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Top 5 Digital Transformation Myths in Industrial Manufacturing

Digital Transformation is the leading theme in board rooms, and this topic now dominates transformation budgets across industries. So, what is Digital Transformation? Given all the noise around this subject, it’s no wonder executives struggle to define Digital Transformation in one sentence. This article will help you define Digital Transformation in one sentence. We will also let out secrets that will help you ask the right questions as you embark on this initiative.

Digital transformation can be defined as using the power of new digital technologies such as cloud, IoT and analytics, social media, and edge computing to transform the firm’s business model and improve customer experience. So, what are the benefits of Digital Transformation to companies?

  1. Inform products for new revenue streams or services
  2. Transform customer engagement
  3. Virtualize people processes while enhancing engagement
  4. Re-define supply chain boundaries
  5. Create new digital ecosystems

Industrial Manufacturers of large, expensive, mission-critical industrial equipment have also embarked on a digitization path. To improve customer experience and digitize the supply chain, they have started to actively participate in the manufacturing processes of their clients to set strict operations management objectives, optimizing the efficiency of machine processes. However, the journey to digital transformation is long and has many pitfalls. In this article, we bust a few myths surrounding digital transformation for industrial manufacturers.

1. Predictive Maintenance Needs Machine Learning

These days, it is a general perception that predictive maintenance is an exclusive domain of Machine Learning (ML) and that it is imperative to implement predictive maintenance. However, it is far from the truth. For instance, a leading industrial manufacturer maximized value capture from predictive maintenance with a basic mathematical modeling technique without using ML. Hence, it is only fitting to assess the marginal value of ML before jumping on the bandwagon.

2. Competitive advantage requires custom development of platforms

Competitive advantage can also come from time-to-market, accessing, best-of-breed components, and improved integration into digital ecosystems, which can come from pre-packaged solutions. For example, Salesforce drives competitive advantage through deep integration of customer procurement systems.

3. Digital solutions create value by transforming enterprise processes

Yes, but the most value is created when you transform your customers’ and suppliers’ processes along the value chain, integrating with the digital ecosystem outside of the enterprise as well.

4. Embark on an IOT journey

Though IoT and IIoT have identical fundamental layers and share the same technologies, they are not the same. IIoT is the subset of the larger IoT that connects industrial assets, predictive analytics, and workers. The manufacturing industry has adopted IIoT to leverage its unparalleled productivity, agility, and efficiency levels to drive astonishing transformations in the domain, driving significant positive business outcomes and personalized customer experiences.

5. A large part of Digital transformation is technology and operations

Digital transformation is not just about making operational changes. It is also about transitioning toward a new lean-agile culture, bringing positive organizational changes. Processes like smart small, iterative engineering, and Minimum Viable Products are no longer exclusive to IT initiatives. It must be adopted at the enterprise level, even in the industrial environment.