Guidebook for Advanced Computerized Maintenance Management System Integration at Airports (2018)

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Question Category CMMS Integration Airports Non-Airport PANYNJ SEA SLC MKE YYZ GCDWR Is CMMS integrated with any of the following systems? Resource management • • • Security • Safety management • • • Automatic vehicle identification Wildlife hazard management plan • • • Payroll • Pavement management • • • Scheduling • • • Electronic log books • Incident management • • • Fleet management • • • Human resources • Building management • Time and labor software • • • Property management • • • Fueling • • • • Airfield lighting • • • Storeroom • • • Geographic information • • • Inspection application (FAA Part 139) • • • Financial software • • • Elevators and escalators • • Baggage handling system • • • Fire protection • • Asset health analytics • Table 4-4. Case studies: CMMS integration comparison (shaded cells indicate planned/future implementation).

Question Category Decision Making Airports Non-Airport PANYNJ SEA SLC MKE YYZ GCDWR Which of the following reports do you produce? What type of data is in the report? Work order priority analysis • • • Planner performance • • Scheduling activities • • • Inventory • • • • • Procurement • • Supervisor work order performance • • Supervisor/skill work order performance • • Work order costs report • • • • Completed work order performance • • • • • • Work order backlog summary • • • • Asset repair history • • • • Asset maintenance costs repair • • • • • Asset maintenance cost exception • Safety work order backlog • • • • Stock item usage report • • • • Work order waiting report • • • • • • Preventive maintenance • • • • • Preventive maintenance overdue report • • • • • Table 4-5. Case studies: CMMS decision-making comparison (shaded cells indicate planned/future implementation).

46 This chapter provides guidance to airport CMMS developers, integrators, and users that will improve their ability to implement and manage the CMMS as it relates to and supports a per- formance management program, and thereby improves data-based decision making. The chapter includes information on basic performance management principles, but it is not intended as instruc- tion for developing a performance management program. Readers can refer to ACRP Report 19: Developing an Airport Performance-Measurement System for information related to developing a performance management program (Infrastructure Management Group, Inc., et al. 2010). This material also is intended to supplement and support ACRP Report 19A: Resource Guide to Airport Performance Indicators (Hazel et al. 2011). ACRP Report 19A presents the results of an extensive research project conducted to identify a set of KPIs found to be most effective and used across the airport industry. A CMMS usually includes some level of KPI tracking and reporting, which can be valuable to understanding the maintenance organization’s performance. This chapter presents an overview of ACRP Report 19A sufficient to provide basic understanding of how and why KPIs are devel- oped, the types of KPIs available, and the information sources that support KPI development and integration into business decision making. The chapter also provides guidance on how to use the ACRP Report 19A information with a CMMS to provide accurate data for performance tracking to inform capital and operational business decisions. It is important to highlight that, although much information is available from a CMMS, it typically is not the only data source supporting the performance management system. The chapter also outlines the steps necessary for development of a performance manage- ment program, including developing a performance management strategy, developing a KPI model, setting up the CMMS to support performance management, leveraging the CMMS data to inform decision making, and communicating KPI analysis and results to decision makers. Overview of ACRP Report 19A: Resource Guide to Airport Performance Indicators Under ACRP Report 19A, Hazel et al. (2011) reviewed literature related to airport perfor- mance measures; reached out to trade associations, government agencies, and other experts in the field; and conducted two workshops to solicit industry views on airport performance indicators (APIs). Through this process, the researchers developed an extensive list of APIs that can be used in an airport performance measurement system. To assist airport practitioners in selecting the APIs that are most appropriate for their particular airport functional interest, each API listing presents and defines each API, suggests methods for C H A P T E R 5 CMMS Integration into Business Decision Making

