CEOs know they need to respond to disruptive technologies to remain competitive. What’s necessary is a pragmatic step-by-step way forward.
What’s all the fuss about?
Warren Buffett promoted the term “economic moat.” This relates to a company’s ability to maintain an advantage over its competitors (through process, technology innovation, and intellectual property) in order to protect its long-term profits and market share. With data analytics, big data, the Internet of Things (IoT), the smart factory, machine learning, predictive maintenance, and blockchain all turning from vision to reality, your competitors are building their ‘moats’ now.
Your competitors are building their moats now...so don't get left behind. Image courtesy: Pixabay
Today, IoT devices and disruptive technologies are being deployed throughout all areas of the supply chain and in a variety of verticals. It's a hopeful sign to electronics OEMs looking to do the same. In the pharmaceutical industry, GlaxoSmithKline is starting to leverage blockchain, cryptographic security and smart contracts to provide verifiable insights as assets are managed and propagated through the entire supply chain. In 2017, Wal-Mart tested a new traceability program using blockchain technology, with positive results. The supermarket giant tracked pork in China and mangoes in the U.S., establishing a digital history for each product.
Formula 1 motor racing company McLaren plans to start 3D-printing parts for its F1 cars trackside at Grand Prix competitions around the world. The firm believes the technology and supply chain approach will give it an advantage over rivals allowing it to make last-minute changes. From manufacturing goods to medical implants and even food, 3D printing technology is set to have a deep and permanent impact on the supply chain.
Data analytics is at the forefront of supply chain management right now, given its power to demonstrably impact competitive advantage. For example, one of the world's leading crop nutrients providers needed to improve competitiveness and assess the cost benefit and rail routing options of 48 potential origin-destination route options in North America.
The insights and implementation support our supply chain and data analytics experts provided helped senior executives select and establish the optimal location for their new $50M North American distribution operation. Consequently, the company was able to get products to market five days faster than its competitors. This competitive advantage (‘moat’) resulted in a 7% increase in the company’s market share year-over-year in four consecutive years. At the same time, our team helped reduce the company’s rail fleet by 50%. This saved $48 million in freight rate and fleet savings, while releasing over $500 million in inventory and working capital for the business.
If you don’t currently have this sort of visibility into your operations, data aggregation and dashboard visualization (using your existing system’s data) is critical to get actionable insights, fast. Tightly connected to data analytics is the advancement in predictive maintenance and artificial intelligence. With manufacturing operations destined to become increasingly autonomous, predictive maintenance (using machine learning to perform condition monitoring and prognostic analysis) is set to revolutionize the way operations are managed and maintained. This involves sensors being deployed all over the factory, providing real-time data on the status of production and machinery performance. By reducing unplanned machine down time by as much as 30 to 50% and increasing overall equipment effectiveness (OEE), companies are set to increase the productivity of maintenance staff by 45 to 55% and reduce maintenance cost by 10 to 40%.