If you work in manufacturing, you know how quickly competitors can gain an advantage: a plant improvement here, a supply chain tweak there—it all adds up. Additionally, the challenges facing manufacturers are driving them to transform the way they manufacture, distribute, sell, and support their offerings across the entire product life cycle. Using big data in manufacturing can give you the upper hand by making you more competitive.
Competition in the manufacturing industry is becoming highly unpredictable as innovation comes from an increasingly wide array of regions and markets. This can leave companies struggling to keep up, making efficiency in supply chains and manufacturing plants more important than ever. Exacerbating this competition is the accelerating innovation cycle. Improved technical capabilities enable competitors to design, engineer, manufacture and distribute products more quickly than ever before, reducing their time to market.
So, can using big data in manufacturing help businesses meet these competitive challenges? Absolutely. Companies with a more holistic view of their enterprise can spot potential issues and optimize their processes to retain a competitive edge.
For example, big data can also drive efficiency in product manufacturing processes through machine learning. This branch of artificial intelligence, which analyzes historical data to understand “normal” process performance, enables companies to monitor plant processes to detect anomalies, and optimize product quality and production yield. This, along with the ability to leverage machine learning-enabled predictive maintenance models, can dramatically minimize plant equipment downtime, driving down overall manufacturing costs even further.
Another problem manufacturers face is that their competitors are taking advantage of more complex, rapidly evolving supply chains. Digital supply chains respond faster to changes in demand due to a real-time flow of information, complete visibility, and the ability to respond quickly.
As manufacturers come under pressure to navigate these supply chains for better pricing and delivery terms, they must also ensure that they meet regulatory compliance challenges around environmental and corporate quality controls. Sourcing nonoptimal components that don’t meet environmental standards could create compliance problems further down the line.
To prevent these problems while making the best use of the supply chain, manufacturers need a holistic understanding of conditions throughout the delivery pipeline. They must extend their visibility from the factory to the supply chain, drawing data from a range of stakeholders, including suppliers and logistics firms. This can create a complete view of the supply chain that will help manufacturers predict and adapt for emerging issues.
The more data sources that you can consume, the more you can understand and refine your manufacturing process. Pulling in supply chain data from logistics partners and suppliers can help you further refine your products by looking for patterns that affect quality and production times. Seeing patterns in supply chain behavior can help you avoid disruptions in materials supply, further enhancing your manufacturing efficiency.
At the other end of the supply chain lies the consumer. There, too, companies face new challenges. Consumers are increasingly empowered, enjoying an unprecedented range of product and service options. Manufacturers that don’t anticipate their customers’ needs risk losing them. It’s all about growth in this hyper-competitive marketplace and growth demands excellence in customer experience with customer-centric interactions, and innovative products and services throughout the product life cycle.
The smartest vendors turn these customer challenges into opportunities. They use big data to gather and analyze customer requirements and feed those insights back into the product design cycle in a process of continuous improvement. They can use a variety of sources for this, including customer relationship management and marketing systems, sales databases, and technical support feeds.
Companies that master big data can meet these industry challenges and set themselves up for longer-term success. Instead of aiming only at short-term goals, such as increasing production volume and lowering costs, they can use data from this unified supply chain and manufacturing ecosystem to gain insights into new market opportunities.
Rather than blindly turning the crank to hit the next quarter’s sales target, smart companies can use this data to identify new geographical and product markets, and plan targeted business expansions, paving the way for structured, healthy growth.
This ultimate use of big data will come after manufacturers use data sources to create a more cohesive view of their product life cycles. Along the way, they can improve their competitive advantage by realizing tangible improvements in productivity and quality.
The data is already latent in the manufacturing plant and in your logistical supply chains. By using big data in manufacturing to power your decision-making, you can unlock its value.
For further insights into how you can own your future in manufacturing, check out this e-book.