CMMS Integration into Business Decision Making 47 collecting relevant data, and, generally, supports the implementation of an airport’s performance measurement system. The report provides a list of 840 APIs grouped into categories labeled “Core,” “Key,” and “Other.” Figure 5-1 shows the number of APIs in each category. Their details are as follows: • Core APIs (29). These strategic APIs are important for airport overall operation or otherwise important at the airport executive level (chief executive officer and aviation director) and/or the airport’s governing board. • Key APIs (132). These strategic and tactical APIs are important for the operations of key air- port departments or functions (e.g., finance and maintenance). • Other APIs (679). Not considered as useful for overall airport operation, to the executive level, or to key airport departments/functions, these tactical APIs can be useful as secondary departmental unit APIs at or below the manager level. Few, if any, airports have the need, the resources, or the data to track and report on 840 indi- vidual APIs. Even among airports with similar characteristics, managers will have different views on which APIs are most important, and over time these views are likely to change as new issues and challenges arise. Based on the results reported in ACRP Report 19A, airports should use between 6 and 20 Core APIs. Accordingly, an organization needs to fully understand its mission, goals, and business objectives as it evaluates its performance measuring options and builds a realistic, sustainable performance model. A subset of the APIs identified in ACRP Report 19A will require data that are typically stored within a CMMS. Identifying which APIs can be supported by the CMMS is covered in this chapter in the section titled “Setting up CMMS to Support Performance Management.” Figure 5-1. Breakdown of airport performance indicator categories.

48 Guidebook for Advanced Computerized Maintenance Management System Integration at Airports Leveraging CMMS Data to Inform Decision Making The potential volume of information and data that can be contained within a CMMS can be both powerful and intimidating. Airports implementing or upgrading a CMMS may be tempted to include most or all available data, reasoning that if the data is not included in the CMMS, it cannot be used for analysis, and therefore cannot be used to inform decision making for risk-based, data-driven decisions. As was discussed in Chapter 3 of this guidebook, however, the CMMS should be designed with the end in mind, including making decisions about which assets, data, and information to include. To leverage the CMMS information for improved decision making, the data requirements must be mapped from the decision-making process back to the CMMS. Given that most busi- ness decisions are (or should be) actively informed from a performance management system, it makes sense that if the CMMS has been configured to support the data requirements of the performance management system, it will support the decision-making process. In addition to supporting the performance management system, the CMMS data provides value to other analysis processes associated with conducting FMEA, RCM, etc. A CMMS user or integrator addressing the data requirements of the CMMS should begin the process with establishment of a performance management model to include the performance mea- sure calculation and data sources shown in Figures 5-1 and 5-2. Figure 5-1 presents a list of initial maintenance and reliability program performance measures selected for tracking and reporting by a maintenance department, and Figure 5-2 presents a list of future potential performance measures the maintenance department might be interested in tracking. It is important to consider likely future performance measures so that the data being collected today will support the needs of the future performance management model. It also should be remembered that the data that feeds the performance management system will usually come from multiple sources, including the CMMS. Some short-term performance measures are: • Assets missing PM plans and/or job plans • Total assets with spare parts indicated • Total assets missing spare parts • Mean time from failure report to correction • Planned work orders to unplanned (PM to CM ratio) • Work Order backlog (critical versus non-critical assets; assumes organization has classified assets by consequence of failure) Some mid-term performance measures are: • Asset re-work work orders • Asset failures (bad actors) • Mean time between failures • Warehouse turns by part/asset classification • Warehouse material valuation • Work order placed on hold due to waiting materials Some long-term performance measures are: • Craft utilization (time associated with work order versus non-wrench time) • Craft training time • Labor hours planned versus actuals • Part utilization, planned versus actuals • Maintenance costs, planned versus actuals • Internal maintenance costs versus vendor maintenance costs

CMMS Integration into Business Decision Making 49 The information presented in Figures 5-4 and 5-5 includes the calculation and data sources for each performance measure. As indicated by the shaded panels, a CMMS is a major source of information for this maintenance and reliability performance management model. Prioritizing the population and management of CMMS data is critical for improving busi- ness decision making. By understanding the needs of the performance management system, the CMMS administrator can identify which CMMS data will be used for decision making, which information needs to be of high quality, and what information might be required in the future. Developing a Performance Management Strategy Use of performance measures is growing in one form or another in most airports in the United States and internationally. Often called benchmarking, or simply as financial and opera- tional data, performance measures are being put in place and used in the daily operations of airports of all sizes. From GA to large hub airports, the need for and relevance of performance monitoring has been manifested. Most commonly, financial and operational data are tracked due to FAA requirements (Infrastructure Management Group et al. 2010). At a minimum, effective performance measurement programs do the following: • Measure only areas that fall inside the airport’s mission area • Measure activities, products, services, and outcomes that move the airport toward its strategic goals • Measure areas that have been identified as environmental, business, structural, or other barriers to success • Involve an inclusive set of short- and long-term, leading and lagging, and operationally diverse measures • Inform management decisions by linking strategic planning to budgeting, resource planning, and other areas of managerial importance The purpose of a performance management system is to provide an organization with the tools it needs to measure performance in various categories at a strategic level and a tactical level. In general, the strategic level performance measures gauge performance against the stated organizational goals, and the tactical level performance measures measure performance of ini- tiative objectives. An organization’s selection of performance measures depends on the organization’s goals and objectives, as well as the organizational structure, the programs that are in place, and the availability of accurate data/information. In accordance with ACRP Report 19A the main characteristics of a well-defined performance measurement system are the following: • Organizational performance measures are gathered and displayed in a system or systems • Performance measures are designed to ensure that past practices are analyzed, and that lessons are learned from prior decisions • Performance measures are used to gauge whether current actions are moving the organization toward a desired future state • The organization may use performance measures from a largely reactive and tactical perspec- tive, but the long-term goal is for more proactive, strategic use • The organization consciously uses data to challenge management decisions, pre-conceived notions, and past practices • The organization combines quantitative information and qualitative information to provide accurate and rich interpretations of organizational activities, outputs, and outcomes

