Workforce Engagement Management

Hi Everyone,

We are looking for a straightforward, easy-to-implement reporting solution available via AppFoundry to capture detailed custom reports across Quality Management (QM) and Workforce Management (WFM) alongside standard contact center metrics.

Our main goals are:

• Out-of-the-box or easily configurable reports for WFM (adherence, shrinkage, forecast vs. actual) and QM (evaluations, scoring trends, supervisor performance).

• Embedded directly within Genesys Cloud CX so our operational leads don't have to switch platforms.

• Low engineering overhead for setup and maintenance.

I've been looking into Genesys A3S Historical, as well as AppFoundry Premium solutions like Brightmetrics and PureInsights.<sources-carousel-inline ng-version="0.0.0-PLACEHOLDER" _nghost-ng-c2273216988=""> </sources-carousel-inline>

For those who have implemented reporting apps for WFM and QM details:

1. Would you recommend A3S Historical or a third-party AppFoundry Premium app for deep QM/WFM reporting?<sources-carousel-inline ng-version="0.0.0-PLACEHOLDER" _nghost-ng-c2273216988=""> </sources-carousel-inline>

2. How seamless was the implementation process and initial data availability?

3. Are there any platform limits or custom API considerations we should keep in mind before going live?

Thanks in advance for your advice and insights!

#Reporting/Analytics

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Saurav Arya
Senior Implementation Engineer
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Hi Saurav,

I'm moving this post over to the WEM Community to reach the WEM SMEs and oth other customers and partners who could help.

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Tracy
Online Community Manager/Moderator
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Answering the QM half rather than the tool comparison, since I have not run A3S and Brightmetrics side by side and would rather not guess at it.

Two things worth settling before you shortlist.

WFM and QM are not the same reporting problem. Adherence, shrinkage and forecast versus actual come out of the WFM engine. Evaluation scores come out of QM. Vendors vary in which of those they actually expose, and listing copy tends to lead with queue and conversation metrics because that is where most demand sits. Ask each vendor at field level which WFM and QM objects they read, not which dashboards they ship.

On QM specifically. If your evaluation coverage sits at the usual one to three percent of interactions, then scoring trends and supervisor performance dashboards are measuring your evaluator population as much as your agent population. Calibration drift between two evaluators renders as an agent trend, and once it is on a leadership slide it gets treated as one. The tool will not tell you which it is looking at.

So before building the QM layer, pull evaluations per agent per month and evaluations per evaluator, and look at the spread. If the sample is thin, a reporting tool will render it beautifully and it still will not carry the decisions your ops leads want to make with it.

For disclosure, I work on conversation analytics at Yameo, which is why I have a view on the QM side. Your question is a reporting question and that is a different purchase, so nothing to sell you here.

How many evaluations per agent per month are you running today?

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Daniel
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I would consider two separate layers when assessing this requirement.

The first is data availability: extracting Genesys Cloud operational, QM and WFM data into a structure that can be used for custom reporting. The second is analysis: understanding why the reported results are changing and what action should follow.

Full disclosure: I'm involved with two AppFoundry solutions addressing these layers:

• Slidy Data Mart extracts near-real-time and historical Genesys Cloud data into AWS Athena and makes it available to the customer's own BI tools. Its WFM datasets include near-real-time adherence and time-off requests, together with historical adherence details, actual activities, adherence and conformance metrics, and exception information.
• COMPASS augments Genesys Cloud with AI-powered Quality Management, conversation intelligence and automation. It combines quantitative metrics with conversation content to explain trends, identify root causes, automate evaluations and reviews, detect coaching or compliance opportunities, and track resulting actions.

This distinction matters because making more tables available is only half of what many customers ultimately need. Traditional reporting is effective at showing what happened; it becomes much harder to explain why without analysing the content of the interactions themselves.

With COMPASS, users can also use the Lens AI analyst to ask questions directly across their Genesys data-for example, what is driving a scoring decline, which customer concerns are increasing, or which behaviours distinguish stronger outcomes, without requesting a new BI report for every question.

For requirements such as forecast-versus-actual or broader workforce planning, I would still validate the precise datasets and reporting expectations upfront rather than assume that one product covers every WFM use case.

More information:

• Slidy Data Mart on Genesys AppFoundry – https://appfoundry.genesys.com/filter/genesyscloud/listing/b45d4b87-db6e-4827-b330-7539d4a6cc18
• COMPASS on Genesys AppFoundry – https://appfoundry.genesys.com/filter/genesyscloud/listing/d6a63b9d-b032-40ee-93eb-924e2b248444

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Hichem Agrebi
[EmailAddress]
CC-Expertise Ltd
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