Improving Semiconductor Research And Development With Analytics

Before analytics was developed, research and development projects were sometimes driven by instinct and guesswork, which, save for some fortunate breakthroughs, proved inefficient in the long run.

integrated microchip

Image source: bryantarchway.com

According to a study by McKinsey & Company, four in five companies in the semiconductor industry need data-driven analytics to speed up their R&D projects and maximize the scarce resources they have because they cannot meet their initial schedules. While semiconductor firms are considered frontrunners in the generation and analysis of data, most companies have not integrated them into R&D projects.

However, there is optimism that advanced analytics will make its way to this department because of the emergence of better computing power and storage infrastructure. The technology and techniques needed to extract, manage, analyze, and display data are continuously being enhanced.

Data analysis methods have also shown improvements. Traditionally, one would gather all the available data and generate inferences from such. After which, insights can be generated to inform decisions.

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Image source: techjini.com

Advanced analytics, however, reverses these processes. It begins by determining the problems and the key decisions that must be made. From here, insights are then identified to clarify those decisions, as well as the information required to produce the said insights. Only after then are the data sources mined.

Capital Asset Exchange and Trading (CAE), headed by its CEO Ryan Jacob, is a semiconductor-focused trading and investment company that uses a unique approach to analytics, asset and buyer due diligence, and rigorous process management to efficiently execute transactions. Learn more about the industry by subscribing to this blog.

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