Since the ushering in of enterprise-wide technology systems almost three decades ago, there have been numerous highly publicized failures. Disconnect between strategy and execution. Unclear scope and unrealistic expectations. Inadequate performance testing and change management. Massive budget and schedule overruns. And when the implementation was eventually “finished” many years later, companies were left with incomplete systems, operational instability, or even worse, total system rejection. So how can organizations succeed with a major technology implementation today when others have failed before? By employing a data transformation strategy and plan.
An Enterprise Asset Management (EAM) system allows organizations to address the complete life cycle management of their assets: from capital planning to procurement, installation, operations, compliance reporting, maintenance, repair, and ultimately decommissioning. But just like any large-scale technology transformation, EAM system implementations must be carefully planned, managed, executed, and measured for organizations to fully achieve their intended results.
For companies in the early discovery stages or those having already decided to transform their asset management function through a new EAM system implementation, the first step is to develop a strategic approach for how the initiative will be accomplished and how its success will be measured post-implementation. Once that has been completed, the next step is to align and validate the organization’s existing data, before confirming which data will be transferred to the new system. The figure below provides a simplistic overview of these steps separated into three (3) distinct phases, with the fourth phase being the system implementation.
Let us discuss each of these three (3) phases in more detail.
Phase 1: Transformation Readiness Assessment
A Transformation Readiness Assessment establishes the ability of each site within the organization to change and estimates the change effort required. This entails obtaining the current-state asset data registers from the company locations to be transformed (typically through a formal extraction process) and in conjunction with site interviews and/or workshops, designing logical and cohesive future-state asset data register attributes. The transformation effort required of each company location is assessed based on operational factors such as readiness of the site for cultural and operational practice change, and the quality of the site’s existing data (both completeness and accuracy). For example, certain sites may have leadership supportive of a new system, while others may not be as willing to change. Some sites may already have an established EAM system in place, while others may be relying entirely on a paper-based approach. Certain sites may already have a comprehensive and accurate inventory of asset data in their register, while others may not be fully aware of what their asset data register encompasses.
In addition to the transformation readiness of each site being assessed, the organization’s Inspection, Testing, and Maintenance (ITM) procedures should be reviewed and compared against current industry best practices. The most common way to accomplish this is to perform a gap analysis against industry codes, standards, and/or specifications for executing regulatory and non-regulatory maintenance work. Consideration should be given to national, state, and local requirements in addition to industry trade groups and/or generally recognized industry associations.
The resulting output from the Transformation Readiness Assessment will provide information on which sites will (and will not) likely be supportive of future change, which do (and do not) already have established operations and maintenance practices in place, and which will (and will not) need help confirming and updating their existing asset data. This information can then be used to help guide the Data Transformation Plan in Phase 2.
Phase 2: Data Transformation Plan
A Data Transformation Plan is the approach by which to execute the EAM system implementation strategy. This begins with developing a Site Transformation Roadmap by determining which of the existing site asset data registers can simply be converted to the new EAM system format while which sites need an entirely new asset data register developed.
For those sites that currently possess reliable asset data and where the existing asset register can be converted, the process is relatively straightforward. But for those sites that do not possess reliable asset data and/or a consistent asset file naming nomenclature in their existing EAMs, an asset data collection and validation plan will need to be developed. The Site Transformation Roadmap should encompass an explanation of sites where existing asset registers will be converted and those sites where the development of new asset registers will be required, including the steps required for asset data collection and validation.
The Site Transformation Roadmap, however, comprises only one component of the Data Transformation Plan, with the Data Transformation Roadmap being the other. The Data Transformation Roadmap should include the metrics and Key Performance Indicators (KPIs) that will need to be introduced to measure the effectiveness of the resulting transformation efforts, post-implementation. As these will help define and measure the success of the overall effort, they must be appropriately determined through careful consideration of proprietary enterprise operations and maintenance benchmarks, targets, and objectives.
Phase 3: Data Alignment, Validation, and Upload
Once the organization has developed and agreed upon a Data Transformation Plan, the next step is to align the data into a format that can be uploaded to the new EAM system.
Data Alignment and Validation includes personalizing, confirming, and validating the new asset data registers at each of the company locations. This encompasses extracting the asset data, analyzing the data, cleaning the data (i.e., ensuring its completeness), validating the data (i.e., ensuring its accuracy), and preparing the data for upload through the development of standardized EAM system templates.
Data Alignment and Validation also includes reconciling the ITM procedures and analyzing and load-leveling the ITM schedules. This is a critical step to help ensure the process by which the organization’s assets are scheduled, inspected, tested, and maintained aligns with the way the asset data will be generated, housed, and maintained within the new EAM system.
After the organization has aligned and validated its data with the EAM system templates and confirmed the data to be generated through ITM procedures, the data can then be uploaded to the new EAM system.
At Enstoa, we help clients at any stage of their EAM system implementation journey. With our diverse functional expertise and global reach, we have learned how best to digitally transform organizations in different industries and countries.
EAM system implementation is a multi-year journey and just like all time-intensive initiatives, is at higher risk for failure. But by understanding the transformation steps and expectations, organizations can be better prepared to handle the challenges along the way and achieve their intended results.
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John Jobst, Director of Strategy & Consulting, leads the operations strategy and management consulting service line for Enstoa’s global clients. A global architecture-engineering-construction leader with over 20 years of experience, John guides executive teams toward transformation of their legacy projects and portfolios by helping them design a target operating model and transformation roadmap for today’s digital world.