Published: 23 November 2022
High-quality, trusted data is critical for successful, talent-related business decisions. If HR analytics leaders are to enable a data-driven organization, they must take pragmatic and targeted actions to improve their talent data quality.
Data quality (DQ) programs are often not aligned with the organization’s strategic objectives. These misaligned programs fail to help business stakeholders outside of talent analytics use talent data, resulting in opportunity cost.
HR analytics leaders find it difficult to collaborate with the business on DQ initiatives, because business stakeholders may have different priorities, DQ adoption capabilities and alignment on end objectives.
DQ initiatives are often reactive in nature and, hence, not embedded as part of a data-driven talent culture.
To create DQ programs that execute effectively against talent analytics strategies, HR analytics leaders should:
Identify and prioritize critical data assets affectingstated
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