Data-Driven Asset Lifecycle Solutions for Each Phase of Asset Lifecycle Management

Graham Perry
September 26, 2024

From acquisition to disposal, every stage of an asset’s life presents opportunities for optimisation and cost savings.

But how can you ensure you’re making the most of these opportunities?

This article focuses on:

Enjoy your read!

What Is Asset Lifecycle Management?

A quick recap first. Asset lifecycle management refers to the strategic process of overseeing an asset from its acquisition through to disposal.

This involves managing the performance, maintenance, and cost-efficiency of assets throughout their useful life.

The goal of effective ALM is to maximise the value of assets, reduce the total cost of ownership (TCO), and optimise asset utilisation.

Each phase of the asset lifecycle:

– can be enhanced through data analytics, enabling organisations to make informed, timely decisions.

Benefits of Data-Driven Asset Lifecycle Solutions

Without data, you’re left to make decisions about your assets based on gut and guesswork, rather than informed insights.

Analytics offers asset managers the ability to:

Lower Total Cost of Ownership (TCO)

Data insights enable organisations to manage assets with greater accuracy, reducing the need for costly emergency repairs and extending the life of critical assets.

By optimising maintenance schedules and avoiding premature asset replacements, the total cost of ownership decreases substantially.

Increased Asset Reliability

By continuously monitoring the condition of assets, good analytics ensure that equipment remains reliable and productive.

Predictive maintenance minimises unexpected failures, while performance analytics fine-tunes asset operations for peak efficiency.

Better Resource Allocation

Analytics-driven asset lifecycle solutions offer facilities and asset managers a bird’s eye view of asset performance, helping to allocate resources strategically —whether financial, human, or operational.

Sustainability and Regulatory Compliance

With the rise of sustainability concerns, asset lifecycle management has evolved to include responsible asset disposal and end-of-life strategies.

Data insights help organisations comply with regulations and reduce environmental impact, all while ensuring assets deliver the best possible return on investment.

Data-Driven Asset Lifecycle Solutions

Let’s take a stroll through each phase of the asset lifecycle and see how data-driven solutions can turn your asset management from good to excellent.

Phase 1: Planning & Acquisition - Making the Right Investment

The journey of asset lifecycle management begins long before an asset is purchased. In this crucial phase, data analytics can provide invaluable insights to guide decision-making.

- Predictive Analytics

By analysing historical performance data of similar assets, predictive analytics can forecast future asset needs with remarkable accuracy.

A study by Deloitte found that companies using predictive analytics for asset acquisition saw a 20-30% reduction in maintenance costs.

- Total Cost of Ownership (TCO) Analysis

Advanced analytics tools can calculate the TCO of potential assets, considering factors like purchase price, maintenance costs, energy consumption, and disposal fees.

This holistic view ensures that decisions are based on long-term value rather than just upfront costs.

Having a clear, data-backed picture of what you’re getting into ensures that you choose assets that are aligned with long-term goals and will require fewer resources to maintain.

Phase 2: Operation & Maintenance - Maximising Asset Performance

Once an asset is in operation, the focus shifts to optimising its performance and longevity. This is where real-time data and IoT sensors come into play.

- Asset Performance Monitoring

By continuously collecting and analysing data from sensors and other sources, you can gain comprehensive insights into how your assets are performing.

This includes detecting potential issues before they become major problems, tracking efficiency metrics, and identifying opportunities for improvement.

According to a report by McKinsey, implementing asset performance monitoring can reduce machine downtime by 30-50%.

- Performance Optimisation

Data analytics can identify patterns in asset usage and performance, allowing for fine-tuning of operations.

Performance analytics helps managers allocate resources more efficiently, ensuring assets are used at their full capacity without unnecessary wear and tear.

Phase 3: Repair & Upgrade for Higher ROI

When your equipment requires repair or upgrade, solid insights can guide decision-making to ensure the best return on investment.

- Repair vs. Replace Analysis

By analysing historical maintenance data, repair costs, and asset performance metrics, data insights provide clear recommendations on whether to repair or replace an asset.

This data-driven approach can lead to significant cost savings – one study found that companies using this method reduced their maintenance costs by 15-25%.

- Upgrade Impact Prediction

Before investing in upgrades, analytics can model the potential impact on asset performance and lifespan.

This allows businesses to prioritise upgrades that offer the best return on investment.

Phase 4: Decommissioning & Disposal - Optimising the End of Life

Here, data insights are invaluable for deciding whether it is more cost-effective to dispose of, sell, or repurpose an asset.

- Optimal Timing

Analytics can help determine the most cost-effective time to decommission an asset by considering factors like maintenance history, performance degradation, and market conditions for second-hand equipment.

- Circular Economy Opportunities

Insights drawn from end-of-life data can also identify opportunities for sustainable disposal methods, contributing to circular economy practices—a rising trend in asset management.

Implementing Data-Driven Asset Lifecycle Solutions with Analytics as a Service

Implementing data-driven asset lifecycle management in your organisation might seem impossible without access to an in-house data department or a huge up-front investment.

But it’s not 😉.

We created Analytics as a Service to allow ALL organisations to benefit from actionable data insights that save time and money and take daily operations to a whole new level of efficiency.

Analytics as a Service solution provides:

All of this at a fraction of the cost of an internal data team, on-demand, as a single subscription.

Do you want to optimise your asset lifecycle with data insights?

Contact Us

Graham Perry

Managing Director

Graham has worked within the built environment technology industry for the last 30 years. He is the lead judge for technology in the IWFM impact awards and has been a judge for the i-FM technology awards for the last 7 years.