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These are the user uploaded subtitles that are being translated: 1 00:00:00,780 --> 00:00:04,830 All right I want to take a minute and walk through a slightly more advanced demo. 2 00:00:04,830 --> 00:00:09,500 We're going to use what's called a what if parameter to do some scenario testing. 3 00:00:09,900 --> 00:00:15,330 And if you look at your modeling tab you'll see this new parameter button that launches a dialog box 4 00:00:15,330 --> 00:00:16,950 that looks like this. 5 00:00:16,950 --> 00:00:24,480 Now essentially these parameters are preset daks measures that produce values within a given range based 6 00:00:24,480 --> 00:00:31,470 on user inputs the data type the minimum the maximum the increment and the default value. 7 00:00:31,470 --> 00:00:37,660 And these can be really good tools to use for things like forecasting or scenario testing. 8 00:00:37,680 --> 00:00:42,990 So the example you see here and the example that we're going to practice is creating something like 9 00:00:42,990 --> 00:00:50,370 a price adjustment percentage captured within a parameter so that we can compare total revenue based 10 00:00:50,370 --> 00:00:57,210 on actual information and actual prices against an adjusted revenue based on the parameter adjusted 11 00:00:57,210 --> 00:00:58,240 price. 12 00:00:58,350 --> 00:01:00,980 And I'm going to show you exactly how that works. 13 00:01:01,020 --> 00:01:07,560 Now one interesting thing to note is that when you create a parameter using the dialog box power be-I 14 00:01:07,560 --> 00:01:14,790 actually generates and creates a new table for you with daks calculations already in place for the parameter 15 00:01:14,850 --> 00:01:16,650 and the parameter value. 16 00:01:16,650 --> 00:01:21,810 So those generate series and selected value functions that you see at the bottom of the screen. 17 00:01:21,810 --> 00:01:27,630 Those are automatically created behind the scenes although we could build them from scratch if we chose 18 00:01:27,630 --> 00:01:28,630 to do so. 19 00:01:29,040 --> 00:01:36,550 So let's head back to our report and try creating a scenario test of our own using these parameters. 20 00:01:36,550 --> 00:01:36,810 All right. 21 00:01:36,810 --> 00:01:41,290 We're going to head to the product detail tab and you're going to want to follow along closely with 22 00:01:41,290 --> 00:01:46,030 this because there will be a number of steps and we're going to have to get back into our daks world 23 00:01:46,390 --> 00:01:49,510 and write a few new measures to make this all work. 24 00:01:49,510 --> 00:01:54,960 So first things first on the modeling tab Here's my new parameter option. 25 00:01:55,180 --> 00:01:57,400 Let's go ahead and launch the dialog box. 26 00:01:58,350 --> 00:02:08,750 Now the settings that I'm going to use given a name something like price adjustment with a percentage 27 00:02:09,520 --> 00:02:14,710 and that's just part of the title it's just text because the values that we're going to use as you'll 28 00:02:14,710 --> 00:02:21,120 see will eventually translate into percentages the data type is a decimal number. 29 00:02:21,400 --> 00:02:29,970 And let's set the minimum to negative 1 maximum to 1 the increment at zero point 1. 30 00:02:30,290 --> 00:02:37,170 And the default 2 0 and we can keep this add slicer to page activate it. 31 00:02:37,190 --> 00:02:44,390 So to recap we've essentially created a scale of values defaulting to zero with a minimum of negative 32 00:02:44,390 --> 00:02:49,520 1 maximum of 1 in point 1 or 10 percent increments. 33 00:02:49,520 --> 00:02:56,160 So let's go ahead and press OK to create that parameter so few things have happened here. 34 00:02:57,080 --> 00:03:05,170 It's dropped this slicer onto my page and I'm going to resize my trending profit to create some room 35 00:03:05,170 --> 00:03:05,640 here. 36 00:03:06,750 --> 00:03:08,620 It's got the slicer. 37 00:03:08,970 --> 00:03:15,670 And as I drag it you'll see that it contains the values the minimum negative one the default center 38 00:03:15,670 --> 00:03:24,440 point of 0 and the maximum of one and not only that but at the bottom of my field list it's created 39 00:03:24,440 --> 00:03:27,760 a new table with two new fields. 40 00:03:27,980 --> 00:03:34,310 One is the price adjustment percentage which is calculated as it generates series function. 