Holly Farm: Case Study Analysis

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Charles and Gillian Giles own Holly Farm, which they run together. Due to a decrease in income from milk and cereal operations, Holly Farm expanded its operations and reopened to the public in 2003. Gillian and Charles used their entire savings to create a 40-space parking lot and a bus stop to handle six 40-seater vehicles (Ponte, 2020). They also built a secure viewing area to observe the milking parlor. They also built special trailers for visitors to be shipped inside the farm on free tours, a rare breed paddock, a children’s activity park, a picnic area and a farm store. They also constructed a small factory to produce real dairy ice cream, artificially flavored ice cream, eggs, sugar, ingredients, and other items bought but not intended for public consumption. The following is an overview of the problems that Gillian is grappling with and an assessment of Gillian’s plan.

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Issues of Gillian

Gillian Gales is not having any issues on her end of the business. The fact that owners cannot bring extra money to the Holly Farm Corporation to grow is one problem. They have spent a considerable amount of money, and the extra revenue would be in grants. As the inflation rate is predicted to be above 10%, it is not suitable for borrowers to assume that they will cover both the interest and the principal’s loan. Gillian may consider other possibilities, such as the firm’s ice cream production capacity being insufficient, which would mean the 10,000-unit storage facility would not keep up with demand.

For stick processing, a container with a capacity of 7,000 items rotates within the cooler (Sasaki et al., 2017). The lack of ice-cream additives would also be a factor in this case, as the inventory must be shipped out of the manufacturer within 6-12 weeks. A reduction in retailers, resorts and ice-cream businesses would mean that retailers will lose their customer base during rush hours.

Gillian must also choose between supporting coach companies and marketing their farms to families and schools. Gillian figures out that one out of every two coach travellers purchases one liter of ice cream, while the other four passengers purchase the same amount. Considering the evidence on how many coaches, they usually have, these numbers, while useful as a starting point, do not allow for correct decisions (Steinbrink et al., 2019).

It is also not fair to make assumptions about the target market for the coming year based on the average performance. There is also a need for additional farm workers; currently, ice cream manufacturing hires agricultural workers’ wives (three). Due to lack of time and fixed times, only four flavors can be produced. If Gillian decided to raise the number of varieties to ten, she would have to recruit more people to make the frozen yoghurt. She would also have to measure and correctly estimate the number of flavors to manufacture if she wanted to increase them.

Gillian is not currently conducting a market study to determine which flavors clients need, which may help minimize the need to expand to ten flavors. Due to Gillian’s lack of marketing materials, the rate of farm cap arrivals has stayed at 15,000 per year; however, this situation is being overlooked as Gillian emphasizes increasing its production side. She now needs to be taking a more constructive approach to increasing farm activity (Kang, Zhao & Horst, 2016). The issue of farm timings inconvenient for picnics and warehouse visits (20% of customers leave before the milking process). Gillian should discuss the fact that many visitors are unable to perceive the milking process.

Evaluation of Sales Forecast

Weekly Demand Pattern

Saturdays and Sundays attract twice as many tourists as Fridays and Mondays, according to the case.

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The highest demand in August 1998 = 3400 guests

Every week request in August 1998 = 850

As a result, Saturday and Sunday are in fierce competition. = 1/3 of 850 = 283

However, this is an estimate; in practice, based on climate, alternative points of interest, and other variables, certain Weekends will be congested than others.

Demand Pattern on a Daily Basis

The pattern of participation over the day of the peak of 283 individuals is depicted in the weekly demand pattern. It is only meant to be used as a starting point for discussion.

1999 Forecast

If the business is encouraged in the same way but with more emphasis, the retail sales will remain unchanged but enhanced by 50%. As a result, daily demand would be at an all-time high.

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283 * 1.5 = 423 individuals

Capacity Analysis

Motor parking

40 cars * 4 individuals = 160

6 buses * 40 individuals = 240

Highest = 400 individuals

Following are some points to consider when having a discussion:-

  • This is influenced by the combination (cars and coaches)
  • Since all visitors arrive in the afternoon, each space is only used once per day (unlike most car parks)
  • There will be a parking issue on weekends in the peak season (June, July, and August) (Saturdays and Sundays).

Milking Parlor Viewing

Just 2.5 hours (time limit for display)

150/60 hours * 80 individuals/hour = 200 individual (highest)

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Saturdays and Sundays in June, July, and August have indeed exceeded this figure. This is when it is active; however, the “usual” capacity is only 180 people, based on 10-minute batches of 12 people. When customers are pressed into entering the gallery, the number of 200 is presumably only used once. This is known as the “learning to cope zone,” It is characterized by behaviors that are exclusively focused on the core purpose.

