Network HR — Rebuilding Triglav's Knowledge Network

A four-round, intermediate people-analytics and talent-strategy simulation set inside Triglav Systems d.o.o., a 540-person, €72M Ljubljana enterprise-software firm building industrial-IoT platforms whose entire competitive edge is the tacit knowledge held in its engineers' heads and the informal ties between them.

On 5 May 2026 a principal architect — Maja K., who the firm's first organizational network analysis (ONA) shows sat at the centre of knowledge flow — resigns, a flagship client implementation stalls, and €2.1M of contracted revenue goes at risk.

The ONA reveals the truth: the knowledge-transfer index has collapsed to 41/100 (cross-squad flow down 30% year-on-year), three connectors mediate ~45% of all cross-team knowledge ties (a single point of failure), network density across the six squads is just 0.06, and the two remaining top connectors both sit in the engagement survey's flight-risk band.

The CEO authorizes zero net new headcount: you must fix knowledge sharing by redeploying and connecting the people the firm already has, before two quarterly client milestones — or leadership forces a rigid functional reorganization that engineering leaders warn will make the silos permanent. Playing the Head of People & Network through Robert Kaše's social-network perspective on HRM, you work four rounds.

Round 1 — Diagnose: read the ONA against the org chart (they look nothing alike), identify the connectors by betweenness centrality, the highest-leverage structural holes between zero-tie squads, and the over-concentration risk.

Round 2 — Plan: design the intervention portfolio under a fixed development budget across three levers — connector investment (de-load the central few vs. the headcount-reflex external hire vs. the concentration trap of deepening dependence), bridging mechanism (relational rotations and communities of practice vs. the documentation fallacy of a wiki vs. conceding the reorg), and deploying line managers as knowledge enablers rather than inward supervisors.

Round 3 — Decide under the cap: commit scarce budget and manager capacity across knowledge-capture and succession (apprenticeship that moves tacit context vs. playbooks), targeted vs. flooded cross-squad rotations, redistributing brokering load onto multiple redundant paths vs. protecting or re-anointing heroes, and funding retention for the flight-risk connectors.

Round 4 — Recover: absorb two shocks — a second top connector signalling an exit and a new strategic client demanding rapid cross-squad mobilization — show the reshaped network holds without a single hero, then make the executive-committee case on the four KPIs and render the rigid reorg unnecessary.

The scoring rewards reading the network not the org chart, de-loading connectors while building the right bridges, transferring tacit knowledge through relationships, redundant multipath brokering, and funded connector retention — and measurably punishes the five classic errors: the headcount reflex, connector over-investment, bridge-everything overreach, the documentation fallacy, and ignoring connector retention.

Final KPIs track the knowledge-transfer index (/100), network density, connector concentration (%), network resilience, and how many of the two remaining connectors were secured.

An intermediate simulation for participants who already know the core concepts of the subject, designed for master's and MBA programmes.