Insight
How to Create a Holistic Reliability Strategy and Successfully Embrace Emerging Technology with IBM MAS
Industry 4.0 has moved fast. Sensors, connected systems and the advancement of Artificial Intelligence (AI) all promise better asset decisions and fewer surprises heading into the next era of the industrial revolution. Some teams have leaned in, while others have added tools as needed. However, both approaches can stall when new capability lands inside the IBM Maximo Application Suite (MAS) before the foundations are solid. Organizations must focus on the process first and then apply the technology secondarily.
Jumping into an IBM MAS implementation or upgrade without considering your organization's entire reliability journey can cause more confusion than progress. What’s needed is a clear baseline, a roadmap out of firefighting, disciplined data that makes AI useful and a measured IBM MAS rollout. With that in mind, reliability teams can move from principles to practice.
Full Suite of Integrated Services
Understand Your Reliability Baseline
Fewer interruptions, steadier yield and simpler inspections all start with definition and governance. Our Life Sciences Enterprise Asset Management team at ABS Consulting recommends that organizations build a clean asset model in their computerized maintenance management system (CMMS), define what counts as an asset, a component and a location, and use it consistently across sites. Then they can rank equipment by impact on quality, compliance, availability and cost.
Part of the criticality process is to realize that not all assets are the same—some are more important than others.
From there, organizations can translate importance into evidence-based care. Use original equipment manufacturer (OEM) guidance as a start. Mature the strategy with meaningful failure codes, fixes for repeat problems and condition checks that spot early wear. Spare parts need to reflect strategy and lead times because waiting for a calibration spare means downtime that could have been avoided.
Move From Reactivity to a Roadmap
Most plants carry a mix of reactive fixes, time-based preventive maintenance (PM), condition-based tasks, and a bit of predictive maintenance (PdM) with analytics. While the reality is that most organizations may never totally get rid of reactive maintenance, they must work to minimize it and evolve toward a proactive approach.
Shifting the balance involves:
- Stabilizing planning and scheduling so more work is planned and wrench time improves.
- Converting calendar tasks to condition-based tasks where the signal adds certainty.
- Using PdM analytics where the consequence of failure is high and the signal is strong.
It helps to think in life cycle terms. Monitoring will be different for early-life versus late-life assets.
Make Data Trustworthy Before You Make it Real-time
AI and PdM tooling amplify whatever you feed them. If master data, routes and failure codes are inconsistent, teams just get faster noise. This is why they must make sure that the fundamentals are in place before implementing some higher level technology, or else they could wind up doing a lot of heavy analysis on data that may not be good quality.
And don’t be fooled by activity, because in general, the reliability think tanks will say that preventive maintenance 50% of the time does more harm than good. Build updates into change control so asset data, parts lists and strategies stay current and validation doesn’t become a rework cycle.
Make sure the fundamentals are in place before implementing some higher level technology, or else teams could wind up doing a lot of heavy analysis on data that may not be good quality.
Know Where IBM Maximo Application Suite Adds Value
With its strong, flexible interface, IBM MAS accelerates the journey when the process is ready. Treat it as the platform that brings CMMS work, asset health, condition monitoring, mobile and analytics into one system of record.
Adopt capability in slices, for instance:
- Pilot on one high-value line (health scoring + one PdM use case).
- Show earlier detection and a clean signal → work order → verified fix flow.
- Scale once proven.
- In parallel, set roles, train the team and document who decides what, how exceptions are handled and who signs off inspection-ready.
Adopt Technology With Confidence
It’s easy to get lost in the technology. But rather than a grab-bag of new tools, life sciences teams need a reliability strategy that lets them adopt tools confidently.
When data is accurate and criticality is clear, disciplined work turns IBM MAS, condition monitoring and PdM analytics into real multipliers for industrial reliability. Uptime improves, compliance stays intact, and costs come down.
IBM Maximo specialists at organizations such as ABS Consulting can guide the transition end-to-end so that this critical-asset technology becomes a fully integrated, inspection-ready platform—one that helps strengthen asset reliability, uptime and compliance across operations.
Revisit our webinar covering The Evolution of Maintenance and Reliability for more insights into the IBM Maximo Application Suite.
About the Author
Walter Betsill - Senior Operations Manager
Walter Betsill has more than 30 years of experience working with maintenance and engineering organizations. He began his career in the chemical industry prior to becoming a cross-industry field consultant. In the 1990s, Walter worked for the two top CMMS software companies, PSDI (IBM Maximo) and Datastream Systems (Infor EAM), first as a field consultant and subsequently as a project manager. In 2000, he became a founding member of GenesisSolutions, now the Asset Management service line of ABS Group. Betsill helps his clients evolve to a better state of maintenance operations and reliability. His current focus is to assist clients in identifying the data that indicate success and then utilize good processes and technology to obtain the data easily and with a high degree of quality.
