Using Earning Value Management

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Marcelo S. Dodson. Devry University, 5540 W. Executive Dr.,Suite. 100 Tampa, Florida, 33609, United States of. America. E-mail: [email protected]

Using Earning Value Management (EVM) to evaluate the quality of farming operations Marcelo S. Dodson Devry University, 5540 W. Executive Dr.,Suite. 100 Tampa, Florida, 33609, United States of America

E-mail: [email protected] Abstract Earned value management (EVM) is a useful method of projects performance measurement. It involves using formulas that integrate project scope, cost, and schedule measures to help the project management team to monitor the project performance against its baseline. EVM analyzes cost and schedule variances on the project execution. However, quality which is affected by the project triple constraints (Time, Cost, and Quality) is not considered on this method. Therefore, this paper intends to propose an equation for Quality Variance and Quality Performance Index using as example two activities existents in a sugarcane crop: furrowing and weed control. The sugarcane crop was planted in September 2011, in a farm located in the south region of the State of Florida, the United States. It was elaborated a schedule and cost management plan, for each one of the 7 sugarcane planting fields, following the methodology proposed by the Project Management Institute in its “A Guide To The Project Management Body Of Knowledge (PMBOK® Guide), 4th edition”. Then, quality indicators for furrowing operation (row spacing) and weed control operation (weed presence between rows) were defined based upon the agronomic specification for sugarcane. Seven months after the crop were planted, a “snap shot” was take on each field where data regarding row spacing and weed presence were collected. Control charts were utilized for row spacing evaluation and an empirical grade for weeds presence between rows was created. Similarly to cost variance, it was defined the Quality Variance (QV) equals to Earned Value for quality (EVq) minus Actual Costs (AC). The same analogy was made from Cost Performance Index (CPI), Quality Performance Index (QPI)= EVq divided by AC. Also, it was considered Planned Value (PV) equals to AC. The results indicated that fields 1, 2, 3, 4, and 5 were out of specification for row spacing and it represented 35% of all samples. Also, fields 1, 3, 4, 6, and 7 had an average of 57% of the area covered by weeds. From these results, it was possible to estimate the Earned Value for the operational quality. Considering that furrowing was the operation responsible to create row spacing, the furrowing AC for fields 1, 2, 3, 4, and 5 was $2,573.80 dollars and EVq equals to $2,035.77 dollars. Therefore, QV indicated that the lack of quality cost $538,03. Quality Performance Index was 0.8. It means that for each dollar that the farm invested on meet agronomic specification, only $0,80 cents was accomplished. Spraying herbicides and cultivating were the operations that direct affected the weed development. Fields 1, 3, 4, 6, and 7 showed an average of 57% of weeds. The combined AC for these activities was $18,923.11 dollars and EVq was $10,065.31 dollars. QV indicated that the lack of quality cost $8,857.80. QPI was 0.5 which means that for each dollar that the farm invested on meet agronomic specification, only $0.5 cents was accomplished. Key words: Project management, sugarcane, EVM, quality 1. Introduction Earned Value Management (EVM) is a technique of performance measurement frequently used for managing projects. The Project Management Institute (PMI, 2008) considers the EVM an efficient form to measure project performance and progress by integrating the work scope with the schedule and costs components. Unfortunately, the project quality, which is affected by these three factors, is not considered on the EVM. Therefore, the objective of this study is to propose equations that included the quality factor in the EVM estimation.

PMI stated “The principles of EVM can be applied to all projects, in any industry” (PMI, 2008, p.181). Fleming & Koppelman (2010) stressed that EVM is efficient in management projects but, it has limitations mananing ongoing operations. In this scenario, it is essential to define what a project is and verify whether a crop can be considered as a project. Also, the term quality must be defined for this study purpose. 1.1. Definitions According to PMI (2008), “a project is a temporary endeavor undertaken to create a unique product, service, or result” (p. 5). And, crop is “the total amount of plant material that can be harvested in a specified area at a given time” (Biology-Online, 2009). Additionally, by taking the sugarcane crop as a reference, it is possible to draw a table that shows some characteristics of a sugarcane crop in Florida, US that meets the project definition (see table 1). Based on these information, it is possible to infer that a crop can be considered as a project. TABLE 1: Sugarcane crop characteristics. Sugarcane crop in Florida, US Sugarcane has essentially four-growth phase's: germination phase, tillering (formative) phase, grand growth phase and Temporary Endeavor maturity and ripening phase The culture has an average economic life cycle of 4 years From the farm standpoint, each harvest produces a certain Unique product (deliverables) amount of sugar per acre The harvested material generates the farm income and it is the Value creation raw material for innumerous products, such as sugar, ethanol, and energy The environmental conditions are unique through the 4 year crop cycle Year by year, pests, weeds, and diseases change their occurrence, intensity, and distribution Constrains Each field has its own characteristics, and Time and resources for farming operations are variable Chemical constraints in the soils, such as acidity and low fertility High cost of inputs The buyer defines the quality standards which payment is dependent on Quality standards The crop has its agronomic specifications, such as row spacing and plants per acre The crop has agronomic, environmental, and legal requirements, regulations, and standards Requirements The crop requires large amounts of materials and physical tools to move or modify those materials* The site geography and conditions must be addressed.* Description*

