Recently, an article from global management consulting firm McKinsey & Company, “Improving the semiconductor industry through advanced analytics,” highlighted the benefits and adoption level of advanced analytics in the semiconductor industry – a subject we and our customers are intimately familiar with. McKinsey observes that the adoption level is low for the industry considering its clear benefits, and cites numerous functional area examples to show what’s being left on the table when semiconductor manufacturers don’t employ advanced analytics. We recommend reading the article (link follows below), but we thought it worthwhile to explore some major aspects of the article that we consider important based on our customers’ experience.
The analytics evolution
The unprecedented capacity to source and parse large amounts of data has resulted in an explosion of analytics methodologies. However, data analysis without a clear end goal or specific purpose can easily fall into the category of “interesting” observations, and have no viable impact on an enterprise. According to the aforementioned McKinsey report, the semiconductor industry is not realizing the benefits of what they term “advanced analytics.”
The addition of the term “advanced” preceding “analytics” is more transformative than the term implies; it isn’t simply a higher level of analytics. Based on a comparison of Gartner’s IT Glossary’s definitions of the terms – “analytics” and “advanced analytics,” a notable difference emerges between the two approaches. Advanced analytics “typically beyond those of traditional business intelligence (BI)… discover deeper insights, make predictions, or generate recommendations.”
Advanced analytics combined with big data aggregation capabilities brings decision-making to the realm of real-time and into the future – not just an assessment of the past, but a continuum of past, present and future toward specific business improvement goals.
Gleaning information from data abundance
Semiconductor manufacturers have a successful history of using systems to gather critical data during production, test and post-production. This abundance of in-line, post-line and metrology data analysis has proven to be useful for decision-making, but despite its accuracy, relevance and volume, it may not be enough. Again, according to McKinsey’s report, few companies “combine and apply advanced analytics to all these production data, even though that could improve many important manufacturing dimensions, including yield, throughput, equipment availability, and operating costs.”
We are happy to know that the “few” companies mentioned by McKinsey that are taking analytics to this next level are Optimal+ customers. Our customers, having analyzed hundreds of terabytes of data and collectively analyzed over 35 billion devices in 2015 alone, are identifying actionable insights daily and using automation to continuously improve operations going forward. With this wealth of “manufacturing intelligence,” our customers now have real-time decision-making expertise, and looking ahead, they are planning for new levels of analytic sophistication that will impact productivity well beyond the production floor.
The volume of manufacturing data will only continue to grow, and the need for clean, validated data will remain paramount, but enterprises must also look at the advanced analytic tools that will provide the most impact for the organization, from the production floor to the executive suite. The McKinsey Report does a good job of highlighting the benefits of advanced analytics in various functional areas including sales, IT, and manufacturing. Here is the link