Disrupting Manufacturing with Digital Transformation

With ever increasing challenges of globalization and competition, manufacturers are now looking at leveraging digital technologies to transform their business models and sharing data and insights with partners across the manufacturing value chain

Disrupting Manufacturing with Digital Transformation - CIO&Leader

At the end of the 19th century and beginning of the 20th century, the Industrial Revolution transformed the manufacturing industry. With the advent of digital technologies, a new revolution is ushering in the manufacturing space, which experts refer to as Industry 4.0.

With ever increasing challenges of globalization and competition, manufacturers are now looking at leveraging digital technologies to transform their business models and sharing data and insights with partners across the manufacturing value chain. While Industry 4.0 promises efficiency of processes and operations and a paradigm shift from products to data driven services, the benefits extend beyond traditional manufacturing output. The digital value chain can be applied across the manufacturing value chain as we shall examine in the next section.

Transforming Manufacturing with Digital Technologies

At the cusp of digital disruption in manufacturing is ‘the insights from data’ generated at each stage of the value chain, that is empowering manufacturers and their partners to transform their business models. Let us examine the value chain and how digital transformation is a differentiator at each stage of the value chain.

  • Raw Material Suppliers – Manufacturers are dependent on raw material suppliers for meeting their production plans based on projected demand. The key to managing the supply demand gap is through effective Supplier Performance Management. Manufacturers are sharing key performance metrics with Suppliers to help them perform better. Inventory Planning and Replenishment KPI’s are also crucial in measuring the efficiency of raw material supplies and this data is shared with suppliers and partners to help them understand the supply-demand dynamics.
  • Inbound Logistics – Manufacturers are dependent on 3rd party logistics providers to provide both inbound and outbound logistics. Inbound logistics is related to movement of raw materials from suppliers to the manufacturing plant. The key transformation drivers are Route Optimization to manage the time for the feedstock or raw materials to reach the plant. Shipment Tracking and Logistics Analytics help manufacturers have an end-to-end view of logistics operations and efficiency of transportation methods in terms of delivery timelines and cost.
  • Production Operations – At the core of any manufacturing enterprise are the principles of Demand Planning to measure the market demand for specific products based on economic parameters and market growth plays. Demand Planning in turn helps enterprises define their Production Plans to meet the market demand for products. Manufacturers are using Big Data Analytics, IoT and Artificial Intelligence (AI) to identify Production Optimization opportunities as well as performing Production Analytics to see efficiency of plant operations. Various parameters like equipment downtime, process throughput and unit-level utilization are aggregated to derive the production optimization opportunities as well as measure Productivity.
  • Outbound Logistics – Finished goods/products stocked in plants are transported by outbound logistics providers to warehouse or wholesalers. Transportation routes are analyzed to see the optimal routes (Route Optimization) helping transporters provide on-time delivery. Weather data is being integrated into route planning to ensure impact of weather events on delivery timelines is minimized. Stock-out Analysis data is analyzed to determine fast moving products from warehouse and wholesalers, helping manufacturers replenish the stocks and use outbound logistics more effectively. Warehouse providers plan their layouts (Warehouse Layout Optimization) leveraging IoT and Big Data Analytics to derive optimal storage patterns. Outbound logistics providers also analyze losses during transportation due to leakages or poor handling which helps plan better transportation operations.
  • Sales and Marketing – Manufacturers are increasingly driven by customer demands and preferences and are going all out to collect data around Customer Segmentation and Marketing Effectiveness of campaigns. Customer Segmentation helps understand customer demand for products based on their business value needs and helps target customers with the right set of products thereby increasing efficiency of marketing campaigns. According to IDC, manufacturers are leveraging Big Data Analytics to help optimize their sales and marketing activities.
  • Customer Servicing – For manufacturers to succeed, they need to retain customers and at the core of customer retention is After Sales Support and Servicing. Enterprises are performing client satisfaction surveys and collecting data from 3rd party data providers on customer satisfaction levels from After Sales Support and Servicing. Customer Relationship Management (CRM) programs are leveraging the customer feedback data to manage customer preferences and retain customers.

