Tableau Set Up

Tableau Set Up

Tableau is a data visualization and analytics tool. One great thing about Tableau is that they provide a free product called Tableau Public, which is perfect for learning and exploring BI and visualizations. We will use this to look at and explore "The Company" data but also show you how to use the tool itself as BI tools are very useful in People Analytics.

Tableau Public is very similar to their commercial versions of Tableau. Two of the big downsides are that you can only connect to a limited number of data sources and you always save your workbooks publicly. While this is obviously not ideal for People Analytics work in the real world, this is not an issue for our needs on this blog. The paid versions, Tableau Server and Tableau Online, can solve your data needs when working with data you need to keep secure.

I will walk you through how to download and setup Tableau Public on your computer and go over some things to get you started.

Setting Up Tableau Public:

• Download Tableau Public Here
• Make sure you sign up for a Tableau Public account as this is how you will be able to save your workbooks!
• When you get Tableau Public downloaded this is what you will see 

1. This is where you can select the data you will be using in Tableau. 
2.  If you need some inspiration for visuals you can create. I highly recommend the "Viz of the day" link. You will find some really great visuals there.
3. The Resources section also has some trainings and sample data you can use. 

• Here is the data we will be checking. If you created your own data you might have gotten different results because of all the random formulas so if your visuals look different that could be the issue!
  
  When you have the data downloaded you can connect to it by clicking "Text File" because it is a CSV file.

• When the data is connected you should see this layout.

1. This is where you can check your data.
2. In this area you can join different data together.
3. Here you can see the data file you are using and make changes to which file you are using.

On the bottom left corner you will see this:

Clicking on Sheet 1 will bring you to your first are to create visuals in Tableau. If you click the tab to the right of Sheet 1 you will create a new sheet. The button to the right will allow you to create a Dashboard and finally the button to the right of that a Story.

Have fun exploring the data and if you have any questions there are many resources online like Tableaus community page to help you learn. I will write more about Tableau and how you can use it in future posts.

Creating "The Company" Data (pt.1)

http://dilbert.com/strip/2006-11-11

As stated previously, one of the things we wanted to work on with Koluit is something called "The Company". This is a fake company that will be using discuss different People Operations/Analytics ideas. The biggest part of this involved making fake data that we could use to make "The Company" seem more real. Here we will walkthrough how this data was created and the reasons behind some of the steps we took.


Data Creation (Basic Info): First to create the data we started with some basic information from FakeNameGenerator.com.

1. Given Name
2. Surname
3. Gender
4. StreetAddress
5. City
6. State
7. StateFull
8. Zipcode
9. Country (This was just a two letter country code)
10. CountryFull
11. Birthday
12. Age

Whats great about this site is you are able to pick Name Sets and Countries. We ran a few different lists because we did not want an equal number of each country.

We ran a large American set (4000 names) because this is where my fake company's HQ and majority of offices will be. We then ran a few smaller lists, Japanese (50 names),  Chinese (72 names), United Kingdom (250 names), and Norway (150 names).


Now while this gave us something to work with, there is still a lot more to add and some data cleaning that needs to be done.


Adding Ethnicity (US Only)

Fakenamegenerator.com was able to provide gender for the names that they gave but we did not see an option for ethnicity.  To do this we created a mapping table with the EEOC defined ethnicities (see here).  You can find the Mapping Table here. We decided to have the employees map to an ethnicity based on a random number they would be given. While we could have given them a number from 1-7 (which is the number of ethnicity options) we decided against this because this would spread the number of ethnicities equally.  This isn't very realistic. We wanted to make this company similar to your average Tech company, which currently leans very white and asian (Google, Facebook, Salesforce, LinkedIn, and etc.). We are setting up my fictions company as similar to a real company so that hopefully we can talk about some of these real life issues including diversity/inclusion.

We used the randombetween(1,100) function in a new column to give a random number between 1-100.

The we created another column called Ethnicity and added this formula, starting at cell P2.

