Edad Media.

Dairy farming is the first interface of milk supply chain. To statistically compare SCOR means for dairy farmers from Pakistan and New Zealand, independent-sample two- tailed t-tests were performed for individual SCOR metrics. Table 6.1 illustrates that almost all SCOR metrics for NZ dairy farmers are significantly different from Pakistani dairy farmers. As discussed earlier in the results chapter that SCOR metrics are either upward or downward directed. The upward directed metrics are those for which higher value refers to the higher performance and vice versa, for example, perfect order fulfilment. Oppositely, for downward metrics lower value refers to higher performance and vice versa, for example, order fulfilment cycle time.

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Table 6.1 Gap Analysis of Dairy Farmers

SCOR Metrics Respondents n Mean Std. Dev. Gap t-stat

Perfect order

fulfilment (%) ↑ NZ dairy farmers _{PK dairy farmers 210} 50 99.8710 _{89.0929 10.13163} .39617 10.78 .000*

Order fulfilment

cycle time (hours) ↓ NZ dairy farmers _{PK dairy farmers 210} 50 33.7000 _14.3238 8.70433 _4.78533 19.3 .000*

Upside supply chain

flexibility (hours) ↓ NZ dairy farmers _{PK dairy farmers} NA _{70 24.0286} NA _5.65934 NA - NA

Overall value at risk

(%) ↓ NZ dairy farmers _{PK dairy farmers 205**} 40 13.2228 _9.2488 14.34750 _7.09263 4.19 .009*

SCM cost (as % of

SCR) ↓ NZ dairy farmers _{PK dairy farmers 210} 50 14.4016 _7.5525 5.17025 _5.75886 6.85 .000*

Cost of production

(as % of SCR) ↓ NZ dairy farmers _{PK dairy farmers 210} 50 51.1338 _{59.1110 10.76393} 7.42204 7.97 .000*

Return on fixed

assets (Ratio) ↑ NZ dairy farmers _{PK dairy farmers 210} 50 .1082 _.4880 .08436 _.41717 0.38 .000*

Return on working

capital (Ratio) ↑ NZ dairy farmers _{PK dairy farmers 210} 50 1.2870 _.5084 .73570 _.32671 0.78 .000*

* Significant at α = .05 and equal variances assumed ** Missing values refer to “No” value at risk

The perfect order fulfilment (POF) is an upward metric which measures SC reliability. The POF value for NZ farmers is higher than Pakistani farmers by almost 11%. Among others, two major reasons reported by the respondents for this performance gap are: First, the product as well as process quality at New Zealand dairy farms is ensured by an integrated quality assurance system in place. The milk quality at NZ dairy farms as well as the entire dairy chain is a collaborative responsibility of all the stakeholders including dairy farmers, dairy companies, regional councils, consultancy firms and regional councils, whereas no such quality assurance system is in practice at Pakistani dairy farms. Second, due to large average herd size (402 dairy cows (DairyNZ, 2014)) New Zealand dairy farmers can afford modern technologies such as automatic milk and cool chain infrastructure which ensures milk quality and safety during storage and transportation, whereas Pakistani dairy farmers are largely (92%) smallholder with 1-6 dairy animals which is why they cannot afford modern farming technologies such as automatic milk and coll chain infrastructure at dairy farm. The automatic milking of the dairy animals, chilling plants to store milk at dairy farm level, and refrigerated transport system to and from milk processing plant are the necessary components of a dairy

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chain. Whether it is informal of formal chain of milk in Pakistan, the very first stage ‘farm production’ is critical for quality assurance. The issues of food safety, sanitary and hygienic conditions at milk production, handling and transport stages in Pakistan dairy chain have also been reported by earlier researchers (Anjum, et al., 1989; Khan et al., 2008; Sarwar, et al., 2002; Tariq, et al., 2008; Teufel, 2007; Wynn, et al., 2006). For example, Tariq et al. (2008) pointed out that farming community is unorganized and smallholder which is why they cannot afford farm infrastructure such as cold chain equipment. The Figure 6.1 shows a subsistence level farmer manually milk water buffalo in rural Pakistan.

