---
id: "prereq-workforce-management-systems"
type: "prereq"
source_timestamps: ["¶3"]
tags: ["infrastructure", "data-collection"]
related: ["action-mine-workforce-data", "prereq-advanced-analytical-capability"]
reason: "Without granular, historical shift-level data, it is impossible to run the analytics required to identify local turnover drivers."
sources: ["tail1"]
sourceVaultSlug: "hbr-seg-tail1"
originDay: 1
articleStem: "hbr-tail-111-service-worker-churn"
sourceUrl: "https://hbr.org/2026/03/the-solution-to-service-worker-churn"
sourceTitle: "The Solution to Service-Worker Churn"
---
# Data-Rich Workforce Management Systems

The localized scheduling approach requires the organization to already have systems that capture **granular, shift-level records**: timestamps of shift starts/ends, break times, task completions, shift patterns, manager approvals, and absences.

The authors note that **nearly every retailer already has this raw data** — they simply use it only for payroll or compliance rather than for retention analytics. Unlocking it is the raw material for [[action-mine-workforce-data]].

**Why it's required:** Without granular, historical shift-level data, it is impossible to run the analytics ([[concept-lasso-regression-workforce|LASSO]]) required to identify local turnover drivers. Pairs with [[prereq-advanced-analytical-capability]].

**Enrichment / counter-perspective:** Small retailers or sectors lacking robust workforce-management systems may not have enough signal for LASSO-style modeling; in low-data environments, qualitative methods, surveys, and participatory design can be more practical.