Industry overview
What is shaping industrial robots & automation
Industrial automation and robotics are moving from large plants to mid-sized manufacturers. Adoption depends on clear payback, integrator support and confidence in the technology.
- Plant heads need a clear business case before investing
- System integrators are central to successful adoption
- Skills gaps slow down deployment
Client background
A state skills mission, working in Tamil Nadu. Client identity is withheld to protect confidentiality.
- Organisation
- A state skills mission
- Sector
- Industrial robots & automation
- Team engaged
- Market Research
- Services
- Government research, Quantitative research, Qualitative research
Client challenge
The mission had set up a training centre for automation skills and wanted to know whether graduates found relevant jobs. The centre had been running for three years with significant public investment, but placement figures came only from self-reported data.
Research objectives
- Deliver on the brief: evaluating a robotics and automation training centre.
- Understand the views, needs and behaviour of trainees.
- Understand the views, needs and behaviour of employers.
- Measure how widespread each pattern is, and explain the reasons behind it.
- Give the client evidence it can act on within 8 weeks.
Target audience
The work focused on 600 trainees and 30 employers.
- trainees600
- employers30
Audiences we typically reach in industrial robots & automation
Plant heads and ownersProduction engineersSystem integratorsAutomation distributorsMaintenance teams
Geographic coverage
Coverage: Tamil Nadu. Market: India.
- India
Research methodology
A mixed-method design: structured research measured how widespread each pattern was, and qualitative conversations explained why.
- 1Brief
- 2Trainee tracer survey
- 3Employer interviews
- 4Insight
We traced graduates six to twelve months after training to record employment, roles and wages, and interviewed employers about graduates’ skills. Graduates were reached by phone and, where needed, through the centre’s alumni groups, and employers were asked to describe specific gaps they had seen in new hires.
Government researchQuantitative researchQualitative research
Sampling strategy
- trainees
- 600
- employers
- 30
- Business respondents were screened on role, company size and involvement in the decision before being invited.
- Qualitative participants were recruited purposively to cover the full range of experiences that mattered, rather than for statistical representation.
Data collection
- Interviews and discussions were led by experienced moderators using a guide agreed with the client.
Data quality & validation
- Recordings and transcripts for every session
- Re-screening of qualitative recruits
- Logic and range checks on the final data
- Work carried out under our ISO 20252 quality procedures
Data analysis
- Cross-tabulation by key groups and locations
- Significance testing on the differences that mattered
- Thematic coding of interviews and discussions
- Journey and decision mapping
Key findings
- Graduates with hands-on programming experience found jobs quickly, while others struggled.
- Industry partners also agreed to offer short internships, giving trainees experience on real production lines before graduation.
Practical experience was the strongest predictor of employment.
Recommendations
- Build on the core insight: practical experience was the strongest predictor of employment.
- Focus effort where the evidence was strongest: graduates with hands-on programming experience found jobs quickly, while others struggled.
- Re-measure after the changes to confirm the effect.
Business impact
- The centre expanded practical lab time and industry projects.
What changed in the business as a result of the work. Impact is described qualitatively.
Deliverables & next steps
- Insight report and management presentation
- Cleaned data file and data tables
- Interview summaries and key verbatims
- Evaluation findings with programme recommendations
- Repeat the measure after changes are in place to track progress.
- A natural follow-on question: how do buyers judge payback?
Client identity is withheld to protect confidentiality.