Asset Information and Asset Intelligence Consultancy

Situation

Companies that manage physical assets have large quantities of less than perfect data that they need to manage, enhance and utilise to make decisions about what should happen to the assets. This is in part an information management task and part a business intelligence task. Overall this represents an asset intelligence task.

All aspects of information management need to be brought to bear on the organisation's data. Often the data is in a fairly uncontrolled state and needs stabilisation before major change can take place. Areas that ultimately need to be addressed often include:

• Data quality and cleansing
• Data structure
• Data integration with business processes
• Data systems
• Data governance
• Data measurement and KPIs
• Culture and behaviour

Business intelligence is key to extracting value from the large quantities of asset data that are available in a physical asset management organisation. All standard kinds of business intelligence are relevant to asset management companies, but there are also some tools and techniques that are specific to them. Standard business intelligence techniques include reporting, data warehousing, statistical analysis and forecasting. More advanced techniques include data mining, simulation and optimisation. Some techniques more specific to asset management companies include "smart" signal analysis, geospatial analysis and deterioration modelling.

Through integrating the work on information management and business intelligence to get the business data, it's management and it's use fully aligned, it is possible to support business decision making more effectively and add significant value to the business through reducing capital and operational costs, reducing risk, increasing customer service and justifying business decisions with regulators and other stakeholders.

Solutions

Using its experience from a wide range of physical asset management companies and more generally with information management and business intelligence in other industries, Optadian works with clients to develop a strategy for transforming their asset information and asset intelligence together with a plan for implementation and then works with them to deliver the changes.

The following diagram shows an example output from previous asset intelligence work used to shape an asset intelligence strategy showing the scope of asset intelligence within a particular organisation.

Example Credentials

Optadian has worked with a range of clients, supporting them with asset information and asset intelligence. This work has been both strategic and delivery-based, often both.

European National Transmission and Distribution Water Utility

Optadian worked with the Asset Management leadership and their managers to explore the key issues, challenges and opportunities that the organisation faced with Asset Intelligence and determine a philosophy for how they wanted their organisation to develop in this area. Optadian developed a framework for all elements of asset intelligence relevant to the client and used this to explore through a series of workshops the approach that should be taken in each area.

Based on the workshops, external input and further analysis a series of outputs were developed and verified with the Asset Management leadership. These included:

• Asset Intelligence Philosophy - A view of what asset intelligence is, why it's important and how it will enable improved business performance
• Asset Intelligence As-is Assessment - An assessment of the data, systems, tools, processes, organisation and culture that underpin asset intelligence and comparison with best practice
• Asset Intelligence Capability Framework - A framework that graphically details all of the people, process, data and technological aspects of asset intelligence, explains what each does and demonstrates how they all fit together
• Asset Management Data Requirements - A value-prioritised view of the data required by Asset Management that needs to be provided through Asset Intelligence
• Asset Intelligence Strategy - Outlines the approach for implementing an Asset Intelligence capability within the client including a "day-in-the-life" view of how improved asset intelligence would actually work in practice
• Asset Intelligence Capability Design - Details all of the capabilities, their nature and extent and how they will be implemented, set against the Asset Intelligence Capability Framework
• Data Governance Approach - Details the data governance that should be implemented to support Asset Intelligence, including organisation, processes and data ownership
• Asset Intelligence Organisation Structure - Support for the development of the new organisation structure and definition of the roles for Asset Intelligence staff
• Asset Intelligence Budget and Benefits Case - Numerical analysis of the costs and benefits of implementing the proposed asset intelligence
• Asset Intelligence Transition Plan - A detailed transition plan specifying the sequence of activities, integrated with other concurrent change programmes,  required to implement Asset Intelligence

Both the outputs and also the process of developing them with the client and the knowledge transfer that this involved, enabled the client to develop all aspects of their Asset Intelligence capability successfully.