In Progressive’s latest podcast episode, we sit down with Rachel Wagner from our partner Hexagon Asset Lifecycle Intelligence, to explore how Asset Performance Management (APM) is transforming the way organisations can manage risk after acquisition, optimise performance, and make smarter, data-driven investment decisions.
Below are short snippets highlighting some of the key questions explored in the episode:
Can you provide some examples of organisations that are successfully translating asset risk insights into measurable, real-world cost savings using Asset Performance Management?
APM In Action: Alyeska Pipelines save over $1,000,000 in optimised maintenance savings.
APM In Action: Western Midstream compressor failure avoided, each saving $50,000 – $70,000.
How can organisations overcome the challenges of asset acquisition?
Industry Insight: Following an acquisition, companies often inherit mature, complex assets with limited visibility into their true condition, performance history, and associated risks.
What are the consequences of operating without an Asset Performance Management (APM) system?
Deep Dive: Without an APM system, organisations remain vulnerable to hidden risks, unplanned downtime, and escalating maintenance costs.
Key Takeaway: APM can help your organisation achieve predictable production at the lowest sustainable cost, while measuring the risk profile of the assets.
What Industries can benefit from APM?
APM is a vital element of overall asset management for any capital intensive industry such as:
- Oil & Gas
- Manufacturing
- Aerospace
- Pharmaceuticals
- Consumer goods
- Power generation
- Data centres
Other questions answered in this podcast:
- How is APM applying AI technology?
- How can you identify which assets are the riskiest to your business today?
- How to determine business spend on unplanned reactive work?
- How to identify all the possible losses of a downtime event?
- What can you do if you don’t have access to historical asset data?
Case studies to read:
Download Jump Starting Reliability in Midstream Oil & Gas case study