(*) Adapted from Construction Extension to the PMBOK® Guide (PMI, 2007) and (Chaves et al., 2011)

Quality is “the degree to which a set of inherent characteristics fulfill requirements” (American Society for Quality, 2010). For the purpose of this study, quality is the realization of agricultural activities according to technical specifications for the respective activity and in accordance to the plant requirement. Moreover, it is considered that these activities are interdependent; consequently, the predecessor activity can impact positively or negatively on the subsequent activity (Peche-Filho et al., 1994). Warburton (2010) pointed out that earned value (EV) converts the physical work from units of measure to financial units, the planned value (PV) is the budget baseline for the work, and the

actual cost (AC) is the cumulative cost incurred and recorded at a given point in time to accomplish the activity. PMI (2008) described that schedule variance (SV) determine the schedule performance of a project and the cost variance (CV) measures the cost performance on a project. Finally, schedule performance index (SPI) evaluates the progress achieved to the progress planned on a project and cost performance index (CPI) evaluates the value of the work completed to the actual cost (PMI, 2008). 1.2. Potential benefits of EVM on farming operations By using EVM on farming operations, farmers would be able to monitor the schedule and costs variances throughout the crop life cycle and per field. They could estimate how much cost being behind the schedule or over costs due external events (e.g. weather and suppliers delays) or internal events (e.g. accidents and machinery problems). By integrating schedule and cost measurement and comparing them to the project (crop) expected value to date, farmers would have a more acurate indicador of the project performance than either time and cost measurements alone. On the quality side, it would be possible to evaluate whether the work performed delivered the agronomic quality for given activity, through the crop life cycle. Farmers would be able to value how much cost the lack of operational quality and how much efforts were converted in work correctly executed. 2. Material and Methods

The sugarcane crop was planted in September 2011, in a farm located in the south region of the State of Florida, the United States. It was elaborated a schedule and cost management plan, for each one of the 7 sugarcane planting fields, following the methodology proposed the Project Management Institute in its “A Guide To The Project Management Body Of Knowledge (PMBOK® Guide), 4th edition”. Then, the row spacing (1.50 meters between rows) was selected as quality indicator for furrowing operation. The agronomic specification for row spacing was 1,52 meters (60 inches) and it was acceptable a variation of 5 cm (Technical Upper Limit, 1,57 m (62 inches) and Technical Lower Limit, 1,47 m (48 inches). For the weed control operation, the percentage of the surface covered by weeds was the quality indicator selected (scale: 1=0-20% of weed presence,…,5=81-100%). Seven months after the crop were planted, a “snap shot” was take on each field where data regarding row spacing and weed presence were collected (Figure 1). It was collected 24 samples per field (4 rows x 6 samples). Control charts were utilized for row spacing evaluation and an empirical grade for weeds presence between rows was created (grade: 1=0-20% of weed presence,…, 5=81-100%). An average for each field was calculated and the results were confronted to the specification (up to grade 2: 040%). The equation for cost variance (CV) is CV=EV-AC and for cost performance index (CPI) is CPI=EV/AV. Using these equations, the first step was to define an earned value for quality (EVq). The EVq equation was defined as EVq=AC versus percentage of the quality indicator that met the specification (PQIS). Then, the equation for quality variance (QV) was defined as QV=EVq-AC and the quality performance index (QPI)=EVq/AC. The PQIS for row spacing was calculated by find the percentage of samples that were met the technical limits (Agronomic specifications). Similarly to CV, QV equals to zero means that the operation was realized under the specification. QPI equals 1 means that every dollar invested to meet agronomic specification was correctly utilized. In order to test the proposed equations, it was considered that the samples represented the whole field and AC was equal to PV. 3. Results Figure 1 shows the control chart for row spacing. Despite the fact of the tractor followed the GPS orientation, the graphs indicated variations through the fields.

Legend: Row Spacing: Blue line Upper Control Limit (UCL): Upper Red line Lower Control Limit (UCL): Lower Red line Technical Upper Limit (TUL): Upper Black line Technical Lower Limit (TLL): Lower Black line Target (Agronomic recommendation): Central Black line

FIGURE 1: Control Charts for Row Spacing Dots above or below the red lines (statistical limits of control) indicated that the furrowing operation was out of control. Dots above or below the black lines (Technical limits of control) indicated that the operation was out of agronomic specification. The results showed that the furrowing operation was out of control on all fields and out of specification on fields 1, 2, 3, 4, and 5. Also, the use of GPS suggested that this gadget can reduce operational variations; however, once the alignment was set up wrongly, the whole line followed that path.