50 Guidebook for Advanced Computerized Maintenance Management System Integration at Airports A performance management strategy begins with establishing a clear airport mission, estab- lishing goals that will work to accomplish the mission, defining objectives that support reach- ing the goals, and developing an action plan that will ensure the strategy is transformed into performance improvement. Mission Statement A performance management system should be built on a clear airport mission. Airports generally develop mission statements based on their enabling laws and rules. According to the National State Auditors Association (2004), the airport should ensure that those mission statements: • Identify who the entity is and what it does • Identify why the things the entity does are important • Make sense to the average stakeholder • Enable the stakeholder to understand why public dollars are being spent on these efforts Goals Goals describe the results desired to be realized as the airport successfully implements vari- ous improvement initiatives. Goals can be thought of as quantitative descriptors for each leg of an airport’s journey to its destination, whereas the mission describes more broadly the “why and how” of the journey. In addition to supporting the mission, each goal should: • Represent a desired, measurable result • Be realistic and achievable • Make sense to others outside the airport Objectives Objectives represent management’s commitment to achieving specified results and spell out the quantity and quality of performance to be achieved in a specified period of time. Objectives are individual targets for the performance improvement initiatives that will move the airport closer to a goal and to its ultimate destination. Action Plan The action plan is a documented series of tactical activities that, when executed, implement the performance management strategy and, when successfully implemented, ensure that the organization eventually meets its mission. The performance measures and standards develop- ment should be part of the action plan. A CMMS is a key source of quantitative data that can support the development and tracking of performance measures. Therefore, the action plan will work to identify various CMMS data required to meet the intent of the performance management strategy. If the team implementing or upgrading the CMMS is not aware of the needs of the performance man- agement system, the quantity and accuracy of the resulting CMMS data may be inadequate to support the desired level of performance measurement. As with any data intensive analy- sis, a performance management system requires multiple years of accurate data in order to establish baselines and trends against those baseline measurements. Because perfor- mance improvement actions are based on the analysis of the data, bad data only produces bad decisions.

CMMS Integration into Business Decision Making 51 To ensure that the right data is collected and the quality of the data is sound, four basic con- cepts need to be applied: 1. When establishing the data requirements for the CMMS, consider the needs of the perfor- mance management system. If a performance management system is not in place, use guidance provided in this report to ensure that the appropriate data is being documented within the CMMS to support future efforts. 2. Consider the CMMS data needs of the entire airport, including financial, safety, environ- mental, production, maintenance, human resources, payroll, asset performance, and asset management performance. 3. Create asset documentation and formal work management processes that will encourage the consistent and accurate documentation of asset and work execution information. 4. Train airport staff and management on the importance of the CMMS data for effective decision making throughout the organization. Development of a Performance Measurement Model The development of a performance management model includes creating the mission state- ment, defining the goals that support that mission, and identifying the lower level objectives that will drive the organization and departments to meet its goals. As illustrated in Figure 5-2, tactical measures can provide input to multiple strategic mea- sures. A key opportunity when building a performance management model is to limit the num- ber of tactical measures to the fewest that will provide an accurate measurement of performance. Doing this limits the amount of work for collecting and entering the data, analyzing the data, and reporting the outcomes. Composition of a Performance Measurement Model A performance measurement model is constructed as a cascading structure in which overall performance is presented at the top of the model with the performance of supporting activi- ties nested below. Several model structures can be considered, with many consistent in using a cascading architecture. A common presentation of performance measurement is the pyramid, as shown in Figure 5-3. The Guide to Airport Performance Measures provides the following guidance for establishing performance areas in an airport (ACI 2012): • Core. These are the core measures used to characterize and categorize airports, such as the number of passengers and operations. Although airports may have little control over these core indicators, especially in the short term, they are important indicators of overall airport activity, and important drivers and components of other indicators. • Safety and security. These are the most important airport responsibilities, and therefore they are categorized separately. • Service quality. This increasingly important area reflects the evolution of airport manage- ment from having a primary focus on facilities and operations to having a strong customer service focus in an increasingly competitive environment. Service quality includes the way in which asset performance delivers comfort for airport customers through provision of water, cooling, heating, sanitation, and other infrastructure services. • Productivity/efficiency. These measures are closely related/overlapping measures of an air- port’s performance. They are sometimes separated into productivity measures, which track output on a non-cost basis (e.g., passengers per airport employee or departures per gate)

