| Items | Firefighting | Stablising | Preventing | Optimising | Excellence |
| Information Requirements | Asset management information needs and relevant data sets have not been identified. |
Information requirements are based on intuition and what is available: • Reports are generic and standard, with little customisation. • Reports requirements are based on day to day operational activities. • Reports and source data are often duplicated. |
Information requirements are based on a formal needs analysis: • These requirements are linked to the AM Scorecard of selected KPIs. • Input data and sources are defined. • The report format, target audience, frequency, responsibilities and development needs have been defined. • The main focus is on measurement and reporting. |
Information requirements have been refined and optimised: • The information flow is mapped and streamlined to increase data velocity. • Aligned with AM KPIs on all levels (strategic, tactical and operational). • Cross-departmental interfaces in information flow are identified. • The main focus is on analysis and problem solving. |
Information requirements have been projected for the next 2 - 3 years: • AM Strategy determines future information requirements. • All stakeholders are involved in the requirement analysis. • Software and hardware purchases are aligned with the AM Strategy. • The main focus is on real-time information |
| Information Systems | No structured asset management information systems are in place. Information is fragmented and processed manually, limiting its value to individuals. |
Information systems are informal and spread across different platforms: • Some managers use spreadsheets for analysis or control. • The ERP or accounting system is used for financial reporting. • Manual systems are used for work planning and control. • Plans exist to implement an EAMS. |
A formal CMMS or partial EAMS is used, but it is a stand-alone system: • It controls maintenance work. • Maintenance, financial and material management information is available. • Systems are not integrated and some reports are difficult to generate. • Access is limited to a few users. • Users are very dependent on the IT Department for support. |
A full EAMS is used, with partial integration with other systems: • All information needs are satisfied. • A large % of the system functionality is being used, according to needs. • Data duplication is eliminated. • Most people involved in AM have access to the EAMS. • System security and database back-ups are in place. |
The EAMS is streamlined and fully integrated with relevant systems: • Database structures are optimised for single point data entry. • Operational staff can develop their own report queries. • The EAMS is used during daily AM tasks. • SCADA provides asset performance or condition data directly to the EAMS. • Cross-system reporting is possible. |
| Data Quality and Accuracy | Data quality is generally very poor, cannot be measured, and is open to interpretation and debate. |
The accuracy and quality of data vary depending on individuals: • There are pockets of excellence. • Data accuracy is only assessed on request, e.g. during external audits. • Some over inspections are used to check the quality of work feedback and operational data. |
Data quality and accuracy are measured and managed reactively: • Managers do spot checks to emphasise the importance of data quality. • Evidence exists that data quality and accuracy problem areas are addressed. • Data quality is still suspect as the systems are new and skill levels are low. |
A formal process is in place to ensure data accuracy and quality: • Statistical samples of data are used to verify and calculate data quality. • The results are recorded as a KPI and discussed during team meetings. • The engagement of front line workers results in more accurate source data. |
The EAMS ensures data quality and accuracy pro-actively: • Data accuracy is checked at data entry (where possible). • Data capturing is automated (e.g. Barcode scanners) to avoid human error. • Data and information verification tests are built into the EAMS. |
| Data Velocity | Data is not processed electronically. People use manual records for decision making regarding assets. |
Data is processed in stand-alone systems (e.g. spreadsheets): • Data processing requires heavy user involvement with little automation. • Data is only processed when it is required for meetings or at month-end. • Data velocity is slow and information is out of date. |
The CMMS or partial EAMS has improved data velocity: • Some data processing is automated and less dependent on user interaction. • A data processing procedure is in place. • Users have been trained to use the system effectively. • Data is captured and processed at least once a week. |
Information is available from the EAMS directly after data is captured: • Artisans enter Work Order feedback directly into the EAMS. • Material management transactions are captured online. • Data is processed within 24 hours or in line with requirements. |
The EAMS uses technology to provide real-time information: • The EAMS is integrated with asset performance and/or condition monitoring systems to import data automatically. • Technology (e.g. barcode scanners) are used to reduce data capturing time. • Workflow tools are used to automate information flow. |
| Data Mining Capability | Data mining is not possible with the existing information systems. |
Data mining is difficult and time consuming: • Information systems are fragmented with separate databases. • Data is largely used for record keeping and limited reporting. • High computer literacy is required for data mining. • Data is captured with limited detail. |
The CMMS or partial EAMS enables some data mining, but it is not used often: • Data mining is difficult because of the use of different systems. • Only a few experts have the required reporting and analytical skills. • Pareto analysis and different trend graphs are mostly used for analysis. • The focus is on reporting, not analysis. |
The integrated EAMS allows more rigorous data mining: • Drill down reports can access data from different information systems. • Key users are trained to mine data and/or develop user-defined reports. • Database structures are visible for drill down or user-defined reports. • The focus is on root cause analysis and problem solving. |
Data mining is a standard practice in asset management: • Data mining is used to investigate what-if scenarios. • Data mining is partially automated via a parameter selection on reports. • Most EAMS users can use the data mining functionality. • Data mining is being expanded according to user requirements. |
| Reporting | Asset management reports are totally inadequate compared to the stated information requirements. |
Reporting functionality is limited and there is no analytical capability. • A few fixed standard reports exist. • Custom reports can only be generated on request by IT experts. |
A reporting capability exists for trended graphs with limited analysis: • Reports show general trends and events accurately, but they are limited in depth. • The system has standard reports and greater flexibility for generating custom reports. |
An effective reporting capability exists to satisfy all AM information needs: • All staff can use the system for data processing and reporting. • Reports can access data from different systems. • Reports can be customised as needed. |
Web-based dashboards provide real-time information: • Key information is displayed in the workplace. • Reports can be customised by front line users. |