Case Study in the Application of Project Definition Rating Index and

Case Study in the Application of Project Definition Rating Index and Best Value Performance Information Procurement System to a Sprayed Polyurethane Foam (SPF) Roofing Project
D.R. Gajjar1, D. Kashiwagi2, K. Sullivan3 and J. Smithwick4
1
Del E. Webb School of Construction, Performance Based Studies Research Group, Arizona State University, P.O. Box 873005, Tempe, AZ 85287; dgajjar@exchange.asu.edu
2
Del E. Webb School of Construction, Performance Based Studies Research Group, Arizona State University, P.O. Box 873005, Tempe, AZ 85287; Dean.Kashiwagi@asu.edu
3
Del E. Webb School of Construction, Performance Based Studies Research Group, Arizona State University, P.O. Box 873005, Tempe, AZ 85287; Kenneth.Sullivan@asu.edu
4
Del E. Webb School of Construction, Performance Based Studies Research Group, Arizona State University, P.O. Box 873005, Tempe, AZ 85287; Jake.Smithwick@asue.edu
ABSTRACT
Pre­planning has a direct impact on cost, time, and quality, and is critical to the success of any project in the construction industry. There are multiple pre­planning tools currently used by the owners and contractors in the industry. The Project Definition Rating Index (PDRI) assessment is one of the pre­planning tools used by the owners to determine the completeness of the scope definition before commencement of the design and construction phase. This paper focuses on measuring and analyzing the PDRI score for a high­risk roofing project in Miami, Florida. The PDRI score of 180 out of 1,000 indicates that the owner had a well­
defined project, good estimate of cost and schedule, and an appropriate team alignment. Along with using the PDRI, the owner also utilized a value­based selection and project management process to deliver the project. The key component of process is pre­planning and identification / minimization of the risks associated with the project before signing the contract. The price and interview criteria were weighted the highest in the selection phase. Five contractors bid on the project and the awarded best value contractor had the highest interview score and the lowest cost. The low PDRI score coupled with a best value contractor who pre­planned the project led to a successful outcome. The project was completed on­time and on­budget with no contractor­generated change orders.
INTRODUCTION
Pre­planning is one of the important aspects for the success of any project in the construction industry. Planning before the project execution has resulted in improving the productivity in the construction industry (Menches et. al. 2005. There are multiple pre­planning tools available in the construction industry. A computer model known as MDA Planner has been used for planning and control in the construction industry (Jagbeck 1994). Business Information Modeling (BIM) has also gained attention in the construction industry due to its ability to obtain project information in the pre­planning phase and also throughout the life cycle of a project at necessary times (Yan et. al. 2014). A decision model that provides the estimate and evaluates the various elements of the project has also been used for pre­design planning process (Merino 1989). Pre­planning is also directly related to project performance in terms of cost, schedule and quality (Cho and Gibson 2000).
Before pre­planning for the actual construction, the owner needs to develop the plans for the actual construction that are related to specific goals and objectives that meet the owners requirements (ASCE 2012). Project Definition Rating Index is one of the pre­planning tools used by the owners to have a quantitative understanding of the scope definition (Cho and Gibson 2000). Best Value procurement that focuses on utilizing the expertise of the contractor for identification and minimization of risks by identifying the best value contractor before signing the contract between the owner and the contractor has also resulted in increased project performance (Kashiwagi 2014).
This paper focuses on measuring and analyzing the PDRI score for a roofing project in Miami, FL coupled with the Best Value Procurement model for hiring the expert best value vendor for the roof installation. The owner of a cold storage facility was faced with the problem with the existing roof of deterioration on the exterior roofing system and the formation of ice popsicles inside the facility. The owner had invested $600K six years earlier with the expectation of a trouble free 20 year roofing system, but now the owner was faced with additional $600K investment due to the existing problems. After realizing that the damage to the roof is not reparable, the FM and the owner agreed to invest an additional $600K for a new roof, but after the assurance that the proper pre­planning tools be implements to increase the probability of the success of the project this time round.
