Power Pivot, Power BI, and Microsoft Excel techniques for Accounting and Finance Professionals.

Guest Post from Ken Puls: Determine Effective Tax Rate

Excel MVP Forever.  PowerPivot Pro On the Rise!

Back in December I wrote about Ken Puls’ role in inspiring the book, and described him as a DAX convert (and also someone who used to intimidate me, in a good way, at MVP Summits back when I was a newbie on the Excel team).  Well I’m happy to welcome a guest post from Ken today.

I think it’s particularly valuable to hear from a) someone who is still relatively new to the PowerPivot journey like Ken  and b) someone other than me, period – since both provide a very different perspective, and that helps us learn.

So, take it away Ken… Smile

Background

In British Columbia we’ve been working with a 12% HST (Harmonized Sales Tax) for the past 1.5 years. Effective April 1, 2013, we’ll be going back to a system with a separate 7% Provincial Sales Tax (PST) and our national 5% Goods and Services Tax (GST) instead. In our case, we wanted to look at sales that will not be PST taxable under the new tax structure, meaning that the effective tax on these sales will drop from 12% to 5%.

So assuming that we have the following tables in an Excel worksheet and the name of the tax table is tblTaxRates, it’s really easy to get the effective tax rate for any date:

tax-1

We simply add a VLOOKUP to the sales table with the following formula copied down the sales table:

=VLOOKUP([@Date],tblTaxRates[#All],2,TRUE)

Easy stuff for any Excel pro. But what do you do if your sales table is in PowerPivot, like this?

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Modeling Viral and Marketing Growth, Part 3 of 3

Why am I doing this in PowerPivot?  Primarily as a challenge.

This is a question I should have answered before I even started down this road.

To be honest, I did it primarily as a challenge – to stretch my brain a little bit.  If I were faced with this exact same task in my daily work, undoubtedly I would just use normal Excel formulas.  In some ways, this modeling exercise has been a deliberate misuse of PowerPivot.  A handful of parameters with no source data whatsoever – this is NOT what the PowerPivot engine was built for, which explains why the PowerPivot solution is actually significantly more difficult than the Excel solution.

“So you’ve been deliberately wasting our time??”

No, I do think there is real value in this exercise, for two reasons:

  1. Brain-stretching with new techniques always comes in handy later.  For instance, on the first post Sergey commented that he’d been thinking about loan amortization measures and this could be applied to that.
  2. I can see this technique being added, as a supplement, to a broader PowerPivot model.  For instance, a model containing lots of real customer data over time, and then a [Projected Customers] measure that forecasts future customer populations based on various assumptions and/or marketing investments.

So with that in mind, here it is:  the final installment of viral/marketing modeling in PowerPivot.

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Modeling Viral and Marketing Growth, Part Two

 
Picking up from last week’s post, the first thing I want to show is that I kinda cheated last time.  To see what I mean, let’s look at Rahul’s original chart:

Viral Marketing Growth in PowerPivot:  Customers Flatten Out Over Time

In Rahul’s Viral Model, Total Customers “Goes Flat” Quickly

In Rahul’s model, if we start With 5,000 initial customers and a viral factor of 0.2, we end up with 6,250 customers and we never get any more!

But in my model from last week, if I use 5,000 and 0.2, customers keep piling up exponentially:

Exponential Ongoing Viral Growth in PowerPivot

In My Model from Last Week, Customers Never Go Flat –
They Just Keep Growing Exponentially

So why the difference?

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Modeling Viral Growth and Marketing in PowerPivot

A Tale of Two Charts

Let’s say you operate a business that relies heavily on “word of mouth” – customers recommending your product/service to their friends and colleagues. Or at least, you THINK it relies heavily on that sort of thing.

You need to decide how much to spend on traditional advertising – to supplement the social/viral marketing that your customers do on your behalf.  Take a look at each of these two charts – the captions for each attempt to capture the knee-jerk conclusions you might draw:

 
Modeling Viral Growth versus Traditional Direct Advertising in PowerPivot

“Advertising?  We Don’t Need No Stinking Advertising!
That is SO Yesterday!  We’re Viral Baby!”

Modeling Viral Growth versus Traditional Direct Advertising in PowerPivot

“All These Youngsters and Their ‘Viral This’ and ‘Social Media That’ – That’s All Just Fancy Excuses to Be Lazy – You Clearly Need to BRING Your Message to the Customer”

If chart 1 reflected reality, you may opt to spend very little on traditional advertising.  But in a chart 2 world, you’d be silly to rely on viral growth.  But which one (if either of them) describes your situation?

Back in October, Rahul Vohra (CEO of Rapportive) wrote a two-part blog series on this topic, posted here on LinkedIn.  I took a note, at the time, to revisit his work and “convert” it to PowerPivot.

It’s a very different kind of problem from what I normally do in PowerPivot – this isn’t about analyzing data I already have, but about calculating future outcomes based on a handful of parameters.  And that leads to some different kinds of thinking, as you will see.

 

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New Customers Per Day Generalized to “New Customers per Month,” etc.

 
 
A Generalized New Customers (or unique visitors) in Time Period - per Month, Year, Etc. in PowerPivot

A Generalized “New Customers in Time Period” Solution, Inspired by Tuesday’s Post

David Hager’s post on Tuesday really planted a seed in my brain.  And then a comment on that post from Charlie got me thinking further.

How can we extend the “New Customers per Day” concept to become “New Customers in <Any Period of Time>?”  New Customers per Month for instance.

