Maker Mentorship Matching Flow

Overview

FlowLibs - Maker Mentorship Matching is a monthly scheduled Power Automate Cloud Flow that automatically pairs new Power Platform makers with experienced mentors in the same or adjacent departments. It queries a Dataverse maker inventory table, identifies new makers (active less than a configurable threshold), matches them with experienced makers (based on a minimum published app count), logs pairings to a Dataverse mentorship table, and posts introductions to a Teams channel.

Use Case

Center of Excellence (COE) teams want to accelerate new maker onboarding by connecting them with experienced mentors who understand their business domain. This flow automates the matching process monthly, eliminating manual pairing and ensuring no new maker is left without guidance. The department-aware matching ensures mentors can provide contextually relevant advice.

Flow Architecture

Environment Variables

Connectors & Connections

Note — All connections are referenced as solution connection references; the flow is portable between environments as long as a connection is mapped at import time.

Customization Guide

Almost every realistic variant of this flow can be implemented by changing environment variable values. A few cases require small edits inside the flow definition — those are called out explicitly below.

Configure Environment Variables

Update all 6 env var values for your tenant: set the Teams Group/Channel IDs, point to your maker inventory Dataverse table, create a mentorship pairing log table, and adjust the threshold-days and minimum-apps thresholds to match your COE policy.

Authorize Connections

Open the flow in the designer and authorize the three connections (Dataverse, Office 365 Users, Teams) with an account that has read access to the maker inventory and write access to the log table.

Adjust Matching Logic

The department filter in Filter_Experienced_By_Department matches by exact department or falls back to 'IT.' Modify this expression to add additional fallback departments or cross-functional matching rules.

Customize Pairing Log Schema

The Log_Pairing_To_Dataverse action writes flowlibs_name, flowlibs_newmakerupn, flowlibs_mentorupn, flowlibs_department, and flowlibs_pairingdate. Ensure your target table has these columns or adjust the field mapping accordingly.

Turn On

Once connections are authorized and env vars are set, toggle the flow to On. It will run on the 1st of each month at 9:00 AM UTC.

Key Expressions

The flow is intentionally light on Power Fx / WDL gymnastics — the heaviest expressions are the branch-name concatenation and the approval outcome check. They are listed below in the order they appear in the flow.

addDays(utcNow(), mul(variables('varThresholdDays'), -1), 'yyyy-MM-ddTHH:mm:ssZ')

concat('createdon ge ', outputs('Compute_New_Maker_Cutoff_Date'))

concat('flowlibs_publishedappcount ge ', variables('varMinApps'))

or(equals(item()?['flowlibs_department'], outputs('Get_New_Maker_Profile')?['body/department']), equals(item()?['flowlibs_department'], 'IT'))

first(body('Filter_Experienced_By_Department'))

formatDateTime(utcNow(), 'MMMM dd, yyyy')