BLUF: T-MDI makes prioritization schemas more transparent and often more effective.
Welcome to Part II of our MDI Blog series. As discussed in the last article, Tactical MDI (T-MDI) serves a valuable purpose – linking facilities and other assets to the mission to enable risk-based decision making. This is especially important as federal agencies and private sector organizations struggle to maintain aging buildings and infrastructure with limited available funding. T-MDI measures the relative importance of facilities in terms of mission requirements from the perspective of operators/managers who use (occupy) the facilities.
This Mission focus is different than the traditional engineering perspective that centers on facility Condition in terms of Risk Management. Combining T-MDI with other facility management metrics such as building conditions to make strategic and tactical decisions changes the paradigm from simply fixing assets that need repair towards investing resources in support of operational missions.
Based upon successful earlier MDI implementations in the Navy, Coast Guard, and NASA, the Air Force implemented the first version of their MDI metric in 2008 using Department of Defense Category Codes (CATCODES). All runways were assigned one score, all dormitories were assigned one score, etc. without regard to how vital each asset was to the mission at specific installations. This blanket approach method did not recognize the differences and unique challenges at each installation such as occupancy rates of facilities and the ease or difficulty of leveraging other nearby facilities to avoid mission failures. For example, a runway at a bomb wing may be more vital to mission compared to a runway at a space wing; or a child development center at a remote and isolated base may have more importance to the mission than one at a base in a populated area where alternative childcare options exist.
Recognizing that the CATCODE MDI scores did not fully represent local operational needs addressed at the individual real property asset level, the Air Force initiated a pilot study in March of 2017 comparing CATCODE based MDI scores with a more robust interview-based process at six installations. Two hundred and twenty different participants were involved in the pilot test (ranging from Wing Commanders to squadron members), which gathered data on 1,834 facility and infrastructure assets. The pilot test was used to develop and improve MDI methodologies, which were compiled in an Air Force MDI Improvement Playbook. Survey best practices, risk management, decision making, and calculation methodologies were evaluated as part of the pilot test. The pilot test also evaluated how asset-specific MDI scores may improve MILCON and FSRM prioritization, force protection, operational readiness, and general risk management.
Figure 1. Tactical MDI score
A major finding of the pilot test was that the methodology linking MDI to CATCODE had very little correlation when compared to the interview-based Tactical MDI scores that resulted from the input at the operator level. Figure 1 shows a comparison of legacy CATCODE MDI scores and interview-based MDI scores with low correlation (i.e. R2 = 0.2365). Because MDI accounts for 60% of the Consequence of Failure score of a project during the FSRM Integrated Priority List (IPL) process, the impact of Tactical MDI is significant. These results confirmed a need to engage with mission operators at the installation level, factoring their perspective about unique local impacting how important each facility is to mission success.
As a result of the pilot study and growing evidence that CATCODE based MDI values were measurably different than interview-based MDI, in 2019 the Air Force completed a portfolio-wide re-baselining effort at over 80 installations throughout the world collecting over 58,000 T-MDI scores. During this process, results continued to reaffirm that interview-based MDI values were noticeably different and more effective than CATCODE based scores. One example is at Joint Base Elmendorf Richardson Alaska, where several training facilities used by US Army Alaska had been assigned low CATCODE-based values but were found during interviews to be vitally important to the ability to deploy forces within 18 hours when activated, justifying much higher T-MDI scores.
Now that you understand how T-MDI is calculated and why an interview-based approach is more effective, let’s look at how relative mission importance can be useful to resource decisions. The below image shows 250 T-MDI scores ranging from 100 to 10. As a resource manager, this data provides full visibility into the Mission Value you are achieving for each resource decision. If a project with a T-MDI score of 100 is funded, you have achieved the maximum mission value with that investment. Likewise, if an investment is made to fund a project having a T-MDI score of 60, you are achieving less mission value but perhaps addressing key safety issues and condition- based needs. When T-MDI is used in conjunction with other inputs such as Condition Index, Safety requirements, and Agency Strategic Plans, prioritization schemas become more transparent and often more effective using a defensible, balanced, and transparent process.
MDI data doesn’t generally change over time unless qualifying events occur such as a change in mission or change in higher-level organizational strategies, but the data does need to be managed to ensure it remains responsive to the operator’s needs. We’ll cover MDI data sustainment towards the end of this series, including Quality Assurance and Quality Control along with best practices. As a challenge, start to think about a mission metric such as MDI that could be used beyond resource decision making. Could it have a role in Work Order response, Master Planning, Installation security, or even looking towards the future to plan and design more resilient installations with fewer single points of failure? All this and more are headed your way as we work through this five-part series.
Senior Consultant for the Asset Management practice at Definitive Logic
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