{"id":42898,"date":"2024-06-14T12:04:00","date_gmt":"2024-06-14T17:04:00","guid":{"rendered":"https:\/\/assetmanagementprofessionals.org\/?p=42898"},"modified":"2025-11-03T12:05:45","modified_gmt":"2025-11-03T17:05:45","slug":"using-analytics-and-performance-indicators-to-drive-better-budget-decisions","status":"publish","type":"post","link":"https:\/\/assetmanagementprofessionals.org\/es\/news-articles\/using-analytics-and-performance-indicators-to-drive-better-budget-decisions\/","title":{"rendered":"Using Analytics and Performance Indicators to Drive Better Budget Decisions"},"content":{"rendered":"

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By Kendra Mock<\/em>
One of the more interesting perks of working as a reliability engineer, in my opinion, is getting to be part of the capital planning process. It never gets off the ground if you don\u2019t have a complete asset register with relevant datasets, but it tends to be the area where executives will listen to the story your data tells. Working for an organization that has a very large global portfolio of both industrial and office space, I had the opportunity to demonstrate the power of data-driven decisions. Historically, each region in this portfolio received a capital budget based on previous year expenditures\u2014a method that incentivized overspending to maximize next year\u2019s budget and discouraged cost savings. It also encouraged requesting excessive capital projects and often resulted in regions vying against one another for funding in a capital catfight.<\/p>\n\n\n\n

The Solution<\/h2>\n\n\n\n


Although capital planning can be a multifaceted process, some of the root concepts are not complex. The first (and longest) step in any good capital planning program is asset validation. Like real estate touts the importance location, capital planning\u2019s greatest value is in asset validation, asset validation, asset validation. Assuming you have a complete asset register with all the relevant details, the equipment then needs to be classified into relevant categories such that you can achieve a level of granularity that will distinguish between significant differences in replacement costs, operating environments, estimated useful life, and risks to business continuity or personal\/environmental safety. From Figure 1, you can see that these pieces of the process are the bulk of the work in setting up a data driven asset replacement program.<\/p>\n\n\n\n

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