PROJECT DEFINITION RATING INDEX (PDRI)
Project Definition Rating Index (PDRI) assists the owners by calculating the total score in terms of weighted checklist that helps in developing a project scope. The PDRI consists of 64 scope definition elements that are divided into three sections and eleven categories. Each of the 64 elements has six definition levels from Level 0 (not applicable) to Level 5 (poor defined scope). The PDRI score sheet is used to evaluate each scope definition level and is rated based on the how well the element is defined in the scope (Cho and Gibson 2000). The total evaluation score for PDRI ranges from 70 to 1,000. The lower the total score, the better the project definition. The PDRI score of <200 is classified as a well­defined project scope from the owner side before the execution phase of the project. The PDRI score for this roofing project before the execution phase was 180 out of 1,000 which can be concluded as well defined project scope, a good estimate of cost and schedule and team alignment form the owner side. Moreover, the owner included the contractor in the scope development phase to use their expertise and experience. However, PDRI alone is not sufficient for a successful project (Cho and Gibson 2000), but there also needs to be a business model that can use the expertise of the contractor in the execution phase. Hence, the owner used the Best Value Performance Information Procurement System (BV PIPS) to select the contractor that can mitigate the risk for the owner by using their expertise.
BEST VALUE PROCUREMENT
Best Value Performance Information Procurement System (BV PIPS) utilizes expertise of the contractor to lower cost and add value to the owner. The BV PIPS is a system that assigns accountability which is otherwise very difficult to assign in a traditional procurement system (Sullivan and Michael, 2011). In the BV PIPS system the vendors compete to differentiate themselves based on their expertise instead of just price and then the expert vendors identifies the major risks involved with the project and the solution as part of the pre­planning before the contract is signed.
Five contractors proposed for this project. The criteria and weights that were used in the selection phase to identify the best value contractor are outlined in Table 1 (Kashiwagi, 2010).
Table 1. Selection & Weightage Breakdown.
Selection Criteria
Proposed Duration
Proposed Total Cost
Sum of age of all the jobs that do not leak
Past Performance
Average age of all the jobs
Average roof size
Interview Rating
Selection Weights
10
43.35
6.66
3.33
3.33
3.33
30
Table 2 shows the proposal information for the contractors that bid on the project. Vendor B received an interview rating on 1.1 out of 10 and they only submitted one past project. Vendor C and Vendor D did not have the high interview ratings. Vendor A and Vendor E had the interview rating of 9.39 and 6.28 out of 10 respectively, but Vendor A had the lowest price and highest number of past projects.
Table 2. Proposal Information.
Criteria
Proposed Duration (days)
Proposed Total Cost ($)
Sum of age of all the jobs that do not leak
Past Performance (out of 10)
Average age of all the jobs (Yrs.)
Average roof size (SF)
# of Surveys
Interview Rating (out of 10)
Vendor A
85
$570,846
Vendor B
60
$798,960
Vendor C
30
$596,000
Vendor D
60
$629,574
Vendor E
60
$685,379
19.1
0.5
84.5
264.0
14.7
10.0
9.9
9.5
10.0
9.6
1.5
0.5
6.5
14.0
3.7
60,244
14
9.39
40,669
1
1.11
12,080
13
4.94
60,595
19
4.83
159,988
4
6.28
The data was normalized for each selection criteria and multiplied by the total weightage to obtain the total point breakdown for each vendor as shown in Table 3.
Table 3. Total Point Breakdown.
Criteria
Proposed Duration (days)
Proposed Total Cost ($)
Sum of age of all the jobs that do not leak
Past Performance (out of 10)
Average age of all the jobs (Yrs.)
Average roof size (SF)
Interview Rating (out of 10)
TOTAL POINTS (out of 100)
Vendor A
3.53
43.35
Vendor B
5.00
30.97
Vendor C
10.00
41.52
Vendor D
5.00
39.31
Vendor E
5.00
36.11
0.48
0.01
2.13
6.66
0.37
3.33
3.29
3.17
3.33
3.21
0.35
0.12
1.55
3.33
0.88
1.25
0.85
0.25
1.26
3.33
30.00
3.55
15.78
15.43
20.06
82.30
43.79
74.41
74.32
68.96
Vendor A was selected as the Best Value contractor and was selected to re­
roof the cold storage facility.