The key disrupting technologies that are reshaping the way manufacturers are making the transition to a connected, intelligent enterprise are as follows:

  • IoT and Industry 4.0 – At the core of the connected enterprise is the use of IoT sensors in industrial equipment, which provides real-time insights and alerts about defects or equipment issues or damaged goods. Industrial plants with IoT embedded in processes helps manufacturers get a real-time view of operations with an ability to monitor and respond to potential issues like equipment performance or process bottlenecks.
  • Artificial Intelligence (AI) and Machine Learning (ML) – AI and Big Data are crucial differentiators for manufacturing by ingesting data from across the value chain that help optimize processes and boost production capacity by 15%. Machine learning algorithms help determine which factors impact production quality and service. Insights shared with suppliers and logistics providers help them optimize operations for an efficient supply chain.
  • Robotics – Robots have been used in manufacturing assembly lines in the past for repetitive tasks. Today robots are enhancing productivity and safety by replacing human works in hazardous work environments like undersea rigs or mining environments. Robots are being used in material handling systems, spot welding, spray painting, etc. Philips uses more robots than humans in a plant manufacturing electric razors. A recent PwC survey revealed that at least 59% of manufacturing companies are using robots.
  • Blockchain – Blockchain has huge potential to transform the manufacturing industry through its distributed ledger that provides secure and transparent records which can be of significant value to enterprises with global supply chains that are often complex and riddled with transparency issues. Data held in a blockchain is decentralized and shared across nodes, which provides insights into the complete supply chain and identify the bottlenecks and issues. Blockchain can help auto manufacturers identify faulty parts and the suppliers supplying them.

As is evident from the transformational impact of digital technologies at each stage of the Manufacturing value chain, companies are increasingly looking at leveraging these technologies not only for collaboration, productivity enhancements and cost optimization but also as a differentiator in enhancing revenues through enhanced customer experience and targeted campaigns. The key benefits that digital disruption has provided are as follows:

  • Collaboration across Supply Chain – Ability to ingest data from across the supply chain has provided numerous opportunities to collaborate better with suppliers, logistic providers as well as end customers. The data collected at various points in the supply chain enhance decision-making around quality of suppliers and has helped in supplier consolidation and better information sharing with suppliers. The same applies to logistics providers as well, where data shared around demand helps logistics providers factor in optimized delivery plans and route optimization. Use of blockchain solutions can also bring in transparency across complex supply chains, enabling manufacturers to make informed decisions based on the insights generated.
  • Cost Optimization – Digital technologies have helped optimize the cost of operations by analyzing data across the supply chain which can be analyzed to generate insights across Raw Material Sourcing, Inbound and Outbound Logistics, Production Operations, Sales and Marketing and Customer Servicing.
  • Customer Retention – Armed with the digital technologies and enhanced customer service capabilities, manufacturers are better placed to handle customer churn as well as acquire new customers by understanding customer demand better. However, customer loyalty can be earned by continuous innovation in optimizing the supply chain as well as enhancing the customer experience.
  • Productivity – As we have seen right across the value chain, digital technologies have brought significant productivity gains through Automation, Big Data Analytics, Robotics and IoT. Ability to handle and process unstructured data from social media sentiment analysis around product and service quality, weather data for route planning optimization has also enhanced productivity of enterprises which would spend many man hours analyzing such data sets and generating insights.
  • Revenue Models – With customer centricity at its focus, manufacturers will look to create customized offers/product bundles to meet customer-buying behavior. This creates an ability to generate new revenue streams as well as look at Cross Sell opportunities based on market demand and competitive intelligence. The ability to merge multiple data sets and generate insights creates new revenue generating models and opportunities.

McKinsey surveyed over 300 manufacturing companies and found only 48% considering themselves to be Industry 4.0 ready, while over 70% of suppliers were found ready. While manufacturers have embraced digital technologies, adoption across the complete value chain is still at different stages of maturity and creates opportunities to build a strong digital foundation with capabilities encapsulating the entire supply chain in close collaboration with suppliers, logistics providers and customers. Industry 4.0 is developing in India, with Bosch implementing smart manufacturing in India while GE is investing USD 200 million to build a multi-modal facility with digitally interlinked supply chain, distribution networks and servicing.

The author is Data Platform Solutions Lead at the Services Integration Hub in IBM and has written three books

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