Ice Cream Production

0.350 M3/day = 0.35 * 48 * 4

= 67.200M3 per annum

= 5.600M3 (per month)

Revenues in 1998 = £300000/£6.0/ liter + £180000/£8.00/ litre = 50000 + 13500

= 63500 litres/ 1000 litres

= 63.5 M3

As a result, revenue reached 95% of capacity in 1998.

Guests have increased by 50%. in 1999 = 7400 individuals.

= 3.7 M3

However, since retail sales are projected to decrease, this is not a concern in itself. Seasonal variation has been compounded because the field is only attended for seven months each year.

Production Line Constraints

Even though Holly Farm’s manufacturing process has a critical capacity constraint, Gillian has been reluctant to address the problem. As a result, its growth strategy has been abandoned, despite its recent sustained sales growth trajectory. She should strive to solve the issue to continue with the growth plan. For example, during the busy season, she can negotiate with her staff to raise the number of working days in a week from four to five, six, or seven (Holley & Lecavalier, 2017). Though, Holly Farm pondered the feasibility of manufacturing various quantities of ice cream packages in response to special orders from the local catering industry, I would advise them to abandon their efforts. More severe capacity limitations would result if they pursued this trial.

Effects of Raising the Number of Flavor Combinations from Four to Ten


Many goods with lower sales will be phased out due to their expiration dates. The profit margin of each type of ice cream in the company could be same as the profit margin of each item in their products when Holly Farm made all ten of these items. Items with total needs of less than 1.5 million cubic meters each year, placing them below the fourth position, should not be produced because they will eventually be phased out due to their expiration dates.

The line extension will result in higher costs due to frequent changing goods and smaller output volumes than full production in most cases. When a different item from the previous one is made, the manufacturing line should be thoroughly cleaned beforehand to avoid making ice creams that vary from their original requirements in color or flavor. In reality, cleaning the ice cream machine in Holly Farm takes an hour between flavors (Radosavljević, Jevtić, & Klimenta, 2016). This meticulous cleaning usually results in higher costs and decreased earnings. Furthermore, a lower volume of output would lead to a higher fixed cost per cost of output and, as a result, a higher overall cost.


Since it costs to ensure that the marketing department can handle all of the expected orders, the company will be able to earn high returns for a fixed time by outsourcing the delivery process. Outsourcing is also critical because it prevents companies from wasting too much time on trivial information (Steinbrink et al., 2019). Most farm managers are aware of the advantages of outsourcing positions in the agricultural sector, such as financial, human capital, and risk evaluation. Holly Farm is a very cost-conscious environment, so outsourcing would ensure that the farm reaps some advantages, such as a specialist’s full-time employment.

Gillian will spend more time on their core functions and develop a large customer base to develop the farm business through outsourcing. As a response, they should prioritize their positions and those of their employees to achieve better efficiency (Ponte, 2020). This will give the farm business a good reputation over other related companies; thus, through outsourcing, they will be able to offer additional support services and achieve a more significant comparative benefit in the company.


Outsourcing choices should be kept to a bare minimum to satisfy the needs of visitors. Protection, promotions, information technology, and advertising are examples of operations that Gillian may not manage. When the burden is subcontracted, the farm can expand slowly, avoiding the Holly Farm from failing due to the employees’ inability to maintain all operations. On the other hand, the only way is to employ more people, while the problem is that the company does not possess enough financial resources to pay additional wages. To be very efficient in the line of services and products they can provide, Gillian should find a suitable manufacturer that she can trust and who specialized in the products they sell to the tourists. On the other hand, outsourcing has some benefits that can help a company save money rather than hire many employees to handle all aspects of the company.


Holley, C., & Lecavalier, E. (2017). Energy governance, energy security and environmental sustainability: A case study from Hong Kong. Energy Policy, 108, 379-389. Web.

Kang, N., Zhao, C., Li, J., & Horst, J. A. (2016). A Hierarchical structure of key performance indicators for operation management and continuous improvement in production systems. International Journal of Production Research, 54(21), 6333-6350. Web.

Ponte, G. (2020). Generative adversarial networks in marketing: Overcoming privacy issues with the generation of artificial data (Doctoral dissertation, University of Groningen. Faculty of Economics and Business). Web.

Radosavljević, J., Jevtić, M., & Klimenta, D. (2016). Energy and operation management of a microgrid using particle swarm optimization. Engineering Optimization, 48(5), 811-830. Web.

Sasaki, H., Kajino, T., Takiwaki, T., Hayakawa, T., Balantekin, A. B., & Pehlivan, Y. (2017). Possible effects of collective neutrino oscillations in three-flavor multiangle simulations of supernova ν p processes. Physical Review D, 96(4), 043013. Web.

Steinbrink, C., Blank-Babazadeh, M., El-Ama, A., Holly, S., Lüers, B., Nebel-Wenner, M.,… Lehnhoff, S. (2019). CPES testing with mosaik: Co-simulation planning, execution and analysis. Applied Sciences, 9(5), 923. Web.

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