Holly farm and trans European plastics Case study teaching notesHolly Farm Over a period of six years, the owners of Holly Farm have developed two additionalcomplementary businesses. The first is a service operation, opening up the farm to payingvisitors who can observe farming activities and enjoy tours, walks and exhibits; the second is anice cream manufacturing facility, which sells to farm visitors and also through the retail trade. The case allows students to explore some capacity constraints in a service business, and tocompare the capacity with demand forecasts.
The teacher will be able to highlight the dangers of ignoring changes in ‘mix’ of demand, and the inappropriate use of averaged data. Students canexplore options for flexing capacity, managing demand and target marketing to achieve a better balance between capacity and demand in a very seasonal business. They can also examine the role of inventory in the manufacture and supply of ice cream, withvarious seasonalities associated with different markets. Again, there are capacity constraints in production and storage.
The case illustrates the dangers that can arise when apparently sensible marketing policiesignore operational capabilities and constraints. Key issues ? Capacity management in services and manufacturing ? Capacity-related inventory ? Marketing/operations interaction ? Strategy in small businesses. Indicative questions 1. Evaluate Gillian’s proposal to increase the number of farm visitors in 2008 by 50 per cent. You may wish to consider the following:What are the main capacity constraints within these businesses? ?
Should she promote coach company visits, even if this involves offering a discount onthe admission charges? ? Should she pursue increasing visitors by car, or school parties? ? In what other ways is Gillian able to manage capacity? ? What other information would help Gillian to take these decisions? Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management , fifth edition,Instructor’s Manual92© Nigel Slack, Stuart Chambers & Robert Johnston 2007 2. What factors should Gillian consider when deciding to increase the number of flavours fromfour to 10? Note For any calculations, assume that each month consists of four weeks including holidays(statutory holidays should be ignored for the purpose of this initial analysis). Discussion 1. IntroductionMost students should be well prepared to provide data and calculations on all the details provided in the case. However, before this, it is important to overview the business, itsobjectives, constraints and forecasts. Objectives ? Both Gillian and Charles need to improve the profitability of their business. ? Charles does not want to disturb the farming business. ? Gillian believes that growth will provide extra profit.
Constraint The Gileses do not want to invest more capital on the business. ? The farm workers and their spouses are provided extra income from the new activities; theymay have become dependent on this money and used to the pattern of employment. ? Growth may be restrained by competitor action (other farms and other ice creammanufacturers) and affected by external factors (the economy, climatic conditions, etc. ) Forecasts The case does not say exactly how the forecasts were derived. However, it is clearly based on asubjective view of the following:(a) Historical growth, rojected forward(b) Policy to expand farm visitors by 50 per cent(c) Realistic view of effect of competitor attack on ice cream retailers. A table in the case illustrates the historical and forecast sales of ice cream in each segment,showing the result of these influences. Students will quickly forget that, despite its credibility, aforecast is uncertain. Yet we often have to plan on the basis of such figures. Some students will also note, either at this stage or later, that the ice cream forecast is expressedin sales (money), whereas production is in litres.
Where the same product is sold at severaldifferent prices, and the mix changes, this could be misleading. Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management , fifth edition,Instructor’s Manual93© Nigel Slack, Stuart Chambers & Robert Johnston 2007 2. Analysis of demand for the farm visitsWhile Question 1 asks the student to analyze various capacities, this is only relevant in thecontext of knowledge of demand. The data on farm visitors is expressed in numbers. The firsttask is to highlight the pattern of the demand for the service. Weekly demand pattern
The case states that twice as many visitors come on Saturdays and Sundays than on Fridays andMondays. Peak demand in Aug 2007 = 3400 visitorsWeekly demand Aug 2007 = 850Therefore Saturday or Sunday demand = 1/3 of 850= 283This demand pattern is an average ; the reality is that some Saturdays and Sundays are busier – depending on the weather, alternative attractions and so on. Daily demand pattern The pattern of attendance is over 283 people on the peak day. This is only indicative for discussion purposes. 2008 Forecast:It could be argued that if the business continues to be promoted in the same way, the demand pattern ill be unchanged, but if it is promoted more, it will increase by 50 per cent. This wouldresult in peak daily demand of 283 ? 1. 5 = 424 people3. Capacity analyses (1) Car parking 40 cars ? 4 people = 1606 buses ? 40 people = 240Maximum = 400 peopleA discussion should note the following: ? This is mix dependent (cars and coaches) ? All arrivals on site are during the afternoon, therefore only a single use of each space per day (unlike most car parks) Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management , fifth edition,Instructor’s Manual94© Nigel Slack, Stuart Chambers & Robert Johnston 2007 ?
