Supply chain management is an optimization game. With AI, businesses are now able to focus more on achieving the best results and have more powerful tools. An industry expert shares ways to optimize supply chains by retraining workers using the latest artificial intelligence solutions.
If the past few years of business transformation have taught us anything, it’s that disruption has and will continue to be the norm—and businesses need to be prepared for it. In this uncertainty, they can only survive and advance by using the tools at their disposal. Thankfully, AI technology has matured enough to serve as a reliable tool for them.
Business leaders can gain a comprehensive view of their organization in real time with the right AI configuration. While trying to apply this information to streamline and optimize operations, they also need to deal with the current talent shortage.
There are no easy solutions, but once AI technology is integrated into workflows and employees accept adequate With training to use smart technologies, businesses will be better prepared for the next big shock. Here’s a look at the three main areas of transformation.
Under the wave of digital transformation, enterprises need to abandon traditional technologies and break down silos in the organization’s technology stack , integrating new technologies into business operations. By integrating weather predictions with supply chains, AI can predict and prevent disruptions due to weather. Weather events are becoming increasingly common and have a disruptive impact on supply chain processes. When a significant weather event occurs, running to standard delivery times is no longer feasible, causing the timeline to be completely disrupted.
Using historical weather trends and meteorological data, artificial intelligence can help companies assess the potential risk of delivery times being affected by weather events. If there is a strong likelihood, businesses can change their plans to prepare for the forecast, and this can even happen automatically as AI has the ability to make changes directly through ordering and shipping instructions.
While you can’t prevent a hurricane from happening, the better you can predict and plan for it, the better your business will perform when it happens.
The popularity of predictive maintenance is growing as enterprises adopt new artificial intelligence and ERP tools Increase. Predictive asset management (PAM) is a form of asset performance management (APM) that uses IoT data to improve asset reliability, reduce maintenance costs, and better understand asset performance. APM ensures assets are operating in optimal condition, improves their stability, reliability and availability, and facilitates the application of IoT data.
PAM reduces costs and time associated with maintenance by streamlining the work order process. Once the AI captures an alarm signal or error code from a faulty device, it analyzes the device’s previous working conditions and related signal codes. Based on the code and the machine's repair trip history, AI determines the correct spare parts and tools needed to complete the repair and records it on a work order, eliminating the need for initial diagnostics of the equipment and the time required to order parts.
Coupled with the Internet of Things and the ability of devices to provide this information directly to artificial intelligence, predictive asset monitoring becomes a reality for anyone using the equipment, such as field service technicians. Game changer.
Getting data right is a critical step in realizing the promise of artificial intelligence and predictive maintenance. For companies using AI in supply chain or asset maintenance, the primary method of designing, building, deploying and servicing assets is to obtain this data from sensors on equipment in the field or from data on the production floor. Businesses can reduce costs through the ability to integrate quality filters into processes and leverage source data to avoid having to physically travel.
This data is the key to understanding the actual condition of these assets. With continuous monitoring, companies can even predict when maintenance work should occur before or after scheduled maintenance. For example, if you see a device's temperature rising before scheduled maintenance, you can address it before the temperature gets too high and the machine goes offline, which will cause a larger disruption. Information coming directly from assets makes the predictive aspects and end results of data usage better.
Continued investment in data science by manufacturers and field service providers creates new job opportunities. A new survey commissioned by IFS shows that nearly a third of businesses see technological advantage as the most important differentiator, a figure that has tripled since 2018. It clearly demonstrates the relentless desire of businesses to take advantage of all the benefits smart technology has to offer.
While interest in deploying advanced technologies will only increase, the supply of skilled workers needed to make such deployments has not kept pace with demand. In fact, according to this IFS survey, nearly 50% of enterprises reported that they had difficulty meeting service level agreements, and 37% attributed this to insufficient technical support. In addition, skills shortages have never been more evident for manufacturers, with 44% stating that skilled labor shortages and turnover are their biggest concerns, and a further 40% citing user adoption of new technologies, 29 % of manufacturers say increasing asset complexity is their biggest concern.
Having the right people is just as important as having the right equipment. Retraining and upskilling existing employees can be a good place to start, especially as labor shortages grow across the economy and attracting the right talent becomes more challenging. By retaining existing employees and retraining them for new roles, companies can make institutional knowledge the key to a well-oiled machine and save costs associated with layoffs. Establishing a healthy company image is key to attracting customers and investment and boosting employee morale.
Starting an apprenticeship program can also help. Hands-on learning on the job allows companies to specifically train employees to their own standards. Employees who complete an apprenticeship program are more likely to stay with the company, which helps the company retain highly qualified technical talent. It's also an affordable way for people to gain new skills to win in the economy and learn relevant technical roles.
Solving any labor problem requires more than one solution. People and technology are two sides of the same coin. Thanks to artificial intelligence and innovation, businesses now have more powerful tools and can focus more on achieving the best results. Although smart technology is mature enough to be used in practical applications, we still need to face the challenge of labor shortage.
To realize the promise of technological advancement, companies must address labor shortages to ensure they have the right workforce. For a business to be successful, it requires advanced technologies and well-trained personnel to apply them.
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