Without semiconductors, we won’t be enjoying most of the advancements and luxuries of modern technology, from flat-screen monitors and smartphones to fast-paced PCs and various IoT devices. However, with the rise of semiconductor revenues come increased R&D budgets. Businesses are constantly challenged by the pace of modernization.
But new productivity tools are helping address the elephant in the room. A huge aspect of all efforts to decrease the costs of IT modernization while boosting productivity is the development of data analytics. Semiconductor companies are keen on applying advanced data analytics for improved management of engineering.
Image source: benzinga.com
Such a move will both improve decision-making while offering novel insights for engineering groups. Advanced analytics is based on both machine learning and pattern recognition, helping uncover, say, any counterintuitive management insight. Their use is likewise seen to deliver productivity gains of over 20 percent.
Semiconductor managers can study via advanced analytics how often-overlooked staffing parameters like collaboration history, team size, geographical footprint, and individual performance affect the company’s engineering department. This will in turn lead to a new competitive edge and improve employee satisfaction. For example, studies have shown that a bigger number of engineers in a given semiconductor project will not necessarily lead to the best results, so a semiconductor company would significantly cut cost while not overstaffing.
Image source: rix-us.com