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Decarbonisation will frame the operating context of so many asset classes and sectors over the next decade. It is disrupting previous lifecycle plans, investment and reinvestment decisions, asset management strategies and tactics, and the physical asset manager's role.

The next decade brings with it the greatest workforce challenge we’ve ever faced. Machines and automation are replacing human tasks. And macro-factors like decarbonisation will impact future jobs and skills. This changes the skills that organisations are looking for in their workforce. Companies are thinking about the future in three different ways: immediate, the next 12 months; short to medium term, the next 3 to 5 years; and long-term thinking and planning for the next 5 to 10 years.

One of the most complex challenges that asset managers face is driving strategic change from a partially empowered position within an organisation. This involves both managing upwards towards executive management and downwards through the mid-level and shop floor, without having all the levers to jockey. How do we define the value of Asset Management, ROIC (return on invested capital), get the CFO’s attention, work with consultants and advisors, find quick wins, and use ISO 55000 as a framework?

The need for Reliability Engineering in High Reliability Organisations (HRO's) is clear: to avoid catastrophes in an environment where normal accidents can be expected due to risk factors and complexity. The consequence of poor reliability in HRO’s is severe. In other industries this need is less obvious, so business leaders are challenged with finding the correct level of investment in reliability and reliability engineers.

The significant increase in mental health and wellbeing challenges over the last few years are a result of job insecurity, high job demand and pressure to perform, lack of empathy and understanding from leadership, and the imbalance between effort and reward. But by far the biggest reasons for this increase are the ongoing effects of the COVID-19 pandemic, and relentless organisational change. Companies reported that the issue is greater than it’s ever been, and getting worse. Poor mental health has a significant impact on an individual’s health, attendance, performance, engagement, and safety.

We are drowning in data. If it’s agreed that assets are important for the business and that data is important for the business to optimise these assets, then it follows that capturing, storing, and making data-led decisions should be of equal importance. However, organisations are now generating enormous amounts of data from their plants and assets. Many of us feel overwhelmed.

From a technology standpoint, we know that the digital twin is a dynamic virtual model of an existing physical asset. It is an up-to-date and accurate copy of the asset, and therefore is fundamental to have real time data attached to 3D model, allowing the digital twin to change in real time along with its physical counterpart. But what is the true value proposition of Digital Twin?

The early adopters of Predictive Analytics Tools and Software might be burning their fingers, but they are setting themselves up for long term success and competitiveness for the long haul. Can your organisation overcome the fear factor of a digital future by scoping correctly and piloting projects to demonstrate value? Does your organisation have a clear business case to invest? Do you understand the impact that Predictive Analytics Tools and Software can have? Does your organisation have the basic foundations in place to enable the digitised future?

Manual work management processes can often be labour intensive and ineffective. Many organisations have adopted systems to digitally capture the information required. These systems are making decisions on how you go about your work to ensure that the right work is done the right way at the right time. A common pain point shared is that before any new tech or continuous improvement programs are even considered, good work management fundamentals need understanding and adherence – identifying work, maintenance planning, reporting, KPI’s, scheduling, work execution, spares management, transitioning from breakdown maintenance, and performance assessment and management.

There are advances all the time in technology that can be scaled to an enterprise level. In some cases, we need to respectfully temper the enthusiasm for the next shiny object and focus on getting bang-for-your buck or solving a pressing business need. Your organisation might have a digital transformation agenda in place, yet it appears apparent that no catalyst has had as big an impact on the speed of adoption as Covid-19. The most successful examples have three things in common. First, there is vision for transformation across the whole organisation that is supported by leadership. Secondly, their initial focus is on two key areas to deploy new tech: predictive maintenance (PdM) and tools to support improvements in work management. Thirdly, they have robust change management programs, and the end users are supported from the beginning.