=if(O2<=52,Mapping!$B$3,if(O2<85,Mapping!$B$6,if(O2<91,Mapping!$B$2,if(O2<96,Mapping!$B$4,if(O2<98,Mapping!$B$8,if(O2=99,Mapping!$B$5,if(O2=100,Mapping!$B$7,"ERROR")))))))

If you are new to Excel type formulas this might be overwhelming. Just know that if the random number is:

• Less than or equal to 52 the formula went to the mapping table and showed B3 which is "White"
• Less than 91 is B2  = "Hispanic or Latino"
• Less than 96  B4= "Black or African American"
• Less than 98 is B8 = "Two or More Races"
• Equal to 99 is B5 = "Native Hawaiian or Pacific Islander"
• Equal to 100 is B7 = "Native American or Alaska Native" 

*If you noticed we made a mistake in the formula, good catch! Anytime 98 was the number we got the "ERROR" as a result. It should have been <=98 not <. For those errors, I replaced them with the ethnicity "White".

Office Location Creation:

This field was pretty easy to create because most of the information was determined when we created the original data. Japan, China (which we changed to Hong Kong), UK and Norway were all given one office location each. We chose a major city in each country and all of the employees from the country were put into that location.

The tricky part was deciding how we wanted to break up the 4k US employees. We figured at first most of the work we would do would be US focused so deciding how we wanted to create this involved a little more thought. Obviously companies have reasons for opening different offices in different locations but its a little hard to make those decisions without any real situations causing us to make those decisions. To help with this (and determining start dates) we created an "About Us" post for "The Company". We decided on 3 offices for the US. One HQ in NYC, one Technology HQ in Boulder, Colorado, and finally another office in San Jose, California.

Why did we choose those locations? Honestly it was somewhat random. We just knew we wanted to have more than two offices and have our offices split by them being Corporate and Tech focused. We also did not want to have them too close together. More offices may be added later. Or some of these offices may be split.

Start Date / Termination Date:

Most of the fields we just wanted to have data in first so we could see it all and then tweak and clean the data once it was all there. This was especially true for the Start and Termination Date.

To create Start Dates we broke the data up by Office location to start. For each office we would pick one employee and manually match them to the date on the About Us page. From there we used this formula:

=[First Employee's Start Date]+(7*RANDBETWEEN(1,510))

The "First Employee's Start Date" is just a reference to the manually created date. We also changed the randomdbetween number from 510 to smaller numbers for newer office locations. We didn't want to have employees with start dates to far into the future.

So what this calculation is doing is using the start date of the fist employee and adding a random number of weeks to it to determine the start date for every other employee.

Termination Date:

For Termination Date we used this formula:

=if(RANDBETWEEN(1,10)<=3,($R2+(7*RANDBETWEEN(3,250))+RANDBETWEEN(0,4)),"")

So because we only wanted some employees to have a Termination date we randomly selected a number between 1 and 10. If that number was less than or equal to 3, it then randomly created a termination date. The Termination Date is the Start Date + 7*random number between 3 and 250. This way the termination date ranges at minimum 3 weeks after the start date and at most 2500 weeks after the start date. Which would mean the maximum is around 4.8 years after the start date. Now because we were doing it by week, this meant that an employees Termination Date was always the same day of week as their start date, which for everyone who isn't an office location founder would be a Monday currently. To fix this we added another RANDBETWEEN with a range of 0-4. This just changed what day of that week the term would occur.



More posts to follow about other fields and how they were created and the reasoning behind some of the decisions!

"The Company" Basic Demographics

We wanted to add some background for "The Company". Here are some facts to keep in mind when looking at the data. More information will be added to this page as more is created.