There will be a problem on peak days (Saturdays and Sundays) and in peak season (June,July and August) (2) Milking-parlour viewing 150 minutes only (fixed viewing period)2. 5 hours ? 80 people/hour = 200 people (maximum)This is already exceeded in June, July and August and on Saturdays and Sundays. Note that this is the capacity when busy, but the ‘normal’ capacity is based on 10-minute batchesof 12 people, which is only 180 people. Presumably, the figure of 200 occurs only whencustomers are under pressure to pass through the gallery. This is known as the ‘coping zone’,where operations concentrate on the core service only. 3) Ice cream output Currently produced on a ‘Level Capacity’ basis, 4 days a week:350 litres/day = 350 ? 48 ? 4= 67,200 litres per year = 5600 (per month)Sales in 2007 = ? 300,000 + ? 108,000(? 6. 0/litre) (? 8. 00/litre)= 50,000 + 13,500= 63,500 litresThus, in 2007 sales was 95% of capacity. 50% extra visitors in 2008 = 7400 people= 3700 litres extraHowever, that in itself is not a problem, as retail sales, according to the forecast, are expected togo down. The real problem is that seasonality has been enhanced , since the farm is visited only7 months of the year. Limitations of ice cream production ?
Fast freezer capacity (key process-max 350 litres/24 hours) ? Storage capacity (7000 litres effective) ? Workers only available/requested 4 days/week ? Capacity planning options (level, chase, mixed plans) Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management , fifth edition,Instructor’s Manual95© Nigel Slack, Stuart Chambers & Robert Johnston 2007 4. Analysis of target markets (i) Promotion of coach visitors Advantages ? can schedule arrival time to suit service ? will come even if the weather is bad ? could be programmed for Friday/Monday only ? occupies less car parking space/person ? simple target market could have specially designed service package (e. g. without viewing gallery) ? promotion is responsibility of coach companies. Disadvantages ? ‘lumps’ of demand may overload service at various times/points. ? may have to discount admission price. © Nigel Slack, Stuart Chambers & Robert Johnston 2007 ? price elasticity of demand for entrance fee ? customer survey needed – what service package do they want? (customers and noncustomers) ? demographic data on target customers ? survey of needs of delicatessen trade/competitors’ offerings. 5. Effects of increasing number of flavours from four to 10 Disadvantages increase in variety and decrease in volume per flavour = product proliferation ? might increase retail sales – but will it affect farm shop sales? ? stock rotation problems (due to limited freezer capacity) ? extra inventory (greater variety of raw materials and finished goods) ? possible lost capacity due to extra set-ups (also note that visitors do not want to see set-ups)(e. g. 1 set up = 12. 5% of daily capacity) …BUT if mixing is not a bottleneck, there may be no change in capacity. ? more complex – supervision – co-ordination – packaging control – scheduling ? increased costs due to above effect on quality control (increased chance of errors) ? priority when stocks are low (to retail or farm shop? ) ? need for increasing freezer capacity in shop ? need for market information (preferences, forecasts, etc. ) ? move away from possibilities of line production in the future ? proof of competitive advantage – trial markets all outlets, or just shops? Advantages ? possible extra sales and contribution ? defend delicatessen trade (competitive advantage) ? potentially, more return customers (to try other flavours). Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management fifth edition,Instructor’s Manua98© Nigel Slack, Stuart Chambers & Robert Johnston 2007 Ice Cream Sales History and Forecast 050100150200250300350400450forecast2003 2004 2005 2006 2007 2008 Year Sales Value…? 000 Retail shops Farm shop total Exhibit1. 1 Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management , fifth edition,Instructor’s Manual99© Nigel Slack, Stuart Chambers & Robert Johnston 2007 Holly Farm: Monthly Visitor Numbers 2007 05001000150020002500300035004000Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Number of Paying Visitors Exhibit1. 2 Nigel Slack, Stuart Chambers & Robert Johnston,