Figure 5-2. Airport performance measurement model. Figure 5-3. Performance measurement pyramid.

CMMS Integration into Business Decision Making 53 and efficiency measures, which track output on a cost basis (e.g., total or operating cost per passenger). Productivity/efficiency includes asset management performance, as defined in Clause 9.1 of ISO 55001. • Financial/commercial. This includes measures relating to airport charges, airport financial strength and sustainability, and the performance of individual commercial functions. • Environmental. This evolving area has become a strong focus for airport managements striving to minimize environmental impacts. Characteristics of a Good Performance Measure As mentioned previously, an effective performance management model will contain the mini- mal number of measures needed to provide the necessary level of information to manage per- formance. In turn, each measure should meet the following SMART criteria to be considered an effective measure (McNeeney 2005): • Specific. The measure is clear and focused to avoid misinterpretation. • Measurable. It can be quantified and compared to other data. • Attainable. It is achievable, reasonable, and credible under conditions expected. • Realistic. The measure fits into the organization’s constraints and is cost effective. • Timely. It can be achieved within the given time-frame. Performance Measurement Categories Categories of performance are as follows (Governmental Accounting Standards Board 1990): • Input. Input shows the amount of resources, either financial or otherwise, used for a spe- cific service or program. Input measures include labor, materials, equipment, and supplies. Demand for governmental services may also be considered an input indicator. • Output. Output shows units produced or services provided by a service or program. Output measures include the amount of products or services provided, the number of customers served, and the level of activity to provide services. • Outcomes. Outcomes show the results of the services provided. Outcome measures assess program impact and effectiveness and show whether expected results are achieved. • Efficiency. Efficiency reflects the cost per unit of output or outcome. • Quality. Quality shows the effectiveness in meeting the expectations of customers, stakeholders, and other groups. Quality indicators show the quality of the services delivered. Setting Up CMMS to Support Performance Management A CMMS provides functionality to track physical assets, spare parts, and the transactional activities associated with both O&M of those assets. Within the execution of these functions, the sys- tem acts as both a work management tool and a data analysis tool. Most CMMS users focus on using the work management functionality, with little appreciation for whether data is being documented within the system, or being documented at all. As a result, the full value of a CMMS is not realized. To leverage the CMMS data for improving performance, the necessary data should be acces- sible and accurate. Given that the options for data fields in a CMMS are endless, the CMMS user must clearly understand which fields are important and which are not. If a current perfor- mance management structure is in place, the performance measure requirements should dictate which CMMS fields should be populated and maintained accurately to support the program. If a performance management system is not in place, the CMMS user can use some of the metrics shown in Figure 5-4 to get started.

