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Version 6.30
Version 6.30
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On this page
  • Overview
  • Usage
  • Categories
  • Scores
  • Score Modification
  • Campaigns
  • Champion employee survey
  • Non-engaged employee survey
  • FAQ / Troubleshooting

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  1. Library packs
  2. Collaboration Optimization

Collaboration Optimization - Usage / Troubleshooting

Last updated 10 months ago

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Overview

The collaboration optimization library pack allows you to measure the actual usage and adoption of a chosen real-time collaboration tool, detect shadow collaboration, engage with users for further context, and identify resistance to change.

Usage

For full details on how to configure this pack with the customizations necessary to fit your organization’s requirements please refer to the .

Once this pack has been configured, minimal maintenance is required, however, there are a few changes to categories, scores and campaigns that might need to be made from time to time.

Categories

This pack contains 5 categories.

The categories are used to identify the real time collaboration tools monitored by this pack and once configured will need very little modification. Once set, the target collaboration tool should not be changed unless you have migrated to a new application and wish to track its adoption by your workforce. The other categories, however, may be modified whenever you wish to add or remove applications from the list of collaboration tools used in your organization. It could be that after having run the non-engaged employee campaign you become aware of a subset of employees using an application or resource that you were not aware of, and wish to track in the future.

Scores

There are two scores included in this pack; Collaboration Optimization and Collaboration Optimization Summary.

The collaboration optimization score measures the usage of the applications specified in the categories mentioned above and scores this usage into ranges. The collaboration optimization summary score references this first score and applies a filter to the scored ranges to define the personas used in this pack. The output of the summary score is binary, 0 or 10.

The main advantage of this approach is that threshold changes to personas can be made easily by modifying only the score files and this will take effect for all metrics and dashboards that reference them.

Score Modification

Once you have configured the pack and have started using it, if you find that you are picking up very few employees in one or many persona metrics then you may have to adjust the parameters of the scores to rectify this.

One method you could try is to start by changing the threshold in the summary score.

Summary score - Champion Employee NXQL:

(select (id #"score:Collaboration optimization/Target collaboration tool") (from user (with user_activity (where user (gt #"score:Collaboration optimization/Target collaboration tool" (real 9.0))) (compute number_of_users)(between now-7d now))))

To use the example from the Configuration guide, if this is changed from “9” to “8” and you see immediate results in the associated metrics and dashboards then you have two choices. If the new query is producing an acceptable number of champion employees then you can leave the change as it is. If, however, this small change has resulted in many more results then you should consider returning the value to “9” and making some changes to the Focus Time ranges in the main score instead.

Campaigns

There are two campaigns included with this pack, targeted at two different employee personas. The first is designed to be sent to the “champion employees” and effectively reward them by offering them some additional hardware that could improve their experience when using a collaboration program, such as a dedicated webcam, headset or a second monitor if they don’t already have one.

Champion employee survey

Champion employees can be of great use to you, as they can act as evangelists for the product, driving adoption amongst their colleagues. For this reason, you may choose to widen the score thresholds to show more product champions so that they be contacted for mentorship or testing purposes. In this case, you would then most likely want to filter this list of employees and only send the hardware offer campaign to the top 10% say, or to send the campaign in different waves to subsets of the list, by region or department for example.

Non-engaged employee survey

The second campaign is designed to be targeted at the non-engaged employees in order to ascertain why it is that they do not make full use of the target collaboration tool provided.

The campaign is set to be targeted manually. You might choose to change this to use an Investigation and send it to all non-engaged users.

FAQ / Troubleshooting

Q: My dashboards aren’t showing any Champion Employees, what have I done wrong?

A: There could be several reasons for this:

  • Are other scores/metrics working OK, have you enabled Focus Time for Windows and macOS devices?

  • Is the target collaboration tool (or domain?) spelled correctly in the category, do you have entries for both Windows and macOS?

Q: I am seeing large numbers of non-engaged employees in one office/region, how can I investigate further?

A: There are a number of ways to tackle this:

  • Check your filtering hierarchy, are these employees really in one place?

  • Check the Digital Experience for these users, there could be a general issue beyond the use of your collaboration tool.

  • If a whole office of employees are non-engaged this is unlikely to be due to hardware issues but as collaboration tools consume a certain amount of bandwidth when making video calls you should investigate potential bottlenecks in the network.

  • You could also try an Investigation to see what other applications this subset of employees are using. It is possible that they are using a collaboration tool that you are not aware of.

Your score thresholds could be too restrictive, see the score section above or the for more details.

Configuration guide
Configuration Guide