Workspace ONE Intelligence for Human Resources – Part 2

By Roy McCord, Staff Architect, and Andrew McCarter, EUC Consultant

In our first post, we covered how to use Workspace One Intelligence to address these questions:

• What is our device base for the service?
• Have the users downloaded the service?

In this post, we’ll cover other common questions that Human Resources professionals may encounter when using Workspace ONE Intelligence.

Question 3:  How often are users using the service, and what platforms are the users coming from?

These high-fidelity questions can be answered in one beautiful chart. Let’s create the widget then breakdown exactly what is being shown.

1. Go to the Workspace ONE Access > App Launch Widgets.
2. Select App Launches.
3. Change the “Equals” to “Includes.” You can then reference all the applications listed inside Workspace ONE Access that use your service.
   • Here we are making sure we are selecting not only our native app deployments (iOS, Android, etc…) but the Web App that can be associated with the native deployment.
4. Add a filter for Event Time > After> Service Enablement Date.
5. Within Data Visualization we have a few options…
   • For the measure portion, we can select “count” or “distinct count.”
     1. “Distinct Count” tallies a user once regardless of how many times they log in.
        • To enable this, switch “Count” to “Distinct Count” and “Event ID” to “User ID.”
     2. “Count” measures an app launch (event id) as a measurable activity. This means that if a user launches the app 100 times that day, it will be counted 100 times on the chart.

• For our example, we are more concerned with the number of unique users accessing our service. Therefore, let’s enable the system for “Distinct Count.”

• The “Group By” field has a general mode and a distinct mode.
  1. By selecting Device Identifier, you will see verbose information about the device launching the application. This includes User Agent (Platform; OS; Model Number).
  2. By selecting Device Type – This tells you broadly where the request is coming from (Browser, Android, iOS).

• For our example, we will utilize Device Identifier.

• Date Range
  1. In our scenario, select “Last 30 Days.”
• Results per group
  1. Extend this to a number that is higher than your total device count so it can show all types of launches.

We now have the following added to our dashboard.  To further help illustrate, I created the same dashboard twice; the left shows the total count of launches regardless of user (count example), and the right displays launches unique per individual.

What does this help us answer?

“How often are our users using this service?”

Our Example: Since the launch of our service, the average launches of the service per day of 2.8. This is unique per user.

“What was our most active day since launch?”

Our Example: When specifically looking at unique individuals, our best day so far was eight total app launches. If you count total launches, we had 13.

“What devices are the users coming from?”

Our Example: All users are coming through a Firefox Browser.

Question 4:  Where are the users consuming the service from (on-site v. WFH)?

This widget is relatively straightforward. We will be using the same category as our previous example.

1. Emulate the start of the previous example by utilizing the same widget category and the following two filters:
   • App Name
   • Event Time
2. To provide insight on a network range the request is originating from, select another filter with “Source IP Address.”
   • Determine what your internal network range is, and identify it with the “Starts With” field. Using the octets in the range, specify the “starts with” as the second section of the filter.
3. Data Visualization has the same ‘Count’ conundrum as the previous example. Choose what best fits your need.
   • Our example will be using “Count” of “Event IDs,” as we want to see the number of launches regardless of user within our internal network “202.*.*.*”.
4. Make sure to label it for ease of understanding.

Having both the widgets aligned vertically gives us great insight to answer some great questions from management.

“What is the trend of our user base for accessing our service”

Our Example: Over the total 17 requests since we released the service, only two requests have been internal, indicating majority access the service when WFH.

Question 5:  How often are users failing to authenticate into the service?

The filter will be almost identical to the previous two. However, this example produces a filter that can be adjusted to show successful vs. unsuccessful logins.

1. Copy the Total App Launches Across Platforms Widget.
2. In Data Visualization change “Device Identify” (or Device Type) to “Success Status.”
   • “Success Status” indicates what authentication requests were successful and which were not.
3. In our situation we do not have a single failure.

This widget is independent as the information needed to baseline exists within the graph. However, placing it within the other app launch widgets gives the dashboard a consistent look and feel.

Question 6:  Where does the application rank in usage compared to other apps on the list?

We are down to the final question for delivering a new service! It so happens that this one is rather easy as VMware has already created a canned widget for this purpose.

1. Go to the “App Launch” widget in Workspace One Access.
2. Select any of the middle three options that suit your use-case the best.
3. For this example, I placed both the “Top Apps Launched Last Week by Application Name” and “Top 5 Apps Launched by Unique Users” widgets on the dashboard to give different representations for potential management inquiries.

Enhancing our chart with these widgets it gives us the ability to answer some of the following questions:

“How does our service compare to others we have used in comparison to usage”

Our Example: Our top service launched 149 times in a single day. Our max is 9 in our short time of being deployed.

“How does our service usage compare on a day to day average of other services”

Our Example: On our best day (12/23) we accounted for ~1/6 of the auth requests from users. We handled nine requests to our services over the total of 60 handled authentication requests.

Conclusion

Our new adoption dashboard now provides some very powerful metrics surrounding consumption of your new corporate service.

There are quite a few other considerations that may be covered in future blog entries, such as:

1. Long term maintenance
2. Monitoring HR-owned devices
3. How to augment reports on service adoption through Apteligent

These are more foundational questions that you can use to build upon for your own unique situation. Delivering on these and other questions using WS1 Intelligence will help you better communicate up the chain effectively.

About the Authors

Andrew McCarter is an EUC Consultant and has been with VMware for the last three years. At work his passion lies modernizing customers, expanding technologies outside IT departments. Outside of work, Andrew is actively pursuing a master’s at Johns Hopkins.  With his limited free time, he explores areas around the USA living full time out of an RV.

Roy D. McCord is a Staff Architect with VMware’s Professional Services Engineering team.  He is responsible for architecting, building, and maintaining VMware’s End User Computing global portfolio of professional services offerings.  Roy has previously worked as a team leader within the Workspace ONE consulting team and helped to build the practice from the ground up.  He holds BS, MS, and MBA degrees from the Georgia Institute of Technology in Atlanta, GA.  Roy resides in Alpharetta, Georgia