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SMPLCTY Analytics

Case 08

Using Predictive People Analytics to Improve High-Value Talent Decisions

Governed workforce evidence and predictive analysis applied to retention decisions for high-value talent, with privacy controls agreed up front.

Client
An enterprise employer
Industry
Other
Decision domain
Workforce retention and capability planning
Capabilities
Advanced Analytics & AI · Data · Decision Intelligence

Measured outcomes

What changed.

This result is reported as an associated outcome observed over a six-month period. Employee turnover is influenced by many factors beyond this engagement, and no causal claim is made.

10%

Reduction in employee turnover over six months

An outcome associated with the period following adoption. Turnover is influenced by many factors, and this analysis does not establish that the work caused the change.

Associated outcome — causality not established.

The situation

Where the work started.

An enterprise employer was losing high-value talent in roles that were slow and expensive to refill.

Workforce evidence existed but was fragmented, and analysis arrived after departures rather than before.

Decision at stakeWhere to direct retention and capability investment, and for which groups.

What prevented the decision

The constraints that had to be removed.

  • Workforce data spread across HR, org and performance systems without consistent effective dating.
  • No agreed privacy and permitted-use position for workforce analysis.
  • Retention discussions relied on anecdote rather than pattern.

What SMPLCTY delivered

The system we built.

Governance and privacy position
Aggregation thresholds, access rules and permitted use agreed with HR and legal before analysis began.
Governed workforce data model
Core HR, org and performance data integrated with consistent definitions and effective dating.
Predictive retention analysis
Group-level patterns identifying where retention risk concentrates, with explicit limits on interpretation.

Implementation

  1. 01Set the governance and privacy constraints first, and designed the analysis within them.
  2. 02Built the workforce data model and validated it with HR.
  3. 03Delivered findings into workforce planning rhythms with guidance on appropriate use.

Applied here

Services and solutions behind this work.

Services

Advanced Analytics & AIForecasting, optimization, predictive models, and applied AI deployed where they measurably shorten the distance to a decision.Data Foundations & GovernanceThe pipelines, models, definitions and governance required by the decisions you have prioritized — scoped to purpose, not to completeness.

Solutions

People Decision IntelligenceWorkforce evidence applied to capacity, capability and retention decisions — governed, privacy-respecting and tied to business outcomes.

Related work

Comparable decisions.

Case 06Building an Integrated Measurement System Across Marketing, Customer Adoption, Cost, and RevenueMarketing activity, customer adoption, cost and revenue measured in one governed system, so contribution is assessed on a consistent basis.Case 07How a Homeless Services Organization Cut Reporting Time by 50%Funder and program reporting rebuilt on a governed data foundation, halving reporting time and returning capacity to service delivery.

Have a decision like this one?

We will frame the decision, map the evidence it needs, and set out what it would take to build the system behind it.

Discuss a DecisionSee Client Work