Figure 6.1 A Rural Farmer in Pakistan

Source: Author

The order fulfilment cycle time (OFCT) is a downward metric which measures the SC responsiveness. Now-a-days the responsiveness has become the basis for competition among the supply chains. However, some processes in agri-food supply chains are not continuous, such as milk production, and they inherit a certain non-productive dwell time. Twice a day milking has 12 hours throughput time whereas once a day milking has 24 hours throughput time. The New Zealand dairy farmers reported that the dairy company collected milk in three formats: once a day, once in two days, and any

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combination of the both in order to minimise milk transportation cost. The appropriate milk collection format depends on the time of year (as milk production varies with seasonality and lactation), herd size, and distance between dairy farm and factory. All the respondent dairy farmers in Pakistan reported twice a day milking of dairy animals. Therefore, the vast majority (80.5%) reported to supply milk twice a day to their customers. However, the remaining (19.5%) used to supply milk once a day mainly due to small volume of sales. The overall OFCT of Pakistani dairy farmers was almost 19 hours less than NZ dairy farmers.

Supply chain agility is measured as upside SC flexibility and value at risk. The upside SC flexibility is a downward metric which measures the ability of a business to response to any unusual increase in demand. The mean value for Pakistani dairy farmers was 24 hours whereas this does not apply to NZ dairy farmers because they already supply all the milk produced to the dairy cooperative or company. The overall value at risk (VAR) is a downward metric and was calculated as VAR as percentage of SC revenue. The VAR for NZ dairy farmers was higher than Pakistani dairy farmers by 4.19%. This performance gap is primarily due to the inherent differences in both the milk supply chains such as the dairy farming in New Zealand is pasture-based, exposed to highly fluctuating weather and employing huge capital investment in land resources whereas in Pakistan is fodder-based where animals are kept in barns and therefore, relatively less investment required for land.

The SC costs are divided into SCM cost and cost of milk production, both downward metrics. The SCM cost of Pakistani dairy farmers as percentage of their supply chain revenue (SCR) was 6.85% less than NZ dairy farmers. The prime reason behind this performance gap is the fundamental difference of scale of operation of the benchmarking partners. Majority (almost 63%) of the selected dairy farmers in Pakistan were smallholders (having less than 10 dairy animals). Moreover, milk transportation cost which is the largest contributor to SCM cost is not applicable to majority of the Pakistani farmers whereas this cost is deducted from farm gate milk pay out of all NZ dairy farmers. The cost of milk production as percentage of SCR of selected dairy farmers in Pakistan was almost 8% higher than NZ dairy farmers. Tariq et al. (2008) report a bunch of reasons for higher cost of milk production at Pakistani dairy farms. These are small scale of production, poor farm management practices, poor productivity per dairy animal, and seasonal variation in fodder availability. On the other side, dairy

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farming in New Zealand is least cost due to its pasture-based milk production system whereas, Pakistani dairy farming is mainly fodder based which is a labour intensive milk production system.

The efficiency and effectiveness of doing business is gauged as return on investment. Asset management varies across geographical locations, cultural norms, regulatory structure, and managerial expertise. The SCOR model measures return on investment in terms of return on fixed (non-current) assets and return on working capital, both upward directed metrics. The value of return on fixed assets ratio for NZ dairy farmers was less than Pakistani dairy farmers with a performance gap of 0.38. This performance gap is mainly due to different structure of capital investment in both dairy industries. This relatively higher level of investment in fixed assets in NZ dairy farms is due to three factors. First, it is predominantly a pasture-based production system where huge capital investments are attached to land. Second, higher compliance cost which means investment in farm infrastructure including automatic milking parlour, chilling plant, effluent management. Third, is the investment in the form of share capital (wet shares) of cooperative which is a pre-requisite to become a cooperative member and to supply milk. On the other hand, Pakistani farmers utilize fixed assets such as land and machinery predominantly for crop farming and relatively less fixed invetment is required for stall-fed dairy production system. The value of return on working capital ratio for NZ dairy farmers was higher than Pakistani dairy farmers by 0.78. Despite of higher investment in the fixed assets at NZ dairy farms, farm working expenses were comparatively less due to the least cost pasture-based production system and economies of the large scale production. On the other hand, Pakistani smallholder farms were operating at diseconomies of the scale and at comparatively higher working expenses. The above gap analysis can be summarised as the Pakistani dairy farmers under performed in supply chain reliability, cost of production, and return on working capital as compare to NZ dairy farmers. The majority of the Pakistani dairy farmers were smallholders and due to diseconomies of the scale of their operation they could not afford modern dairy farming technologies such automatic milking, milk storage at controlled temperature, and other precision dairy farming (PDF) technologies.

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