Can industrial policy work like a service-customized to a specific sector, its development stage, and expected outcomes? In China, the answer is yes. There, the state acts less like a central planner and more like a system architect and service operator. Industrial policy isn’t a one-size-fits-all formula; it’s a flexible system where tools, timelines, stakeholders, and KPIs are chosen based on context.
This model delivers high returns because each action is tied to a goal and a measurable result. It’s not about distributing budgets-it’s about investing for impact. That’s what makes China’s approach adaptable and effective for other countries, including Kazakhstan.
China doesn’t use universal solutions. Instead it applies a policy configurator, where every measure is selected based on:
• Industry development stage (emerging, growth, maturity, decline);
• Type of company (large firm, SME, startup);
• Regional conditions (infrastructure, talent base);
• Strategic goal (import substitution, exports, tech leadership).
Tools China uses:
• Financial:
◦ R&D subsidies;
◦ Concessional or risk-based lending;
◦ Guarantee funds for SMEs;
◦ Grants for prototyping;
◦ Insurance for tech risks.
• Regulatory:
◦ Fast-track product certification;
◦ Preferential access to public procurement;
◦ Export-compliant standards.
• Institutional:
◦ Tech parks and incubators;
◦ Regional venture funds;
◦ Export accelerators and trade fair platforms.
• Infrastructure:
◦ Industrial clusters with shared logistics;
◦ Science and education campuses in industrial zones.
Each tool comes with KPIs, and continued support depends on results.
Kazakhstan takeaway: Build a “policy toolbox” with flexible configuration and public KPI monitoring.
Instead of vague slogans like “promote innovation” or “digitalize the economy,” Chinese policy starts with problem diagnosis.
Example:
• Problem: Talent drain in AI sector;
• Tool: Joint university campuses + tax breaks for startups;
• KPI: More AI graduates hired; new AI firms registered.
Every intervention is tied to a specific metric, enabling real-time policy adjustment.
Kazakhstan application:
• Diagnose before launching state programs;
• Shift from “budget disbursement” to “problem–solution–impact” approach;
• Make support conditional on KPI achievement.
China breaks industries into stages, and each stage gets tailored tools and targets:
• Emerging:
◦ R&D grants, accelerators;
◦ KPI: patent count, private investment volume.
• Growth:
◦ Infrastructure, logistics, financing access;
◦ KPI: revenue growth rate, export value.
• Maturity:
◦ Export subsidies, compliance with international standards;
◦ KPI: global market share, labor productivity.
• Decline:
◦ Diversification support, retraining programs;
◦ KPI: share of new products, cost reduction, job retention.
Kazakhstan implication: Apply lifecycle logic-mining and biotech need different policies.
Tax incentives work for biotech but not for heavy industry. Why? Different growth drivers. Biotech thrives on venture funding and quick scale-ups, while metallurgy needs long-term orders and strong logistics.
China evaluates each sector’s sensitivity to incentives before acting.
Kazakhstan needs: Pre-test policy tools-will SMEs actually use a grant program before rolling it out?
Tools without audience fit don’t work. China differentiates support by company type:
• Large firms (infrastructure, standardization);
• Medium-sized enterprises (access to IT, applied science);
• Startups (venture funds, incubators);
• Newcomers (training, microgrants).
KPIs differ too:
• Large firms: export volume, standards compliance, R&D output;
• SMEs: productivity and revenue growth;
• Startups: 3-year survival rate, pilot projects with large clients.
Kazakhstan must: Segment support. One-size-fits-all programs lower efficiency.
In China any sector isn’t just factories-it’s a system:
• Workforce (education aligned with demand);
• Science (applied research);
• Infrastructure (logistics, clustering);
• Finance (banks, VC, subsidies);
• Demand (state orders, export platforms).
Example: Support for new materials included:
• Engineering education;
• Lab-equipped tech parks;
• Raw material preferences;
• Purchase agreements with large firms;
• KPI: export revenue growth, local sourcing in supply chains.
Kazakhstan action: Design sector-specific packages that combine multiple instruments.
Every policy tool in China is KPI-linked:
• R&D: patents filed, commercialization rate;
• Exports: revenue growth, new markets entered;
• Jobs: net job creation;
• Investment: private capital mobilized per yuan of support.
Even local officials are evaluated based on KPI outcomes.
Kazakhstan should:
• Make KPIs mandatory in all support programs;
• Build a digital KPI monitoring and reporting system;
• Shift from budget input to outcome-based performance.
China’s industrial policy isn’t bureaucracy-it’s a responsive growth system. Where others issue subsidies, China fine-tunes processes. Where others apply blanket measures, China tailors the solution.
Kazakhstan must move from form to substance: design support around actual problems, select tools like a pharmacist does medicine, tie every program to outcomes, and transform government from administrator to growth architect.