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New Customers per Day – Technique by David Hager

 
Hi folks.  Today we are fortunate to have a guest post from David Hager.  He explains a technique for counting how many new customers are acquired or “seen” each day.  (I’m going to think about whether this has web site traffic analysis uses as well – New Visitor vs. Returning Visitor sort of stuff).

***UPDATE:  Inspired by David’s work, I extended this technique to cover per Month, Year, Week, etc.:  http://powerpivotpro.com/2013/01/new-customers-per-day-generalized-to-new-customers-per-month-etc/

Count of New Customers per Day in PowerPivot

By David Hager

Information vital to any company is being able to identify customer patterns. Counting how many new customers per day a company acquires is perhaps the most important data that can be obtained. The following model will show how this can be done with DAX measures in PowerPivot. For comparison, two other measures are included in the Pivot Table (shown in Figure 1).

TotalCustomersPerDay:

=COUNTROWS(Table1)

Note that COUNT(Table1[CustomerID]) would return the same result.

DistinctCustomersPerDay:

=DISTINCTCOUNT(Table1[CustomerID])

This measure returns the number of unique customers.

NewCustomersPerDay:

=CALCULATE([DistinctCustomersPerDay],DATESBETWEEN(Table1[Date], BLANK(),LASTDATE(Table1[Date])), All(Table1[Date]))
CALCULATE([DistinctCustomersPerDay],DATESBETWEEN(Table1[Date], BLANK(),LASTDATE(Table1[Date])-1), All(Table1[Date]))

This formula shows the real power of DAX. The first part of the formula (highlighted in green) returns the running total of the DistinctCustomersPerDay measure. The second part of the formula (highlighted in yellow) returns the running total of the DistinctCustomersPerDay measure up to the previous day of the pivot table row context. The difference affords the number of new customers per day.

 

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CFO Magazine Webcast on Monday

 
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If You’re a CPA, and Need CPE Credit, Consider
Watching Me Show Off PowerPivot for an Hour

I’ve had an interesting new experience this week – I recorded a webcast for CFO Magazine.  Bill does these all the time and asked if I’d be interested in doing one this month. 

I’m usually game for this sort of thing, and it did turn out to be fun.  Squeezing a whirlwind tour of PowerPivot as well as a bunch of specific how-to techniques into a single hour – there’s a certain pace to that which I kinda liked.  I had to be thrifty with what I showed.

(I suspect Bill is a lot faster at recording these than I am however – I spent probably 20 hours recording a one hour webcast.)

Anyway, two key points:

  1. The webcast is not free.  It is certified as training for accountants and there is a $149 fee for the session, so unless you are a CPA, I suspect you are going to skip this one.
  2. It includes a copy of my book.  The $149 fee for the course does not go to me – that goes to the CFO Mag organization.  But you do get a copy of the book, and yes, they do pay me for the book.

What I Cover in the Webcast

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NETWORKDAYS() Equivalent in PowerPivot?

 
There is no NETWORKDAYS() Function in PowerPivot

There is no NETWORKDAYS() Function in PowerPivot

A Post on Thanksgiving?

Normally I would take today off and not have a post.  But I’ve posted so many updates about the book lately that it’s got to feel like this place has turned into an advertisement shop, and I want to keep the “real” content up.

So consider this a Thanksgiving “bonus” post – me giving thanks for everyone ordering the book, and everyone tolerating my desire to post updates about “my baby” every five minutes Smile

A Missing Function

It’s funny, I’ve never used NETWORKDAYS() much (if at all) in regular Excel, so I didn’t realize this until someone posted on the MrExcel forums – how do I do a NETWORKDAYS()-style calculated column?

Something like this:

NETWORKDAYS in PowerPivot

Desired Result

So how do we get to this?

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Budget Calculations That Change by Level

 
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[Pct Sold Smart] Measure Matches [Shape Pct Sold] at the Shape Level (Orange Cells) But Matches [Raw Pct Sold] Down at the Color Level

Quick Post Today

I’m halfway on vacation today in Florida, visiting family, so I will keep this brief.  I saw this question today on the forums.

Sales and Stock Tables

The question is pretty simple – I have a Sales table and a Stock table:

image

Sales Table – the Numerator of our Pct Sold Measure

image

Stock Table – the Denominator of our Pct Sold Measure

And we want a measure that returns Percentage Sold. 

But there’s a twist:  at the Shape level, we want to use something other than Stock as the total.  We want to use another cap, a Shape-Level cap:

image

At the Shape Level, We Want to Use These Values (Instead of Stock) as the Denominator

First Step:  Lookup Tables

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Same Store Sales Continued – Using Store Open/Close Dates

 
In a comment on Tuesday’s post, Cory asked the following question:

“I want to use the stores start date to determine if it should be included in the same store calculation or not. Y/Y SSS calculation regardless if there are sales for that store this year or last for the specific date range I’m looking at (typically by month for last 13 months). The other twist to my SSS calculation is the store must be open for at least 15 months before it is included in my SSS Total. I hope my question makes sense. Thanks for any guidance you or anyone can offer.”

Remember that in my first post, if a store had sales last year, and this year, I included it in the SSS (Same Store Sales) calc.

If we have columns in our data indicating the date a store opened (and when it closed), it’s a very rational thing to want to use that instead.

So I invented some new columns on my fictional Stores table:

I'm Going to Use These (Fictional) Store Open and Close Dates to Drive my PowerPivot Same Store Sales Calc

I’m Going to Use These (Fictional) Store Open and Close Dates
to Drive my PowerPivot Same Store Sales Calc

So, how do we do that?

First, I create a measure to calculate when a store opened.  I add this to the Stores table itself:

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