This package is the complete design of ReEngage, an engagement survey whose resistance to response bias is guaranteed by the measurement structure itself. The design philosophy and integration architecture are open for evaluation; the sealed portion contains the BL-method logic specification, the scoring specification, the question template collection, the AI-powered question customization guide, a minimal API implementation (Python), and an output sample.
The official name is ReEngage.
ReEngage means "to engage again" or "to reconnect." This name symbolizes the core concept of this design philosophy: structurally reconnecting the relationships between organizations, individuals, and management.
Engagement surveys are widely used as a foundation for understanding organizational conditions and driving improvement initiatives.
However, the following structural issues exist in actual operation:
As a result, the data obtained often does not accurately reflect the actual state of the organization.
The fundamental cause lies in the following:
The response structure is inherently vulnerable to psychological and organizational bias
In conventional survey formats:
Consequently, what is measured is not reality but the outcome of interest-balancing behavior.
ReEngage does not rely on ethical norms or respondent goodwill.
Instead, it is designed based on the following principle:
Data integrity is ensured by the measurement structure itself
Psychological factors are assumed to exist, and their impact is minimized through structural mechanisms.
The causal relationship between responses and evaluation outcomes is made impossible to infer.
Rather than a single scale, multiple behavioral axes are measured simultaneously to extract actual conditions.
Individual response biases are assumed, and their impact is diluted through aggregation.
The measurement structure itself — not UI or presentation — is the core of value.
ReEngage is built on the following design principles:
The uniqueness of ReEngage lies in:
This philosophy enables the following:
ReEngage targets the following:
This philosophy does not directly address:
The standard system architecture for integrating the ReEngage scoring logic engine into existing HR infrastructure.
flowchart LR
A[Respondent] --> B[Existing HR Tool]
B --> C[Internal Infrastructure / Data Integration]
C --> D[ReEngage Scoring Logic Engine]
D --> E[Score Output JSON]
E --> F[Dashboard / BI]
E --> G[HR & Field Reports]
The data integration sequence between existing HR tools and the ReEngage engine.
sequenceDiagram
participant HR as HR Tool
participant GW as Integration Gateway
participant RE as ReEngage Engine
participant DB as Data Store
participant BI as Dashboard
HR->>GW: Send response data (question_id, choice_id)
GW->>RE: Scoring request (with context_level)
RE->>DB: Save score results
RE-->>GW: Return per-axis / integrated / insights
GW-->>HR: Relay results
DB->>BI: Provide visualization data
The processing flow from response data input to score output.
flowchart TD
I1[Question Definition Data]
I2[Mapping Definition Data]
I3[Response Data - answers]
P1[choice_id → Axis Contribution Conversion]
P2[Per-Axis Score Calculation]
P3[Integrated Score Calculation]
P4[Normalization]
P5[Insight Generation]
O1[JSON Output]
O2[Formatted Report]
I1 --> P1
I2 --> P1
I3 --> P1
P1 --> P2 --> P3 --> P4 --> P5
P5 --> O1
P5 --> O2
A deployment configuration example including integration with HRIS, survey tools, and identity providers.
flowchart LR
subgraph Existing[Existing Environment]
H1[HRIS]
H2[Survey Tool]
H3[Identity / SSO]
end
subgraph ReEngage[ReEngage Scoring Logic Engine]
R1[Question API]
R2[Score API]
R3[Scoring Core]
end
subgraph Analytics[Analytics Platform]
A1[Data Warehouse]
A2[Dashboard]
end
H2 --> R1
H2 --> R2
H1 --> R2
H3 --> R1
R2 --> A1
A1 --> A2