Asset Management: Moving from a Reactive to a Predictive Business

January 072013
Asset Management: Moving from a Reactive to a Predictive Business
January 2013
 
By Nuris Ismail & Reid Paquin of Aberdeen Group
 
With the uncertainty surrounding the economic recovery, manufacturing executives are compelled to make difficult decisions related to capital and operational budgets that remain very tight. Unplanned downtime, inability to maintain planned production rates, safety and environmental incidences are all problems that can be traced directly to recurring equipment failure and operation mismatches in production rates and capacities. Asset management is the methodical planning and control of an asset throughout its lifecycle, including design and construction, operation, maintenance, upgrades, and eventual disposal or decommission.
 
Aberdeen's December 2011 Enterprise Asset Management report uncovered that over half of the respondents have tight capital budgets as the main force driving a focus on asset management. A year later, Aberdeen’s Asset Management: Building the Business Case for the Executive study found that there is a large decrease in the number of respondents, with slightly more than a quarter of manufacturers feeling this pressure (Figure 1). However, it is also apparent that manufacturers still operate in an economic recovery. Manufacturers are now pressured with not only reduced capital budgets, but also reduced operational budgets and rising material cost. As a result, cost cutting is a constant battle for all business units; this is especially true in asset-intensive industries, where the operational costs are generally higher.
 
Figure 1: Internal Pressures Driving Organizations to Focus on Asset Management
Source: Aberdeen Group, November 2012
 
The ultimate goal of any successful asset-management program is to extend the lifecycle and maximize the efficiency of all assets. Therefore, it comes to no surprise that pressure to maximize Return on Asset (RoA) is a close second. There is a constant battle in manufacturing to get the most out of the current asset base and the subsequent aging of the asset. Manufacturers are challenged in balancing these two pressures because while every manufacturer wants to maximize asset utilization, they can't do it at the sacrifice of the safety of employees, processes and the quality of their products.
 
Aberdeen used four key performance criteria to distinguish the Best-in-Class from Industry Average and Laggard organizations. These metrics measure the success of an organization's asset management program not only in terms of how it has improved plant operations, but also how successful these programs have been for achieving financial goals.
 
Table 1: Maturity Class Performance
Definition of Maturity Class
Mean Class Performance
Best-in-Class:
Top 20%
of aggregate performance scorers
  • 91% Overall Equipment Effectiveness (OEE)
  • 1.5% Unscheduled Asset Downtime
  • 30% Reduction in Maintenance Cost
  • +20% Return on Assets vs. Plan
Industry Average:
Middle 50%

of aggregate
performance scorers
  • 83% Overall Equipment Effectiveness (OEE)
  • 6.6% Unscheduled Asset Downtime
  • 13% Reduction in Maintenance Cost
  • +7% Return on Assets vs. Plan
Laggard:
Bottom 30%

of aggregate performance scorers
  • 72% Overall Equipment Effectiveness (OEE)
  • 16.3% Unscheduled Asset Downtime
  • 1% Reduction in Maintenance Cost
  • -13% Return on Assets vs. Plan
Source: Aberdeen Group, November 2012
 
Definition for the Key Performance Indicators
  • Overall Equipment Effectiveness (OEE): Measured as a percentage by multiplying availability times performance times quality
  • Unscheduled Asset Downtime: Measured as the amount of unscheduled time the asset is offline against total asset availability
  • Maintenance Cost: Measured as year over year reduction in total maintenance costs
  • Return on Asset (RoA): Measured as the percentage of return on asset (new income/total asset) goal achieved versus corporate goal
Performance on the four metrics above is directly linked to the success of a company's asset management program. The Best-in-Class enjoy less than a tenth of the unscheduled downtime and 26% higher OEE when compared to Laggards. In fact, Best-in-Class manufacturers reduced their maintenance cost by 30%, hence under-spending the planned budget. These metrics show that even in the face of reduced operational budgets the Best-in-Class are saving money and improving performance.
 
Business Capabilities
 
Companies operating in an asset intensive industry face two major competing pressures. On one hand these organization attempt to operate in a reduced operational and maintenance budget environment, while on the other hand maximize Return on Assets (RoA). To address these opposing market pressures, Best-in-Class companies have implemented a series of business capabilities to drive the success of asset management programs. At the highest level, that includes means being predictive to asset conditions. Enabling predictive asset management processes requires timely access to the right information in a form that enables employees to make effective decisions. Organizations should focus on reducing the time required by maintenance and reliability professionals to find this necessary information.
 
Figure 2: Knowledge and Performance Capabilities
Source: Aberdeen Group, November 2012
 
The Best-in-Class companies first collect all of their asset information from different plants and store it in a centralized knowledge warehouse. In doing so, they remove this information from individual data sources (such as excel spreadsheets and access databases located on personal computers) and have a single repository for data collection. In addition, the Best-in-Class also provide historical and real-time asset data for intelligent decision making.
 
By having robust data like this at hand, manufacturers can see how a particular asset has historically performed and compare that to how it is running in real-time. This is crucial in determining whether an asset is running at its peak or if maintenance is needed. In addition, by using trending data, companies are able to predict adverse events. Best-in-Class companies provide this information on-demand, thus enabling easier information access, which reduces unscheduled downtime and improves asset performance. All of these capabilities are needed for manufacturers to move from a reactive, break-fix methodology to a predictive maintenance strategy. 
 
The Use of Mobility
 
While Best-in-Class companies are more likely to invest in asset management solutions, they are also more likely to empower their employees with mobility tools. Overall, the adoption of mobility in manufacturing has been slow, to the say the least, but where Aberdeen is seeing the largest adoption of mobility solutions is in asset management.
 
The Best-in-Class lead the charge in this technology adoption and are more likely to use mobility to allow their operators to access asset condition information while on the job (Figure 3). Mobile technology lets operators view relevant data in real time. As a result of this increased access, operators are better equipped to service assets when they need maintenance, repair, or inspection.
 
Figure 3: Mobility Gaining Ground
Source: Aberdeen Group, November 2012
 
In addition, mobility can be employed to improve change request management. Traditionally, change management relies on an outdated, paper-based system. This process is burdensome because technicians must travel back-and-forth between work sites and the dispatch center for new assignments. There is also a heightened risk of error with this system because there is no guarantee that the information will be entered into the database. With mobility, workers can receive their assignments in the field, spend more time working, and create work orders right on their devices.
 
Providing mobile devices to field workers lets them input data automatically, access pending work orders, track repairs, and perform other critical tasks that traditionally required a trip to a work station. These tools are essential in many industries, like Oil and Gas, Utilities, and Mining, where work stations are not easily accessible. Best-in-Class companies are over 2.5-times more likely to use mobile devices while making their maintenance rounds. Improved data capturing allows for better analysis and evaluation and, as a result, the Best-in-Class are rapidly embracing mobile technology.
 
With the tightening of budgets, managers are being asked to do more with less. Because of this, it is not easy to procure funding to start or improve upon an asset management program. However, the operational and financial gains that stem from a proper management system well outweigh the investment needed. By implementing a program centered on reliability and predictive maintenance, companies will be able to gain visibility, improve efficiency, and ultimately save money. To find out more about how the Best-in-Class are successfully implementing an effective asset management program as well as other topics affecting manufacturers today, read Aberdeen’s Asset Management: Building the Business Case for the Executive.
 
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