Performance Metric Performance Target Calculation Data1/Source Data2/Source Data3/Source Data4/Source Total Annual Maintenance Costs / RAV 3% $Labor + $Material + $Contractor / RAV Maintenance Labor Cost CMMS Material Cost CMMS Contractor Cost CMMS Replacement Asset Value (RAV) % Inventory Value / RAV 1% Inventory Holding Value / Replacement Asset Value x 100 Value of stock Held in Inventory CMMS Replacement Asset Value Plant Critical Equipment Availability 97% Total Targeted Production Time - (unscheduled unavailability + scheduled unavailability hours)/ Total Targeted Production Time x 100 Targeted Production Time (99.5%?) Unscheduled unavailability Scheduled unavailability Normalized Mean Time Between Failure (nMTBF) NA - Increasing Trend Total Operating Time (for population) / Number of failure events (for population) Total Operating Time for population Number of Failures for population CMMS % Proactive labor hours vs total labor hours (Proactive + Reactive) 80% ((PM hrs + PdM hrs + PMR hrs + PdMR hrs) / Total Hours) x 100 (PM hrs + PdM hrs + PMR hrs + PdMR hrs) CMMS Total Proactive and Reactive Hours CMMS (proactive + reactive) % Schedule Success 90% Count of scheduled Labor Hrs Completed / Total scheduled Hrs x 100 Total Scheduled Hrs Complete CMMS Total Scheduled Hrs CMMS % PdM Inspection labor hours vs total labor hours (PdM + PM + PdMR + PMR+ Reactive) 15% PdM hrs / Total Hours PdM hrs CMMS Total Proactive and Reactive Hours CMMS (proactive + reactive) Total Maintenance Costs / MGD NA - Trend $Labor + $Material + $Contractor / MGD Maintenance Labor Cost CMMS Material Cost CMMS Contractor Cost CMMS Production in MGD Maintenance Contractor Costs / MGD (6 Month delay in reporting) NA - Trend $Maintenance Contractor Costs / MGD Contractor Cost CMMS % Total Compliance Annual - Maintenance 100% Total Compliance Commitments Completed/ Total Compliance Commitments for calendar year Total Compliance Commitments Completed CMMS Total Compliance Commitments CMMS % of Emergency & Urgent Labor Hours vs Total Labor Hrs (All Priority) Downward trend (If % of total -Less than 7.5%) Total Emergency Labor Hours (Order Priority "X") / Total Labor Hours x 100 Total Actual Hours on WOs with Priority X / CMMS Total Actual Hours on WOs / CMMS Avg Mean Time To Repair MTTR Decreasing Trend Sum of Time to Repair per Work Order / Total Work Orders Time to Repair per WO CMMS Total Work Orders CMMS % PM Hours by Operations NA-Trend PM Hours OPS / PM Hours Total x 100 PM Hours OPS CMMS PM Hours Total CMMS Avg time from Purchase Request to Material Receipt NA-Trend Material Receipt Date - Purchase Request Date Material Receipt Date Purchase Request Date Number of Stock Outs for critical equipment maintenance <2% Number of times a critical spare is needed but not in stock / number of times critical spare is needed x 100 Number of times a critical spare is needed but not in stock CMMS Number of times critical spare is needed CMMS % Hrs for Skills Training 2 - 3% (40 hrs per employee per year) Count of Hours of Maintenance Skills Training / Total Available Working Hours x 100 Hours of Maintenance Skills Training CMMS Total Available Labor Hours % of Compliance Related Calibrations Completed YTD 100% YTD Compliance PM Calibrations Completed / Total Count of Compliance PM Calibrations For Year YTD Compliance PM Calibrations Completed CMMS Total Count of Compliance PM Calibrations Scheduled For Year CMMS % of Compliance Related Inspections Completed YTD 100% YTD Compliance PM Inspections Completed / Total Count of Compliance PM Inspections For Year YTD Compliance PM Inspections Completed CMMS Total Count of Compliance PM Inspections Scheduled For Year CMMS % YTD Maintenance Spend / Maintenance Budget 95% - 105% YTD Maintenance Spend / Annual Maintenance Budget x 100 YTD Maintenance Spend CMMS Maint.Budget Average Response time to Operations request by WO Priority Need to establish - Trend AVG (WO Start Date & Time - Customer Request Date & Time) WO Start Date & Time CMMS Customer Request Date & Time CMMS (If provided with work request or pushed to CMMS) % Planned Work orders vs Total Wos (Planned + Unplanned) 95% Planned & Sched WOs / Total WOs x 100 Planned & Sched WOs CMMS Total WOs CMMS Work Backlog (crew weeks) 4 - 6 weeks Total Backlog Labor Hours / Total Available Crew Hours per Week Total Backlog Hours CMMS Total Available Crew Hours per Week CALCULATED On Time PM Comp. Rate 95% Count of PM WOs completed on or before due date / Total PM WOs Scheduled x 100 Total PM WOs with status "complete" and complete date equal to or less than due date CMMS Total PM WOs scheduled CMMS Figure 5-4. Initial maintenance and reliability metrics model spreadsheet.