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“ASSET MANAGEMENT” vs “DATA MANAGEMENT”

“ASSET MANAGEMENT” vs “DATA MANAGEMENT”

Most of the existing, off-the-shelf Asset Management software programs today are not for Asset Management. Even though most of the vendors claim to have AMS software, their programs are actually for Data Management, so their systems are not performance-based AMS and lack the analysis tools and processes to perform planning, programming and budgeting.

What is the difference between the “Data Management” and “Smart Asset Management”?

Data Management is an administrative process that includes acquiring, validating, storing, protecting, and processing required data to ensure the accessibility, reliability and timeliness of the data for its users. Data management cannot use data to translate it into information that can be used by agencies to perform planning, programming and budgeting.

Smart Asset Management is a methodology using analysis tools to proactively manage an organization’s assets so as to meet business and customer needs at the lowest possible cost over the longest period of time. It draws upon knowledge and techniques from engineering, business management, economics and computer/network technology. Ultimately, Smart Asset Management equates to getting the right information to the right people at the right time for better informed decisions and optimum results.

How Does Smart Asset Management Apply to Government Agencies?

Smart Asset Management holds many potential benefits for government agencies. For example, it:

  1. Provides tools for project-, programming- and policy-decision-making;

  2. Provides a framework for short- and long-term planning, programming and financial analysis for infrastructure improvements;

  3. Helps ensure compliance with federal regulations and accounting practices such as those from the Governmental Accounting Standards Board (i.e. GASB 34), it will help agencies generate asset report cards; and,

  4. Helps organizations use their resources to get the best possible results.

Knowledge of Existing Assets is critical to a successful Asset Management Program.

Often, agencies cannot answer the “simple” questions:

  1. What is the condition of an asset?

  2. How is the asset performing?

  3. Are we maintaining an adequate Level of Service for our customers?

  4. What is the most cost-effective rehabilitation solution for an asset?

  5. Where and when should we invest in rehabilitation versus reconstruction?

  6. Where is the greatest need for rehabilitation?

  7. Is the rehabilitation program funding enough to sustain the system and maximize its life?

  8. What is the optimum level of program funding required to maintain the sustainability of our assets?

These questions can only be answered through the development of a sustainable Smart Asset Management System (SAMS).

A SAMS manages the infrastructure inventory data and analyzes the condition and performance parameters, providing key information for the capital and maintenance strategic planning processes.

Many public agencies, as the first step towards good asset stewardship, are starting to manage their assets using some form of asset management system. One of the fundamental requirements for a successful AMS implementation is that it be based on good business practices and that it effectively integrates, or incorporates, the established management systems/practices and engineering analysis.

Smart Asset Management Systems: Asking the Right Questions

Asset management software for government agencies can be expensive, not just to buy but, also, to maintain. To avoid making mistakes now, that will be paid for months or even years later, ask the software vendor the right questions.

The right AMS software will provide the information needed to maximize the performance of assets, control maintenance costs, and improve operations. At the same time, it will monitor asset conditions and ensure necessary maintenance is performed while allowing the organization to perform asset-forecasting, financial analyses, risk assessments and “what if “analyses, determine remaining service life of an asset, and develop short- and long-range roadway improvement plans.

To help make informed software choices, the following important criteria should be asked of every vendor.

You must ask, “Does your asset management system (AMS) have the following tools to allow you to perform planning, programming, budgeting, establish priority, and develop short- and long-range plans?” If yes, ask them to provide practical examples of how their system is performing the following analyses:

  1. Economic analysis - lifecycle analysis (looks at the total cost of an asset over its entire useful life)

  2. Optimization selecting the - most cost-effective maintenance options

  3. Structural evaluation - pavement overlay design

  4. Engineering analysis - alternative evaluation

  5. Performance / LOS evaluation

  6. Investment analysis - “what if” analysis

  7. Financial planning

  8. Asset valuation

  9. Condition evaluation

  10. GAP analysis

  11. Treatment selection models

  12. Develop scheduled maintenance plan

  13. Add-back points - update asset condition as maintenance is performed

  14. Objective Priority

  15. Needs assessment

  16. Failure mode analysis

  17. Risk assessment - mitigation measures

  18. Remaining service life

  19. Deterioration rate - to determine cause of asset failure

  20. Criticality of Assets

The software program should also include the following forecasting tools:

  1. Performance / Level of Service (LOS)

  2. Budget

  3. Condition

  4. Maintenance action

  5. Failure modes

  6. Predict when assets are likely to fail or not deliver required LOS

These analysis models are a must before making the decision to purchase any off-the-shelf software for your organization. With prediction modeling, transportation agencies can:

