Data quality, misleading metrics, and surveillance concerns
FREE02 – People Professional Technologies
This CIPD Level 0 learning video, part of the FREE02 – People Professional Technologies unit, explores critical risks and limitations of people technology and analytics by examining data quality issues, misleading metrics, and surveillance concerns in HR systems. Designed to address assessment criteria AC 3.2, the video helps learners understand how poor data quality can distort decision-making, why metrics can be deceptive, and the ethical implications of monitoring employee behaviour in modern organisations. By watching this video, CIPD students will gain essential knowledge of the practical and compliance challenges associated with HR analytics, enabling them to evaluate technology implementations more critically and advocate for responsible people analytics practices in their organisations.
What this video covers
Covering Assessment Criterion 3.2 of FREE02 – People Professional Technologies, this video addresses three interrelated risks that arise when organisations deploy people technology and analytics: poor data quality, misleading metrics, and employee surveillance. The discussion centres on what the computing principle "garbage in, garbage out" means for HR systems, examining how inaccurate, incomplete, or duplicated records undermine workforce planning, pay reviews, skills gap analysis, and retention decisions. Data governance frameworks and the conditions that produce unreliable input data both feature as part of this treatment.
The video then turns to the problem of misleading metrics, using employee turnover rate as a concrete illustration of how a figure that appears favourable can obscure more troubling realities. It examines the tendency to measure what is easy to count rather than what is strategically meaningful, and looks at the risks of benchmarking against industry averages without accounting for an organisation's specific sector, location, workforce composition, or strategic context. The discussion positions critical interrogation of metrics — questioning what a figure actually measures and what influences it may not be capturing — as a necessary analytical habit rather than an optional refinement.
Surveillance concerns form the third strand of the video, with attention given to the range of monitoring capabilities now available through people technology, including the tracking of activities, communications, locations, and biometric data. The video examines the tension between legitimate organisational interests and employees' reasonable expectations of privacy, and considers the requirements that UK data protection law places on the collection and use of personal data. Proportionality, transparency, and the communication of monitoring purposes to workers are all addressed, alongside the workforce trust and wellbeing consequences of excessive or covert monitoring practices.
Assessment Criteria 3.2
Discuss risks and limitations of people technology and analytics.
Indicative Content
To include: poor data quality; misleading metrics; surveillance concerns; low adoption; accessibility barriers; bias in data/AI; over-automation; loss of human judgement; change fatigue; cyber/security risks.
What You'll Learn
Video covering: Data quality, misleading metrics, and surveillance concerns
About FREE02 – People Professional Technologies
To develop learners’ understanding of key technologies used in people practice, how to select and use them responsibly, and how they can improve people insights, efficiency and employee experience.
More FREE02 Videos
Essential People Metrics
AC 3.1 – Explain how people data and analytics can be used to support decision-making.
Introduction to People Data, Dashboards and KPIs
AC 3.1 – Explain how people data and analytics can be used to support decision-making.
Using Data for Decisions and Avoiding Common Pitfalls
AC 3.1 – Explain how people data and analytics can be used to support decision-making.
Adoption challenges, accessibility, and AI bias
AC 3.2 – Discuss risks and limitations of people technology and analytics.
Over-automation, human judgement, change fatigue, and security
AC 3.2 – Discuss risks and limitations of people technology and analytics.
Introduction to measuring success and adoption/usage metrics
AC 3.3 – Evaluate measures of success for people technology.
Operational measures including efficiency, errors, and compliance
AC 3.3 – Evaluate measures of success for people technology.
Strategic measures including insight quality, employee experience, and ROI
AC 3.3 – Evaluate measures of success for people technology.
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