41 00:03:34,350 --> 00:03:39,320 You can see that the three arguments that the function takes are the minimum the maximum and the increment 42 00:03:40,340 --> 00:03:48,680 and the second field an actual measure essentially uses the selected value function to capture or harvest 43 00:03:49,100 --> 00:03:53,540 whatever value is currently represented by the slicer. 44 00:03:53,540 --> 00:04:00,650 And that means that as we move this slice slicer left and right we are producing a value using a measure 45 00:04:01,250 --> 00:04:02,690 that we can now reference. 46 00:04:02,690 --> 00:04:09,510 In other measure formulas because if we don't do that then this is kind of just sitting here as an island. 47 00:04:09,740 --> 00:04:12,790 And it's not really impacting anything around it. 48 00:04:12,800 --> 00:04:18,140 So the first new measure that we need to create is an adjusted price. 49 00:04:18,140 --> 00:04:24,740 And if we go into a product lookup table you'll recall that we've already created a measure for average 50 00:04:24,740 --> 00:04:31,970 retail price when I'm going to do now is create a new measure in this product table and I'm going to 51 00:04:31,970 --> 00:04:44,980 name this measure adjusted price and I'll define adjusted price as the average retail price times one 52 00:04:45,370 --> 00:04:51,010 plus whatever the currently selected value in my parameter slicer is. 53 00:04:51,250 --> 00:04:56,560 So I can search for price adjustment and you see how it gives me that measure that was automatically 54 00:04:56,560 --> 00:05:00,960 created that price adjustment percent value measure. 55 00:05:01,090 --> 00:05:05,780 Remember that's capturing the current value of that slicer. 56 00:05:05,980 --> 00:05:13,540 So by multiplying my average retail price by one plus that slicer value I'm essentially defining an 57 00:05:13,540 --> 00:05:21,190 adjusted price that modifies my average retail price in steps of 10 percent from zero which is essentially 58 00:05:21,190 --> 00:05:28,540 dropping the retail price to nothing or up to 200 percent which is essentially doubling the actual retail 59 00:05:28,540 --> 00:05:31,740 price so that's step one. 60 00:05:31,760 --> 00:05:34,360 A press enter to create that measure. 61 00:05:34,550 --> 00:05:42,110 And now just to see if this is working let's add a multi-role card and click off of our slicer and a 62 00:05:42,110 --> 00:05:48,890 multi-role card and the two fields that I want to pull in are my average retail price and my adjusted 63 00:05:48,890 --> 00:05:50,500 price. 64 00:05:50,530 --> 00:05:56,260 So right now because my price adjustment in the slicers set to zero these two fields should reflect 65 00:05:56,260 --> 00:05:57,470 the same thing. 66 00:05:57,790 --> 00:06:06,900 And I'm noticing we need to format here some selected just price and why don't we format this as currency. 67 00:06:08,100 --> 00:06:18,430 So now if we move this slicer you see the adjusted price changing all the way up to a maximum which 68 00:06:18,430 --> 00:06:25,410 should be double the original or actual average retail price which it is other side of the spectrum 69 00:06:26,530 --> 00:06:30,740 we can drop all the way to the point where the adjusted price is zero. 70 00:06:30,760 --> 00:06:33,480 So this is working exactly as we'd expect. 71 00:06:34,450 --> 00:06:35,770 Let's set it to zero. 72 00:06:36,640 --> 00:06:41,170 Let's kind of resize create a little bit of room here. 73 00:06:42,350 --> 00:06:48,150 Here we go and I'm going to drag my multi-role card right underneath the slider there. 74 00:06:48,370 --> 00:06:56,110 So that's step 1 and to the next step is to actually take that adjusted price and feed that into some 75 00:06:56,110 --> 00:07:02,830 of our other calculations in our sales table like our revenue measure and our profit measure because 76 00:07:02,830 --> 00:07:08,340 at the end of the day those are the actual values that I'm scenario testing here. 77 00:07:08,410 --> 00:07:15,130 We're really trying to see what impact this type of pricing adjustment will have to actual bottom line 78 00:07:15,580 --> 00:07:16,970 revenue and profit. 79 00:07:17,350 --> 00:07:24,610 So let's go to our sales table and let's drill into our total revenue measure and remind ourselves how 80 00:07:24,610 --> 00:07:33,370 this original revenue measure was calculated used some X to multiply order quantity by the product price 81 00:07:33,480 --> 00:07:35,970 and the related product lookup table. 