The Use of AI for Materials Inventory and Data Management

Artificial intelligence for IT operations (AIOps) is an umbrella term for the use of big data analytics, machine learning and other artificial intelligence technologies to automate the identification and resolution of common information technology issues. 
The systems, services and applications in a large enterprise produce immense volumes of log and performance data. AIOps uses this data to monitor assets and gain visibility into dependencies without and outside of IT systems.
Information Technology plays a major role for a business to save more time and money, helping employees more productive and draws more business. In this case, we can clearly states that IT is not a business plan but rather, it strongly “supports” a business plan.For modern business, having a high quality data is essential for making decisions, help boost lead conversions, and drives success in inventory management.

A data driven-environment’s common data quality issues are poor organization, incorrect and poorly defined data, data inconsistency, and poor data security. Validating and cleaning bad data records equates to costly data cleansing tactics that threatens business efficiency.

When it comes to materials management optimization, obtaining an AI-enabled platform can quickly give a solution in providing inventory visibility and rebalance. It is a promising alternative compared to traditional cleansing methods.

This platform is widely used by businesses that maintain  and operate big data to achieve operational excellence. With the use of  AI platform, it is mostly possible to  ensure efficient operations. Businesses mostly in Maintenance Repair and Operations (MRO) use this platform solution  to keep an on-site inventory of the most commonly used items that can reduce downtime, extra expenditures, and the general stress of restocking. Industries mostly in Automotive, Industrial Equipment, Utilities, CGS, Aerospace, and Electronics, mainly uses this AI platform to optimize inventory management.

Wikipedia’s concise definition of inventory optimization is that “It’s a method of balancing capital investment constraints or objectives and service-level goals over a large assortment of stock-keeping units (SKUs) while taking demand and supply volatility into account.”

Artificial Intelligence is transforming the way we work, live, and collect data and it can help leverage technology in many ways to improve the MRO industry. It’s an effective way to utilize the use of  technology or devices to act smarter than humans.

Here’s the Top 5 substantial Reasons to use MRO Optimization:

1. To help avoid the risk of overpaying and under performing.
2. Effectively determines stock levels.
3. Balance demand and supply.
4. Increase service and safety levels.
5. Provides decision support system.

To be able to compete in dynamics market, relying on data stewardship is necessary to speed and scale a business. At this time, trusting manual process doesn’t makes sense if an organization aims for operational excellence and continually improve the consumer/partner experience.

With the right tools and technology, supported with the right MRO process and best practices, organizations can digitally transform. Leveraging data for more strategic, creative opportunities driving to advanced supply chains forward.

It is important to develop a full understanding of what specific MRO the company needs, to be able to efficiently foresees and monitor the inventory, suppliers, cost and services. To thrive, it is crucial to have positive mindset towards innovation and technology.

Again, with the right tools and with the right kind of help, inventory and performance efficiency can be achieved rather than relying on manual approaches that are prone to error.


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