Industry-Led Data Models in the High-Tech Manufacturing Industry

As companies grow, their supply chains become increasingly complex and difficult to manage. A point is reached where it no longer makes sense to keep using traditional, on-premise systems to keep up with a rapidly changing, dynamic market. 

Market leaders are encouraged to change their approaches and reflect the needs of a much more volatile market. In this article, we’ll explore how operations in the high-tech manufacturing industry can use data-driven and technology-based methods to stay ahead of the curve with examples.

The power of data analytics in MRO 

Harmonized data across sites 

Keeping track of data in operations with many moving pieces can be a challenge. This is especially true when it comes to synchronizing maintenance, inventory, and procurement data to keep MRO operations running smoothly. However, without a harmonized system, it is almost impossible to gain meaningful insights from data collection. 

According to Balika Sonthalia, a partner in E2E operations at Kearney, MRO leaders make the mistake of looking for external data when trying to improve their supply chains as opposed to optimizing processes using the existing, internal data that they already have. 

The right materials management solution should harmonize your supply chain data from multiple locations and consolidate it into a single, intuitive platform. Not only does this offer a 360-degree view of your entire supply network at the tip of your fingers, but by synchronizing data you can virtually eliminate the need to dig through disparate systems.

What should be noted is that unstructured data can’t be added to normal databases to gain meaningful insight because it doesn’t conform to standard data modeling practices. Using a purpose-built cloud-based solution, however, uses the data “as is” across the entire system so that you can gain meaningful insights and make better decisions faster than ever before. 

Efficient processes come from optimized systems

Today’s manufacturing and supply chain landscape vary from day to day with delays often compounding on one another. To keep up with changes, procurement and MRO teams can’t allow processes to stagnate by referencing outdated forecast models or ignoring them all together. Rather, they must be flexible enough to adapt and pivot when disruptions arise. 

Optimization tools and strategies should build upon what already exists, using historical data to create a system that’s tailored to your operation. Industry 4.0 tools such as artificial intelligence (AI) and machine learning (ML) can use existing data to find patterns and simulate models that reflect the subtleties of the current market to provide recommendations for the best possible outcomes. 

The system should be able to factor in lead time constraints, consider what-if scenarios around item lifecycle, help mitigate the effects of disruptive events, and pose actionable suggestions that are the most sustainable operational strategies.

Data analytics in action 

Reduced costs and strategic procurement 

A.I enhanced data analysis is an excellent way to accelerate your ability to take a detailed look at your spending and cut back on costs. Previously, procurement teams had to use manual data collection methods to sift through piles of paperwork before manually analyzing and making sense of data. 

However, supercharging your system with natural language processing (NLP) can help you track where, when, and how money flows out of your MRO storerooms from start to finish. Information regarding spare part values, holding costs, and plant utilization can be used to create detailed spending models so each dollar is well spent. 

What’s more, with a digital trail of cash flow around existing inventory levels, teams can identify and eliminate any occurrences of rogue spending. 

A.I. driven data analytics are also useful when it comes to supplier performance review and overall management. An AI-based system can evaluate suppliers based on various metrics and Key Performance Indicators (KPIs) to keep them accountable. They can then be ranked according to their performance and the scores obtained. Some metrics to look out for are:

• Lead time
• Product quality 
• Pricing 
• Shipping delays and shortages (OTIF)

Tailored maintenance schedules 

When managing MRO parts and maintenance requirements, there is no shortage of unexpected, disruptive events. 

One of the biggest threats to supply chain activity that has plagued MRO businesses is unplanned downtime events which can have both tangible and intangible costs. 

An intelligent system that comes with predictive analytics capabilities out of the box works with existing data and newly collected data to suggest optimal times for maintenance based on the asset’s make, model, use, and records of downtime. 

With routine and strategically planned maintenance, it’s possible to increase the lifespan of assets without increasing maintenance costs.

It doesn’t just stop there. Intelligent solutions powered by machine learning can also forecast which replacement parts are needed for assets. It makes it easy to strategically restock and prevent downtimes that arise from shipment delays or wasted expenses on excess stock. 

Data-driven solutions lead to effective and efficient outcomes

The ability to harness the insights of big data is how supply chains will move forward with more resilience and efficiency.  New solutions offering purpose-built capabilities are allowing companies to unlock the full potential of their operations.

Although digital transformation has a ways to go, it has become an industry standard. MRO leaders that take action and adopt purpose-built data models into their supply chain will put themselves miles ahead of the curve, all the while identifying best practices in a market filled with uncertainty.  

Find out how Verusen can help your operation run leaner, faster, and smarter today.