Combine Historic and Predictive Construction KPI's to Gain a Full View
In Part 1 of this series, we laid the groundwork for why KPI's can be an indispensable tool within the construction industry and we examined a handful of general KPI types.
Here we will provide a simple example of some construction KPI's in action.
KPI Example
Let’s pretend I have a $1000 BV (Budget Value) to develop a BIM model of a semiconductor facility for a prospective client who wants the model in 4 weeks. Timely completion of this BIM model is very important if I want to win the actual bid, so I set up some KPI’s to track my progress and predict my outcome.
KPI Formulas That Will Be Used Historic:
From here we can determine the Earned Value Index or EVI where EVI = AV/(BV * % Complete). EVI will provide a baseline performance indicator where:
This factor can then be used to feed Predictive budget or schedule models. Predictive: The Project Management Institute calls these SPI and CPI or Schedule and Cost Performance Index.
These can be applied to forecast:
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I decide I will measure my progress at week 1 to see where I stand at the end of the first quarter of building the model. My plan is to be 25% complete, so $1000 BV x 25% = $250 PV (Planned Value).
At week 1 I come to find I have spent $500 (Actual Value) and I've only completed the foundation of the fab; let's say I'm 10% complete. Therefore, my historical values in this context are:
- $1000 = BV
- $250 = PV
- $500 = AV
- 10% = % Complete
- $100 = EV
Now I need to calculate my Earned Value Index (EVI), which would be $500 / ($1000 * .10) or EVI = 5.00. According to the numbers, I have spent $500, only earned $100 (EV), and my EVI > 1.00. I am in trouble. Now would be a good time to turn to predictive KPI’s. As PMI suggests, let’s use SPI and CPI to see how much trouble I am in and predict where I'm headed.
SPI = EV/PV so my SPI (Schedule Performance Index) = $100/$250 or .40. I have only recognized 40% of my planned progress…not good. I will finish way behind schedule.
CPI = EV/AC so my CPI (Cost Performance Index) = $100/$500 or .20. This means that I am only recognizing ¢.20 worth of work done for every $1.00 I spend to my original plan…not good. I will finish way over budget.
Looking forward, if my project continues on this same performance track, measuring from the 25% complete mark, I can now predict the following outcomes:
Schedule
4 Weeks (Original plan) divided by my SPI of .40 = 10 week final schedule. I can now predict a schedule overrun of 6 weeks.
Cost
$1000 (Budget Value) divided by my CPI of .20 = $5000 EAC (Estimate At Completion) or predicted final cost. I can work backward to say EAC – AV = FTC (Forecasted to Complete) to tell me I have to come up with $4500 to finish.
In my example, my predictive KPI’s tell me I am headed for trouble. I can use this information at the 25% complete mark to drive behavior and guide decisions to influence a different project outcome. I can use trends in KPI’s at check-in points on week 2 and week 3 to see if the changes in behavior I made at the end of week 1 (after I reviewed my 1st KPI’s) had an impact.
The biggest watch-out here is that one of these KPI’s (% complete) can be highly subjective, so a team should work hard to try to assign value of natural project milestones to make the KPI’s as objective as possible.
What if in the example above, the facility foundation was the most cost, schedule and labor intensive part of the entire model and represented 60% of the overall project effort? Very different KPI story with the exact same data but we changed one subjective variable.
To Conclude
As you can see from the example above, the point of the KPI’s are to show a trend, to predict future state, and drive behavior.
Good trend, happy future state, stay the course, do more of what you have been doing, it is working.
Bad trend, sad future state, change course, try something different.
If you would like more information about how we can help you with construction productivity improvement, please feel free to access our large-scale modularization fact sheet below:
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