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Accelerating Digital Transformation in Industry: Cyient's Proven Approach
Accelerating Digital Transformation in Industry: Cyient's Proven Approach Cyient
Accelerating Digital Transformation in Industry: Cyient's Proven Approach
Kim Devlin-Allen Kim Devlin-Allen Written by Kim Devlin-Allen, Read the recent blogs posts , press releases and news written by Kim Devlin Allen
on 15 Nov 2019

It’s often said “data is the new oil.”  However, like oil, it often starts in a crude form. Processing and refining data into more valuable information for decision-making is the secret to getting the best return on your digital transformation investment.

Why is information from data analytics important to manufacturers today (and tomorrow)?

Analytics bridges real-world inputs to real-world outputs leveraging the speed and power of the digital world to integrate more information, adapt to it, and evolve operations for better business outcomes.  Advancements in sensor technology, connectivity, communications networks, and the cloud mean that manufacturers can tackle challenges that previously were either too complex to scope, too costly and time-consuming, or lacked adequate information to root cause and validate.  Artificial intelligence, machine learning, and deep learning can not only help to more quickly and accurately identify patterns and trends from historical data, but they learn and adapt as new data comes in.  Analytics can merge previously disparate data from various business systems so your production line can get smarter based on your procurement system, and your procurement system can get smarter based on your quality system.  Although driving efficiencies, improving quality, and reducing costs are key benefits for smart factories today, the benefits emerging that will shape tomorrow are how the data can generate and grow new business opportunities.  IIoT-enabled products delivered to consumers and business customers can send data back to you, to help improve your product or service and open up new revenue streams never before explored, all backed by data.

 

What is the biggest myth or misunderstanding about data analytics?
Data scientists are trained to look for anomalies, identify trends, develop theories, and implement models and algorithms to get the best information from the data.  That sounds hard, and it is.  But what can be even harder is the work to explain the value of analytics and gain alignment to invest in the digital technologies and data science teams needed to realize the vision of Industry 4.0 and data analytics.  Often, especially in complex operations, the scope of work can feel overwhelming, setting expectations on outcomes and timeline can be difficult, questions and answers prove hard to articulate, and the journey requires extensive coordination between operations, IT, business units, and finance.  A phased approach and the involvement of one or more experienced eco-system partners can help companies achieve the incremental or end-to-end transformations that are manageable and get the investment support of leadership. 

Learn how Cyient can help accelerate your digital transformation with analytics-enabled solutions fueled by information.

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