Asset Data Management System – A White Paper for Discussion
The Data Special Interest Group has developed an Asset Data Management System Model for discussion by the AM Council membership. Take a look at the details here.
Feedback Sought on the Asset Data Management System Model White Paper
Julian Watts is the AMCouncil National Lead for the Data Asset Special Interest Group (DiAM SIG) and would like to receive feedback on the white paper via email and is interested in finding out your response to the following questions:
Asset-intensive industries continually strive to improve profitability while at the same time reducing business risk and expenditure. Today’s financial climate and market competition require organisations to improve productivity and asset performance with less resources and capital. A recent study indicated that around 47% of organisations associated the inability to achieve asset management goals with the ‘lack of visibility into actual asset condition and performances’. To read the rest of the article co-written by Mustapha El Hayek and Ian Gordon from Meridium, please visit 
Discover how an Australian utilities company used big data-driven insights to optimise lifecycle planning, budgeting and strategic management. The solution was easy to use and easy to understand, enabling the organisation to proactively identify problematic or costly assets prior to asset failure and to use predicted future costs to inform annual maintenance activity. Discover how the intelligent allocation of limited resources and the accurate forecasting of future asset costs provide huge benefits.
Today’s tough financial climate and market competition requires organisations to improve their productivity and asset performance with less resources and capital. Discover how Asset Performance Management (APM) strives to use the increasingly large amounts of data to help asset management professionals make better decisions for their businesses.
Big Data is a hot topic – there’s an increasing trend to focus on the value that data analytics can bring to business. But despite the buzz, there is very little attention being paid to the quality of all this data. Discover just how important quality is when it comes to your data and learn about a simple four step solution to improving data quality.