Thinklytics

Semiconductor Analytics Consulting

Semiconductor and fabless chip analytics. We unify wafer yield, supply chain, customer, and revenue data into one trusted operating picture for leadership.

Topics

  • semiconductor data analytics consulting
  • yield analytics
  • semiconductor BI consulting
  • fab operations analytics
  • supply chain analytics semiconductor
  • process excursion analytics

What clients in this industry usually arrive with

  • Reporting cannot be trusted, described as sales and finance numbers do not match or inconsistent KPI reporting. Resolved by Metric governance, data cleaning, master data management, data engineering.
  • Reporting takes too much work, described as automate monthly reporting or combine reports from multiple systems. Resolved by Executive reporting, integrations, ERP consolidation.
  • Employees waste time finding information, described as search internal company documents or find policies and procedures quickly. Resolved by Knowledge assistant, RAG, unstructured data platform.
  • Systems require manual handoffs, described as eliminate manual data entry between systems or automate approval workflows. Resolved by API integration, workflow automation, human review design.
  • AI projects are not delivering value, described as measure AI ROI or AI pilot not moving to production. Resolved by Strategy, readiness assessment, AI PMO, adoption.
  • AI is too risky to deploy, described as AI confidential data protection or control AI agent permissions. Resolved by Governance, AI security, agent identity, evaluation.

Other industries

Start with the 30-day Analytics Truth Audit.

Semiconductor analytics built for yield and margin.

Why semiconductor analytics projects fail.

What semiconductor clients ask before they engage.

Often paired with semiconductor engagements.

Yield data should pinpoint the problem before it compounds.

No unified view of inventory, lead times, and supplier risk across procurement systems

Process, equipment, and material data live in separate systems with no unified query layer

Yes. We build data pipelines from MES, process control, and equipment data systems into a unified analytics layer. We normalize data across tool types and process steps so you can correlate defects and excursions across the full process flow.

Yes. We build unified dashboards that connect foundry yield data, delivery performance, and cost data so fabless companies can manage TSMC, Samsung, and other foundry relationships with a single view of performance.

How do you handle the volume of process data in a fab environment?

We design data architectures that handle high-volume time-series process data efficiently. This includes data compression, aggregation strategies, and query optimization so your analytics layer performs at the speed your operations team needs.

Most semiconductor data foundation engagements run 12 to 16 weeks given the complexity of process data integration. We start with a 30-day Analytics Truth Audit that maps your current data landscape and prioritizes the highest-impact improvements.

Data analytics consulting for semiconductor manufacturers. Unify process, yield, and supply chain data to reduce excursion response time and improve margins.

Data analytics for semiconductor companies. Yield, supply chain, and operational metrics.

Semiconductor manufacturers and fabless chip companies operate in one of the most data-intensive environments in any industry. Process data is fragmented across 500 or more steps with no unified defect correlation view. Equipment failures are discovered after the fact. Supply chain shortages are identified too late. We unify operational, process, and business data so your team can isolate excursions in hours, not days.

We pull together process, yield, and supply chain data into one spot.

We create dashboards that let you see how your yields and operations are doing, right now. No extra noise, just simple data you can use to make fast calls.

We create models that catch issues early and help crank up production yields.

The 30-day Analytics Truth Audit maps your current process data landscape and identifies the highest-impact improvements for yield and operations analytics.