How much is data worth to your business? According to a study by Boston Consulting Group (BCG) and the World Economic Forum (WEF), manufacturing companies could save billions by combining their digital records. This article explains the opportunities sharing data creates for manufacturers and the obstacles they may encounter.
While big data and artificial intelligence (AI) are changing the face of industry, BCG and WEF’s research has found they also could produce benefits worth $100 billion for businesses worldwide. This conclusion is based on a survey of 996 manufacturing managers by calculating the savings their various suggestions could bring to manufacturing companies.
Data sharing is considered a viable opportunity by manufacturing managers. Of those surveyed, 72% thought sharing data with other manufacturers would improve operations, while 47% believed optimized assets are the biggest benefit of sharing data more widely. How can this contribute toward billions in savings?
Learning to save
BCG and WEF’s study estimates the manufacturing industry could save $40 billion by optimizing assets through machine learning. The idea is interconnected machines use predictive algorithms to improve each other’s performance (see Figure 1). With access to performance data, machines can help reduce downtime and optimize processes.
A further $40 billion could be saved by tracking products along the supply chain more effectively. If users know where a product is at any particular time, they can better plan their processes and prepare for supply and demand fluctuations. By using data to create a comprehensive picture of the supply chain, users can reduce inventory levels, stocking only what they need, and make better informed, or even automated, purchasing decisions. Both will directly benefit the bottom line.
BCG and WEF’s report estimates a further $15 billion could be saved by knowing the origin and condition of products along the entire value chain. This knowledge can be invested into improved quality management by finding the root causes of faulty products more quickly and accurately. Companies that operate in highly-regulated environments, like the food industry, could realize a large part of these savings.
Obstacles to data sharing
While BCG and WEF’s suggested uses for data sharing clearly have their advantages, achieving those savings is not without challenges. One involves buying and building the new computing infrastructure needed to connect machines, companies and industries, which can be costly and time consuming. Instead, a faster and potentially more cost-effective way to digitalize processes is by retrofitting new technologies to old equipment.
One way to retrofit is through the use of smart sensors, the global market for which is growing at a 19% annual rate and is expected to reach $60 billion by 2022, according to Deloitte. Sensors can be fitted to existing machines to gather data on their performance and allow decision-making about production processes, in real time. A specialist supplier of industrial automation parts, such as Radwell International, can help in sourcing the retrofitting components needed to fully embrace digitalization.
Take the example of a packaging line where managers can’t understand why output is lower than normal. Smart sensors could be fitted at each stage along the line to work out which process is causing faults or slowing production. This will tell the managers where their losses are and enable them to fix the issue quickly and effectively.
Another example is fitting a range of computerized numeric control (CNC) machines with sensors that supply data about their performance. If a CNC machine in one location produces burn marks because of an improper feed speed, the same type of machine at another location could automatically correct its speed to avoid the same problem — otherwise known as machine learning. By analyzing the resulting stream of data, manufacturers can glean clues on common faults and maintenance cycles and achieve tangible cost savings.
Data sharing also can involve sharing design specifications and tolerances with suppliers and customers. This can reduce the tolerance stacking that occurs when different suppliers maximize their tolerance allowances, resulting in a final product that fails to meet the customer’s standards.
Another challenge for manufacturing managers is increasing data sharing capabilities can increase security risks. Data sharing multiplies the access points through which hackers can infiltrate computers, which is why manufacturers should implement an effective system hardening strategy, to close such loopholes. Effective data sharing should be accompanied by regular system hardening audits to identify system vulnerabilities and help install software patches that secure data sharing.
Better to share?
By effectively using smart technologies and digitalization strategies, you can not only collect useful data, but use it to improve efficiency within your business. AI and big data have made it possible for information, such as that gleaned from smart sensors fitted to manufacturing machines, to be continuously analyzed and used to optimize assets.
What could data sharing be worth to your business? While saving $100 billion across U.S. manufacturers is a huge estimate, digitalization will enable manufacturers to share data safely, securely and in ways that significantly benefit their bottom line.
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