82 00:07:36,400 --> 00:07:43,720 So rather than reinvent the wheel and create a new adjusted revenue measure from scratch let's copy 83 00:07:43,720 --> 00:07:51,880 this entire measure press Enter create a new measure within the sales table and press control B and 84 00:07:51,880 --> 00:07:53,080 paste that. 85 00:07:53,380 --> 00:07:59,500 And now instead of total revenue this version of it is going to be named adjusted revenue. 86 00:07:59,830 --> 00:08:00,340 Okay. 87 00:08:00,400 --> 00:08:05,110 And I'm still multiplying order quantity from the sales table. 88 00:08:05,110 --> 00:08:13,060 The only difference now is that instead of multiplying quantity by actual product price going to multiply 89 00:08:13,090 --> 00:08:14,010 order quantity 90 00:08:17,410 --> 00:08:23,250 by that measure that we just created or adjusted price. 91 00:08:23,470 --> 00:08:25,760 So we've removed the related function. 92 00:08:25,810 --> 00:08:29,720 We're not pointing to a related price field in the product table. 93 00:08:29,830 --> 00:08:34,620 We're multiplying order quantities by this new adjusted price measure instead. 94 00:08:34,990 --> 00:08:40,750 So when you press enter measures created there it is just that revenue. 95 00:08:40,830 --> 00:08:45,700 And now the final step from a daks standpoint is to create one more. 96 00:08:46,170 --> 00:08:56,430 And if you recall we had defined profit as revenue minus cost therefore adjusted profit is simply going 97 00:08:56,430 --> 00:09:03,120 to equal our adjusted revenue minus the total cost. 98 00:09:03,120 --> 00:09:09,670 So same exact formula except instead of plugging in total revenue we're plugging in adjusted revenue. 99 00:09:09,790 --> 00:09:12,220 No lock that one in as well. 100 00:09:12,220 --> 00:09:15,640 And now we've got adjusted profit and adjusted revenue. 101 00:09:15,660 --> 00:09:19,710 So let's take this thing to the finish line and visualize what this looks like. 102 00:09:19,950 --> 00:09:28,410 To do that I'm going to copy this line chart that we've created Paiste second instance which we can 103 00:09:28,410 --> 00:09:29,620 pull in right here. 104 00:09:32,690 --> 00:09:37,150 It's going to kind of rearrange things a bit. 105 00:09:37,160 --> 00:09:38,960 There we go. 106 00:09:39,070 --> 00:09:42,170 Now I don't need my analytics tools here. 107 00:09:42,260 --> 00:09:50,190 Get rid of my trend line get rid of my forecast we're going to go back to fields and instead of simply 108 00:09:50,190 --> 00:09:56,870 showing total profit I'm going to show total profit right alongside adjusted profit. 109 00:09:57,180 --> 00:09:57,770 Okay. 110 00:09:58,080 --> 00:10:00,520 So now both are being visualized here. 111 00:10:00,720 --> 00:10:07,670 And at the moment both values are exactly equal because my price adjustment is set to zero. 112 00:10:07,680 --> 00:10:14,280 Now if I bump up that adjustment to point two or 20 percent look what happens. 113 00:10:14,280 --> 00:10:24,250 Now we see that adjusted profit is $549 total profit or actual profit is 340 574. 114 00:10:24,600 --> 00:10:32,550 So what that tells us is that with a 20 percent lift in the product price for the HWC logo cap we could 115 00:10:32,550 --> 00:10:36,890 potentially increase weekly profit by about $200. 116 00:10:37,020 --> 00:10:43,080 And then if we adjust in the other direction and if we reduce product prices you'll see that these kind 117 00:10:43,080 --> 00:10:50,370 of reverse order right all the way down to a 50 percent reduction in price means that you're actually 118 00:10:50,370 --> 00:10:53,080 losing money on that hat. 119 00:10:53,190 --> 00:10:59,060 So you can see where the breakeven points are you can see how these different scenarios play out. 120 00:10:59,220 --> 00:11:01,530 And remember this is still at the product level. 121 00:11:01,530 --> 00:11:09,630 So everything we're looking at here is related to this logo cap remember we can go back we can drill 122 00:11:09,630 --> 00:11:18,350 into a different product like the water bottle and we can see a completely different trend and test 123 00:11:18,350 --> 00:11:22,690 completely new scenarios with each product individually. 124 00:11:22,730 --> 00:11:29,160 So let's go ahead and just kind of tweak formatting get things to a good point here will default to 125 00:11:29,160 --> 00:11:36,390 a price adjustment parameter value of 0 stretch this out a little bit. 126 00:11:36,410 --> 00:11:37,510 So there you go. 127 00:11:37,520 --> 00:11:43,430 Good example of how to use these parameter tools to create different types of interactive scenarios 128 00:11:43,910 --> 00:11:45,750 inside of your power be reports. 14156

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