  1. Forecast current and future budgets and link the recommended repair costs to the agency budget

  2. Develop a multi-year roadway preventive, rehabilitation, and maintenance program that includes priority programming

  3. Perform “what if” analysis based on various budget levels or various levels of pavement repair expenditures

  4. Predict future conditions of network and individual facilities without maintenance and rehabilitation, and estimate future performance resulting from different maintenance and repair strategies

  5. Predict when a defect will start or where a defect will exist

  6. Coordinate maintenance activities

  7. Determine remaining service life and value of assets

  8. Improve decision and support capabilities such as economic optimization of investment alternatives

  9. Determine optimal maintenance strategies for entire facilities

  10. Forecast current and future facility deterioration rates and probability of facility failure

  11. Forecast benefits from each treatment and effectiveness of different treatments

  12. Maximize a limited available budget by using optimization and prioritization models

A critical component of an Asset Management strategy is the use of economic analysis tools to aid in the evaluation of asset maintenance, replacement, and improvement strategies.

Smart Asset Management System (SAMS) Components

SAMS include the following asset management components to support the planning, programming and business requirements of the government agencies. There are four primary components: data collection, analyses, design, and update.

Data Collection Components:

  1. Inventory: physical features;

  2. History: project dates and types of construction, reconstruction, rehabilitation, and preventive maintenance;

  3. Condition survey: asset distress and surface defects and;

  4. Database: compilation of all data files used in the AMS (including project coordination and data integration).

Analyses Components:

Analysis schemes are algorithms and mathematical models used to interpret data in meaningful ways. SAM’s software must combine into one package the database, analysis scheme and decision criteria, including lifecycle cost analysis, optimization algorithms and performance predictions.

  1. Condition analysis: Distress and surface defects.

  2. Performance analysis: Asset performance analysis, risk assessment, optimization and an estimate of remaining service life.

  3. Investment analysis: An estimate of network- and project-level investment strategies. These include single- and multi-year analyses and should consider lifecycle cost evaluation.

  4. Financial analysis: The agency’s asset financial strategy should include lifecycle planning, decision-making, and financial management components. This will allow estimates of total costs to correct present and projected conditions across the network. It will also show expenditures by maintenance type and the funding source.

  5. Decision criteria are rules that must be developed to guide pavement management decisions. As pavement management systems have evolved, decision criteria have become more complex and now account for items such as risk assessment, critical factors and, in limited cases, environmental effects.

  6. Engineering analysis: Evaluation of design, construction, rehabilitation, materials, mix designs, pavement overlay design, and maintenance.

  7. Feedback analysis includes evaluating and updating procedures and calibration of relationships using PMS data and current engineering criteria.

Why SAMS?

A SAMS is not a just software system but is a management organization, a set of procedures and a suite of integrated decision support tools or software systems that, when combined, improve the management process to make structured, systematic decisions about the maintenance, rehabilitation and reconstruction of infrastructure assets. It is important to the Technology Strategy to ensure that data of all forms (infrastructure asset data, performance and diagnostic data, and financial data) are efficiently and reliably integrated and accessible to all who need access.

However, agencies recognize that the world in which it operates is changing and requires strategies different from those that have worked in the past. In response, agencies are planning to transform the way asset management is applied at the agency, with improved business processes that make the most of new technology and a comprehensive knowledge management strategy that will maximize agency capacity and prepare the workforce for the future.

The development of the SAMS advances agencies’ asset management initiatives and prepares the agency to address the changing environment in which it operates. The SAMS must also satisfy new Federal legislation that requires all local governments to prepare a risk-based AMP.

Smart Asset Management is a processing and decision-making framework that uses economic, business, technology and engineering considerations to make cost-effective investment decisions that consider an extended timeframe. The goal of any Asset Management process is to use a system-wide approach to improve operations and make the organization more effective by considering the full investment and lifecycle of assets.

Given the billons of dollars of linear and non-linear assets managed by government agencies, a proactive and informed decision-making process is essential.

The SAMS approach requires rigor and discipline. Any recommendation to invest in an asset must have clear, strategic justification in terms of meeting the agencies’ objectives, and must demonstrate that the recommended option offers strong value for the money.

The need to maximize the benefits of a comprehensive infrastructure preservation program requires that agencies move forward with an advanced asset management system. The need for a Smart Asset Management System (SAMS) is driven by the business requirements to manage the overall asset lifecycle cost, to create a sharable, knowledge base about the agencies’ assets, to maximize the return on the capital invested, and to meet regulatory requirements such as GASB 34.

