going to go back to fields and instead of simply
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showing total profit I'm going to show total profit right alongside adjusted profit.
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Okay.
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So now both are being visualized here.
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And at the moment both values are exactly equal because my price adjustment is set to zero.
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Now if I bump up that adjustment to point two or 20 percent look what happens.
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Now we see that adjusted profit is $549 total profit or actual profit is 340 574.
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So what that tells us is that with a 20 percent lift in the product price for the HWC logo cap we could
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potentially increase weekly profit by about $200.
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And then if we adjust in the other direction and if we reduce product prices you'll see that these kind
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of reverse order right all the way down to a 50 percent reduction in price means that you're actually
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losing money on that hat.
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So you can see where the breakeven points are you can see how these different scenarios play out.
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And remember this is still at the product level.
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So everything we're looking at here is related to this logo cap remember we can go back we can drill
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into a different product like the water bottle and we can see a completely different trend and test
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completely new scenarios with each product individually.
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So let's go ahead and just kind of tweak formatting get things to a good point here will default to
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a price adjustment parameter value of 0 stretch this out a little bit.
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So there you go.
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Good example of how to use these parameter tools to create different types of interactive scenarios
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inside of your power be reports.
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