RESULTS
The PDRI score of 180 out of 1,000 is a low risk score. The score that is <200 has a well­defined scope, business plan, site selection and facility requirements. Hence, the owner had a clear idea of the vision and the requirements of the project and a good estimate of cost and schedule before the commencement of the construction phase.
Vendor A that was selected for this project was able to pre­plan and minimize the risks using the BV PIPS system for the owner. Table 4 outlines the risks that occurred during the construction phase. The cost deviation of $28,485 was caused due to the connection from the wall clip to the beam was not attached in multiple locations which as a design error. The risks from the client were due to the late issuance of NTP and extended time from the owner for procurement for a better scope definition. The unforeseen risks were due to unsafe roof decking and safety issues caused by ammonia lines. Vendor A did not generate any source of risk throughout the project to the owner due to its expertise.
Table 4. Project Risks.
Source of Risk
CONTRACTOR IMPACT ­ General Issues
DEALER IMPACT ­ Sub/Supplier Issues
DEALER IMPACT ­ Oversight of Design
ARCHITECT / DESIGNER IMPACT
CLIENT IMPACT ­ Scope Change / Decision
CLIENT IMPACT ­ Contractors (GC, Mech., etc.)
CLIENT IMPACT ­ Contract / Payment
CLIENT IMPACT – Other
Impact of unforeseen conditions
0
0
0
1
Schedule Impact (Days)
0
0
0
0
2
63
$0
2
75
$0
1
0
5
30
0
188
$0
$0
$610,000
Total # of Risks
Cost Impact ($)
$0
$0
$0
$24,485
CONCLUSION
Pre­planning from both the owner and the contractor is critical for the success of any construction project. The PDRI pre­planning tool provided the owner with the well­defined scope, team alignment and good estimate of cost and schedule before the commencement of the construction phase. PDRI helped the owner to identify, measure and mitigate the project risks before they occur setting up the stage for the successful execution phase. The Best Value Performance Information Procurement System (BV PIPS) was successfully able to identify the expert Vendor A due to the lower cost and highest interview score. BV vendor was successfully able to pre­plan, minimize the risk for the owner in the construction phase by using their expertise and caused no contractor generated change orders. In conclusion, the owner received a high performing SPF roof with a 15 year warranty with no signs of ice popsicles.
REFERENCES
Jägbeck, A. (1994). ”MDA Planner: Interactive Planning Tool Using Product Models and Construction Methods.” J. Comput. Civ. Eng., 8(4), 536–554.
Menches, C., Hanna, A., and Russell, J. (2005) Effect of Pre­Construction Planning on Project Outcomes. Construction Research Congress 2005: pp. 1­10.
Yan, P., Xie, X., and Meng, Y. (2014) Application of the BIM Technique in Modern Project Management. ICCREM 2014: pp. 302­311.
ASCE (2012) Pre­Contract Planning for Construction. Quality in the Constructed Project: Third Edition, pp. 111­118.
Cho, C. and Gibson, Jr., G. (2000) Development of a Project Definition Rating Index (PDRI) for General Building Projects. Construction Congress VI: pp. 343­
352.
Kashiwagi, Dean. "Best Value Performance Information Procurement System (PIPS)." 2014 Best Value Standard. Mesa: Kashiwagi Solution Model (KSM), 2014. 2.1 ­ 2.8. Print.
Kashiwagi, D., Smithwick, J., Kashiwagi, J., and Sullivan, K. (2010). A Case Study of a Best Value Manufacturer, Journal for the Advancement of Performance Information and Value, Performance Based Studies Research Group & CIB W117, 2 (1) pp. 23­32.
Sullivan, K. and Michael, J. (2011). ”Performance Measurement Approach to Contracting and Delivering Design Services.” J. Prof. Issues Eng. Educ. Pract., 137(4), 248–257