TABLE 2: Estimated Costs for field operations, per hectare Description Machinery Quantity Furrowing JD_6420+furrower 3-Row 1,00 Herbicides - pre emergence CASE_Patriot_3185 + Herbicides 1,00 Herbicides - post emergence CASE_Patriot_3185 + Herbicides 1,00 Cultivating JD_6420+Cultivator 3-Row 1,00 Fields 1 2 3 4 5 6 7

TABLE 3: Quality Earned Value for furrowing operation Total Area (ha) AC (US$) PQIS (%) Evq (US$) QV (US$) 19,0 9,8 9,8 23,1 12,9 29,0 19,1

397,84 204,87 206,57 484,55 271,18 608,67 400,39 2.573,80

45,8 50,0 75,0 79,2 75,0 100,0 100,0

182,35 102,44 154,93 383,61 203,39 608,67 400,39 2.035,77

(215,50) (102,44) (51,64) (100,95) (67,80) 0,00 0,00 (538,03)

US$/ha 20,99 69,70 68,45 16,15 QPI 0,5 0,5 0,8 0,8 0,8 1,0 1,0 0,8

From these results, it is possible to estimate the Earned Value for the operational quality. Considering that furrowing is the operation responsible to create row spacing, table 3 shows that the furrowing operation total AC, for fields 1, 2, 3, 4, and 5, is US$2.573,80 dollars and EVq equals to US$2.035,77 dollars. Therefore, QV indicates that the lack of quality cost (US$538,03) dollars. It means that, the farmer invested US$2.573,80 dollars for opening furrows under the agronomic specification but, the operation just achieved its objective in 75% of the area. Consequently, the farmer lost US$ 538.03 due wrong work. Quality Performance Index was 0.8. It means that for each dollar that the farm invested on meet agronomic specification, only $0.80 cents was accomplished. Fields 1 2 3 4 5 6 7

TABLE 4: Quality Earned Value for Weed Control AC(US$) PQIS (%) Evq (US$) Total Area (ha) 19,0 9,8 9,8 23,1 12,9 29,0 19,1

2.924,71 1.506,10 1.518,60 3.562,14 1.993,55 4.474,55 2.943,46 18.923,11

67,5 100,0 47,0 13,0 100,0 50,0 40,0

1.974,18 1.506,10 713,74 463,08 1.993,55 2.237,28 1.177,38 10.065,31

QV (US$)

QPI

(950,53) 0,00 (804,86) (3.099,07) 0,00 (2.237,28) (1.766,07) (8.857,80)

0,7 1,0 0,5 0,1 1,0 0,5 0,4 0,5

Spraying herbicides and cultivating were the operations that directly affected the weed growth. Fields 1, 3, 4, 6, and 7 showed an average of 57% of weeds. QV indicated that the lack of quality cost US$(8.857,80) dollars. The farmer invested US$ 18.923,11 dollars on the weed control but, only US$10,065.31 was converted in effective weed control. QPI was 0.5 which means that for each dollar that the farm invested on meet agronomic specification, only $0.5 cents was accomplished (Table 4). The results on both tables 3 and 4 reinforce the need to monitor and control farming operations per field. Under same agronomic specification, each operation was performed differently on

each field. The QPI showed the variation range for furrowing (0,5-1,0) and weed control from (0,1-1,0). Therefore, farmers should evaluate operational performance per field in order to maximize its efficiency and minimize financial loses. These numbers indicated the farming operations varied from extremely efficient (1,0) to total inefficiency (0,1). These variations are responsible for reducing the farm competitiveness and they may impact on the potential yield. Considering the sustainability point, low GPI indicates that resources were wasted and potential reduction on the farm profitability. 4. Conclusion In conclusion, the objective of this study was to proposed equations that included the quality factor in the EVM estimation. The results indicated that the QV and QPI were a simple way to estimate the cost of quality on farming operations. Also, they made easier to identify performance variations by field. However, further investigation is necessary to validate this proposal under different crops, farming operations, agronomic specifications, and their interaction. 5. References American Society for Quality. (2010). ASQ. Retrieved 08 03, 2011, from http://asq.org/learnabout-quality/cost-of-quality/overview/overview.html Biology-Online. (2009, 09 03). Biology-Online. Retrieved 03 24, 2012, from http://www.biologyonline.org/dictionary/Crop Chaves, R. A., Dodson, M. S., Rodrigues, L. H., & Smith, V. Y. (2011). Project Plan: South Florida Farm Inc. Sugarcane Project. Course Capstone not published. Tampa, FL: Devry University. FAO. (2006). Food Security and Agricultural Competitiveness: Concepts and Perspectives. Retrieved 04 02, 2012, from www.fao.org/sd/erp/stluciaconference/may18/stluciarawlins.ppt Fleming, Q. W., & Koppelman, J. M. (2010). Earned Value Project Management. Newtown Square, PA: Project Management Institute, Inc. Peche-Filho, A., Costa, J. A., Ferreti, G., & Storino, M. (1994). Avaliação do grau de picagem de material orgânico: uma proposta de metodologia. "Organic material chipping Evaluation: a proposed methodology". Congresso Brasileiro de Engenharia Agrícola (p. p.252). Campinas: UNICAMP; SBEA. PMI. (2007). Construction Extension to the PMBOK® Guide. Atlanta, GA : The Project Management Institute, Inc. . PMI. (2008). A Guide to the Project Management Body of Knowledge. Newtown Square, PA: Project Management Institute.