Performing Analysis

April 29, 2017

Introduction

Performing Analysis is where you'll leverage the data collected over time and perform a variety of innovative comparisons to gain insights at all levels of your organization. The type of analyses you can conduct is only limited by the amount of data available to you and the way it is structured, so this is where your data collection efforts pays off!

The main benefit of comparing various sets of data across time and organizational structure is that you can gain uncommon insights and identify concrete improvements that help inform your agile enterprise transformation strategy. By collecting data, visualizing the challenges and acting on the information, your organization will be on its way to become a high-performing, continuous improvement enterprise.

Prerequisites

Before you can perform any of the tasks below, you need to open a Comparative Agility account and have created at least one Collector containing team member submissions. In addition, to perform more advanced analyses involving organization-wide comparisons and identifying differences based on a time dimension, you need to create multiple collectors containing submissions from team members at various points in time.

Case 1 — Perform Team Analysis vs CA Word Index
Case 2 — Compare Aggregate Data vs CA World Index
Case 3 — Compare a Team over different points in time
Case 4 — Comparing parts of the organization based on Geographic Location

Case 1 — Perform Team Analysis vs CA Word Index

The simplest form of analysis one can do in Comparative Agility is to compare a single team to the CA World Index. This is a quick way to identify how a given team is doing compared to the world’s largest agility benchmark and a great way to get started on your continuous improvement journey.

step 1 In this example, we will use a single Collector - representing one team with multiple member responses - and compare this to the CA World Index Collector to the right. Defining the data set that forms the basis of the analysis is easy:

1.Select the dataset that you want compared (baseline data set) on the left-hand side of the screen
2. Select the dataset that you want the baseline compared to (target data set – in this case the CA World Index Collector) on the right-hand side of the screen
3. Name the report and click on "Generate Report". The report will open after a few seconds of processing.

Note: Comparative Agility allows you to compare a variety of baseline data sets to target data sets. The differences are displayed in the report – together with the raw averages of the baseline data set.


Case 2 — Compare Aggregate Data vs CA World Index

The first example was great to get us started, but most companies contain multiple teams that represents the organization. With Comparative Agility, it is easy to get a quick perspective of how your part of the organization is doing compared to the CA World Index.

In this example, you'll notice we will work with a few more Collectors. The R&D Department contains 7 collectors, each representing an individual team that belongs to the R&D organization. Earlier, we got a view of how one of these teams were doing compared to the CA World Index; now we're going to expand our analysis to encompass the entire R&D Department. step 2

Defining the aggregated dataset is similar to the previous example:
1. Select the R&D Department parent on the left-hand side to indicate your baseline data set. (Notice how the 7 children are automatically selected, as well.)
2. Select the dataset that you want the baseline compared to (target data set – in this case the CA World Index Collector) on the right-hand side of the screen
3. Name the report and click "Generate Report". The report will open after a few seconds of processing.

Note: This report will aggregate all the data from the teams within the R&D parent and compare this to the CA World Index. If there are specific teams that you do not want to be part of the analysis (perhaps they are brand new or otherwise not relevant for your report), you can simply uncheck the respective collector before running the report.


Case 3 — Compare a Team over different points in time

Being able to compare various levels of organizational data against an industry benchmark can help us gain some insights, but to embrace a continuous improvement mindset it is important to examine how teams, programs and the organization itself is doing at various points in time. Having this information reveals whether your efforts are having an effect and is a key component of an enterprise wide continuous improvement strategy.

You’ll notice in this example that we have multiple Collectors with the same team name, yet with different dates indicated at the end of the name. step 3 This means that we have gathered data from this team at various points in time, which allows me to do some interesting comparative analyses. Let's give it a try:

1. Select the Collector on the left-hand side that represent the most recent time you collected data. In this case, we'll select "Infrastructure Team – January 2017"; this is now by baseline dataset.
2. Select the Collector that you want to compare this dataset to. In this case, we'll select "Infrastructure Team – May". This is now the target dataset.
3. Name the report and click "Generate Report".

The report will open after a few seconds of processing and will display the differences in how the team perceives it is performing across 8 dimensions of agility from January 2017 to May 2017. The raw averages for May 2017 is also displayed.

Note: Although we only compared a single team at different times in this example, you can also aggregate teams (just as we did in the previous example) and perform a similar time analysis at various levels of the organization. If you wanted to find out how the R&D Organization had improved over the last six months, you'd combine lessons we just went through.
How you structure your collectors in Manage Collectors will help you; adding layers helps increase your analysis options. You can always aggregate up from the team level, regardless of how large or complex your organization is.


Case 4 — Comparing parts of the organization based on Geographic Location

In this example, we'll show how you can quickly compare various parts of your organization based on the geographic location of the teams. This can be an important insight to help identify whether there are unique needs and challenges to a given location you were not aware of.
You’ll notice that in this example, we have a R&D Department parent with additional sub-parents defined by the location which has each multiple children. Let's see what we can do:
step 4
1. I will select the New York parent Collector on the left-hand side of the screen to indicate my baseline dataset.
2. I select the Bengalore parent Collector on the right-hand side of the screen to indicate the target set.
3. I remember that the Team 4 has just been formed and should not be part of the analysis. I therefore unclick this Collector
4. I name the report and click "Generate Report".
The report will open after a few seconds of processing and will display the differences between how the respective teams in New York perceive they are doing compared to the teams in Bengalore.
Note: We now gained some insight into how New York was doing vis-à-vis Bengalore. What if we want to get Sydney’s perspective? We can run a new report that compared Sydney to either Bengalore or New York, or we could aggregate two of the locations. The only limit to the number of analyses you can run is the amount of data available and your imagination.