Sustaining the life of agency infrastructure systems is essential to the wellbeing of the community. This can only be accomplished through cost-effective rehabilitative, preventative and corrective maintenance actions for each asset. A detailed Smart Asset Management plan that ensures the sustainability of those systems must be developed. This plan must consider the condition and performance for each individual asset or group of assets and be able to forecast operating and capital requirements over a multi-year period.

Summary “Existing AMS”:

Most of the Asset Management systems available today do not have the technical capabilities to provide a smart infrastructure asset management system (SAMS) solution that meets the agency’s needs and performs technical analyses. They do have one or two modules, which use subjective information for network-level analysis. Agencies need a SAMS to help them provide a strategic, tactical, and financial plan for project-level planning. To ensure that the management of the agencies’ infrastructure follows sound asset management practices and principles, the system needs to be capable of performing analysis while prioritizing available resources and establishing desired levels of service.

A critical component of an asset management strategy is the use of economic analysis tools to aid in the evaluation of asset maintenance, replacement, and improvement strategies. Most existing systems lack this analysis tool.

Most existing systems are designed for network planning, NOT project-level planning, which means they are not able to do project-level analyses or develop objective and defensible short- and long- range plans. Even for network planning, they make a lot of assumptions and use subjective judgment. They do not have defensible tools to perform the proper system analysis.

Additionally, existing systems do not have the right and objective performance modeling, meaning they are not able to do project forecasting. Prediction modeling can facilitate the development of a successful and cost-effective preventive maintenance plan. These systems use linear prediction modeling, which is not consistent with actual asset performance. Whereas objective prediction modeling provides an accurate prediction of future demand, budgets, asset conditions, and other data needed to plan for improvements and repair. These systems are good for data management, NOT asset maintenance management.

General Discussion

Most existing AMS do not consider all significant factors that affect asset performance, planning programming, budgeting and maintenance for the agency’s infrastructure. AMS should address the unique needs of the agency’s infrastructure. An agency’s AMS must be customized based on the agency’s asset types, performance and budget.

Asset management is more than just a piece of software and/or hardware that can be purchased off-the-shelf. It is a complex combination of spatial inventories and work-management processes. It tracks and analyzes, with a long line of cause and effect outcomes. The use of a successful asset management solution over time (i.e. additional data input, updates, historical recording, etc.) will improve decision-making and reduce the requirements of reactive maintenance of infrastructure, which can save Public Works a lot of money.

Government agencies must implement a Smart Asset Management System (SAMS) that has the above tools, allowing the agencies to establish priority, develop short- and long-range plans, and perform planning, programming, and budgeting.

The right AMS software will provide the information you need to maximize the performance of your assets, control maintenance costs, and improve your operations. At the same time, it will monitor asset conditions and ensure that the necessary maintenance is performed, while allowing your organization to perform planning, programming, budgeting, and develop short- and long-range roadway improvement plans.

In addition to a Smart Pavement Management System, a Smart Asset Management System also requires a robust Maintenance Managements System to keep track of the day to day expenditures used to maintain not only the roads but also the attached structures such as signs, bridges and culverts as well as the scheduling of maintenance work. Detailed information on the cost of labor, material and equipment used to maintain the road network must be kept in order to determine “best practices” based on the performance of the various maintenance approaches. The system should also keep track of the cumulative cost for the various annual maintenance programs and sub-programs or line item items; this information is required to generate complete and accurate GASB 34 reports. An effective and proactive Fleet Maintenance Management System will complete the Smart Asset Management System.

Author: Dr. Ali Roohanirad, P.E.

drroohani@yahoo.com

816-520-9087

Education:

B.S., M.S., Doctor of Engineering: Kansas University 1981

Infrastructure Asset Management System and Transportation Planning

Technical /Managerial Experience: 1981- 2019 Jackson County, MO

Director of Public Works

Traffic Engineer /Transportation Section Head

Maintenance Engineer/ Asset Manager

Publications:

Pavement Management System for local government

Infrastructure Asset Management Manual

Teaching and Research Experience:

Adjunct Professor, University of Missouri, Kansas City Teaching Transportation Related Courses 1997- 2002

  1. Infrastructure Asset Management System, Pavement Design

  2. Traffic Engineering I, Traffic Engineering II

  3. Transportation Planning, Highway Geometrics Design

  4. Infrastructure Asset Management, Pavement Management System

  5. Highway Safety Evaluation

Training Program: Federal Highway Administration (FHWA)

Infrastructure Asset Management System

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