About "The Company"

Founded: New York City in 2009

Company Type: Technology

Product: App called - Widgets

Offices:

• NYC, New York (HQ) since 5/4/2009
• Boulder, Colorado (Tech HQ) since 1/25/2010
• United Kingdom since 9/2/2013
• San Jose, California since 2/13/2014
• Japan since 10/12/2015
• Oslo, Norway since 2/24/2015 (acquired company called "Gizmos")
• Hong Kong since 12/1/2016

Senior Leaders:

• Patrice Moore - CEO
• Justin Edgin - CTO

Basic Company Employee Demographics (In Progress):

• Tableau

"The Company" - The Why and The What

Image source

As we stated previously, one of the things we wanted to work on with Koluit is something called "The Company". In short, it is fake company (and company data) that we will be using for learning People Operations and Analytics ideas here at Koluit.

You can find the most up to date version of the data here.

Why did did you create your own data and not use one of the employee data resources that are out there (Like IBM's or MySQL's)?
Well none of the data resources really touched everything we wanted to work on. They all seemed to be missing something. While we could have just built on top oh what they already had, we liked the idea of building this data ourselves and expanding it for different projects over time.

Why do you need dummy company data?

• For testing/sandboxing new tools and systems - When we want to try out a new tool like an ATS, HRIS, Tableau, Alteryx and etc. we usually can't just dump in our real data. Having a realistic dataset with varying fields allows you to get a better understanding of how these tools would work "in the real world".
• Getting Help in Public Communities/Forums - Sometimes when we are using a tool, we come across issues that we can not solve on our own. Lots of sites have great community pages where you can ask other users for help. The only issue is most of the work we do in People OPs/Analytics is dealing with highly confidential information which we (for obviously reasons) can't share on a public forum. This means we need to spend the time creating a few fake data points and make it robust enough where you can properly show the issues you are facing. Having data like this ready allows you to easily replace your real data (or use this information while you are building/testing) and show a realistic environment for the issues you are facing. 
• Sharing People Analytics Tools and Best Practices - This blog is a perfect example of this. Sometimes you just want to share your work or your ideas, but your hands are tied because your visuals, analytics or ideas are tied to real people data. This data allows you to share your people data ideas in an open source environment.

What else will you be adding to this database?

Our goal is to add a few more fields and clean up the standard demographic data you would find in an HR database. Once that is completed we will try and create some engagement, performance, and learning data in connection with these employees. In the long term future we would like to do quarterly or bi-annual releases that contain changes like hires, terms, transfers, promotions, and the like. This would then allow us to keep historical data in the database. We will be tracking ideas and issues we find on this Trello page. Have some ideas or suggestions? Please email us at contact@koluit.com. 

Purpose

"Rick and Morty" Adultswim S1Ep9

The purpose of this site is to work on topics related to People Analytics/Operations from varying angles. These posts will all be labeled based on their focus. Here is an explanation of the different labels.

1. "The Company" - We are in the process of creating a fictional company and a fictional dataset (found here).  We will use the data to go through real world examples of reporting and People analytics. The first few posts in this topic will go over how we created the data for "The Company" and the reasoning behind the decisions we made.
   
   As we progress, we will be treating "The Company" as if it was a real company and go through examples you might face as a People Analyst at this company.
   
   We will also be releasing HR policies as the "The Company". This will be done for two purposes: First, to discuss and research current hot button topics like workplace flexibility, unlimited PTO, diversity/inclusion initiatives and so on. Second, this gives us new situations where the employee database can be used and see how these new programs and inititives impact the company.


2. Toolkit - This is where we will go over some tools and skills we have used when doing work in the "real world". This will hopefully be a great way to learn new skills.


3. Articles - We will use this to give our take on articles and current topics that are going on related to business, people operations, HR, and people analytics. This might be similar in some ways to the policies that are written for "The Company" but this will be more focused on the actual topics that are being discussed and not how they are impacting our fictional business.


4. Reviews - We would love to review some of the vendors and tools that are out there for People Ops/Analytics, especially as "The Company" dataset becomes more robust. We are not sure how much of this will actually be done, but if you have something you would like to be reviewed please email us at contact@koluit.com.