These days, data is more ubiquitous and accessible than ever before. So are you using it to make informed business decisions when it comes to facility maintenance?

It’s time to start using the technology available to us and leveraging the information that’s at our fingertips to create value, reduce maintenance costs, and increase reliability.

Predictive Asset Optimization 

Predictive Asset Optimization (PAO) employs big data and analytics to optimize the production time and life expectancy of your assets. By applying predictive analytics, your organization can be proactive and prevent costly operational delays.

In other words, today’s technology can predict when a problem is likely to occur, allowing you to perform preventative maintenance before an actual problem arises.

Furthermore, according to IBM, PAO enables organizations to:

• Monitor, maintain, and optimize assets for better availability, utilization, and performance
• Predict asset failure to optimize quality and supply chain processes, ultimately accelerating an organization’s time-to-value 

Being Data-Driven at Your Facility 

All of this technology and data is great, but it won’t be helpful unless you and your team can utilize it effectively. In order to do so, your organization needs to have:

1. Knowledgeable People 

It all starts with your team. The more bought-in and willing your team is to make adjustments based on predictive analytics, the more your data-driven facility maintenance initiatives will succeed.

2. Structured Methodologies

These methodologies should run the gamut: from risk management and risk based maintenance to mechanical integrity, legal and regulatory compliance, and life cycle costing. 

3. Defined Roles and Responsibilities 

In order for your people to succeed, they will need clearly defined roles and responsibilities that outline exactly how the data is to be implemented into their decision making processes. 

4. Structured Work Processes

Similarly, work processes need to be clearly defined so that team members know what is expected of them, and they should include quantifiable measures of success.

5. Software and Tools

Last but not least, software and other tools will need to be leveraged in order to interpret the data. This will help turn data into information team members can utilize to make decisions with regards to asset life cycle management and risk management. 

Finding a Partner 

In order to achieve your data-driven goals, you’ll need to enlist the help of a knowledgeable vendor. This facility maintenance partner should help you reach your goals by providing the following: 

1. KPIs: Defined KPIs to help close the loop.

2. Blueprints: Functional blueprints for implementation based on the business case.

3. Equipment: Software, process equipment, etc.

4. Best Practices: In regards to maintenance processes, asset management, computerized maintenance management systems, reliability processes, etc.

5. Support: By turning data into technical solutions.

6. Asset Performance Management: Helping clients implement asset performance management in order to achieve desired results.

Conclusion 

Data-driven facility maintenance is the facility management practice of the future. By utilizing all of the technology and data now available to us, we can fine-tune our processes and develop systems that improve operational efficiency, increase reliability, and reduce maintenance costs.