Pieter Bronkhorst, Chief Technology Officer, Hamilton City Council
In today’s hyper-connected, hyper-aware world, enabling the organisational Enterprise Asset Management (EAM) strategic goals through technology is becoming one of the most significant challenges for the CIO.
Enterprise assets form the backbone of all industries and represent a significant part of its investment and spending. The core objectives of Enterprise Asset Management are to optimally manage the asset lifecycle through informed decision making to manage cost, increase return on investments, and accurately predict the lifecycle. The EAM system functionality provides an enterprise view of all assets across the organisation to enable decision making to achieve those objectives.
The EAM systems has been evolving over a number of years into a hyper connected eco system where real-time data is the norm, updated through multiple data sources to enable asset management decision making.
EAM are being disrupted by industry trends that are revolutionising the Asset Management industry. The EAM industry will benefit from improved information decision making and enhanced predictive modelling to gain optimal value from the assets.
Four technology trends that are transforming EAM are:
Drones are becoming the most captivating development in the asset management industry as it provides a cost effective platform that can be deployed into high risk, time sensitive, or inaccessible environments to gather information and feed it back to the EAM system.
The platform allows for the collection of a number of different data sets such as geospatial data and imagery to more complex on-board sensory data. The ability to achieve a bird’s eye view of asset operations has become indispensable to some industry verticals.
Internet of Things (IoT)
The evolution of connected devices and the innovative connectivity solutions that enable them to communicate has brought a range of opportunities for the development of not only new connected asset types, but also retrofitting existing assets.
The EAM industry will benefit from improved information decision making and enhanced predictive modelling to gain optimal value from the assets
The industry has reached the point where IoT and EAM industry intersect. Assets will increasingly be procured with a requirement to be embedded with IoT devices that can be integrated into the EAM system. The expectation of EAM systems are for near-to or real-time connectivity to enrich the asset information available for decision making.
Artificial Intelligence (AI)
The use of AI in the EAM industry is not new as most EAM systems have had a level of predictive modelling as part of its core functionality. The explosion of data available to the EAM system will push the boundaries of what is inherently possible and will necessitate the use of the data handling capabilities that the Cloud AI brings.
The use cases of AI are unlimited with examples such as the ability to present the AI with conversational abilities such as bots, will allow asset managers to converse with the data rather than traditional models and reports. Using AI to monitor and analyse the social media feeds will help identify where assets might be failing or have failed outside of the expected parameters.
Future asset modelling will become richer through the integration of many organisations data which will allow for a broader understanding of the performance of assets across horizontal and vertical industries.
Augmented Reality (AR)
Capabilities to capture imagery in multiple formats and accessibility of 360-degree camera technology has opened up the ability for humans to interact with their assets in ways never seen before. The rapid evolution of Augmented Reality has not just placed asset managers around their assets but also inside the assets, with the future integration of real-time datasets and AR to allow asset managers to see the performance and operation assets.
It is about connecting the data
Connecting the sheer volume of the data generated to the EAM system creates no simple challenge for the CIO in terms of data governance, integration, connectivity, storage growth, and security.
The typical EAM system had its purpose as a monolithic system, but to leverage these disruptive trends requires a rethink of its traditional make up. A cloud enabled EAM system should be considered in context of the many forms of Cloud to determine how it forms part of the solution architecture to enable the EAM outcomes. A cloud enabled EAM system should be capable of leveraging the cloud capabilities such as AI, machine learning, hyper compute power, big data and analytics, large scale storage, data warehouse, IoT management, and other SaaS offerings. Public Cloud, Private Cloud, Hybrid Cloud, and SaaS provide different opportunities and challenges that needs careful consideration.
Key areas that require consideration for a cloud enabled EAM system are: Security, Infrastructure Capacity Planning, Connectivity and latency, Information Classification, Privacy, Financials – Capex to Opex shift and Consumption Models, and People change impacts.
The opportunity for the CIO to enable a hyper-aware, hyper-connected EAM system lies in the ability to lead the selection of the most appropriate technologies to connect the data.