Operations Management , fifth edition,Instructor’s Manual100© Nigel Slack, Stuart Chambers & Robert Johnston 2007 Visitors per Day: Aug 2007 050100150200250300Wed Thu Fri Sat Sun Mon Tue DayNumber of Paying Visitors Exhibit1. 3 Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management , fifth edition,Instructor’s Manua101© Nigel Slack, Stuart Chambers & Robert Johnston 2007 Exhibit1. 4 Farm Visitor “in-process” Inventory:Saturdays and Sundays in August 2007 050100150200250300 9:0010:0011:0012:00 13:0014:0015:0016:0017:0018:0019:0020:00 TimeApproximate Number of Visitors onSite
Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management , fifth edition,Instructor’s Manua102© Nigel Slack, Stuart Chambers & Robert Johnston 2007 Exhibit 11. 5 Total Sales and ForecastLitresSales to 2007 2008 (forecast)Retail shops 50,000 43,333Farm shop 13,500 20,000Total 63,500 63,333 Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management , fifth edition,Instructor’s Manual103© Nigel Slack, Stuart Chambers & Robert Johnston 2007 Model answers to short cases Producing while the sun shines 1. How should a business work out what it is prepared to pay for these increasinglysophisticated weather forecasts?
All this hinges around the costs associated with being wrong. For example, if a business makingcottage cheese produces 10 per cent too much in one period, what costs will it incur? The maincost, in fact, will be the increased likelihood that early production of the product will increase thechance that it is not sold before its sell-by date in the supermarket. Similarly, if it under produces by 10 per cent, what will be the financial penalties? Here the costs are likely to be a reduction inpotential revenue because the company’s brand was not available in the supermarket whencustomers wanted to purchase it.
Going through these calculations gives the company anapproximate idea of the cost of being wrong by 10 per cent. Now compare this with the cost of buying a sophisticated weather forecast. Of course the weather forecast could be itself wrong. But at least the company can ask some basic questions such as, ‘Suppose the weather forecastmeant that we were only wrong by (say) 5 per cent instead of 10 per cent, would half the cost of being wrong by 10 per cent be more or less than the price we pay for the weather forecast’?
If the price of the weather forecast is lower than that the question to be asked then becomes,‘What are the chances that the weather forecast will reduce our risk of being wrong to 5 per centinstead of 10 per cent’? None of these questions give a definite answer (though there are moresophisticated probability-based techniques which can help) but they do allow for a moresystematic appraisal of the investment in the forecast. number* Description (A) Last 12 months’ sales(000s)Physical inventory 2 Jan(000s)Re-order quantity (000s)(B) AverageInventory (approx half of ROQ, 000s)Estimate of stock turn(A/B) 016GH Storage bin large 10 0 5 2. 4. 0033KN Storage jar + lid 60 6 4 2. 0 15. 0041GH 10-litre bucket 2200 360 600 300. 0 7. 3062GD Grecian-style pot 40 15 20 10. 0 4. 0080BR Bathroom mirror 5 6 5 2. 5 2. 0101KN 1–litre jug 100 22 20 10. 0 10. 0126KN Pack (10) bag clips 200 80 50 25. 0 8. 0143BB Baby bath 50 1 2 1. 0 50. 0169BB Baby potty 60 0 4 2. 0 15. 0188BQ Barbecue table 10 8 5 2. 5 4. 0232GD Garden bird bath 2 6 4 2. 0 1. 0261GH Broom head 60 22 20 10. 0 6. 0288KN Pack (10) clothes pegs 10 17 50 25. 0 0. 4302BQ Barbecue salad fork 5 12 8 4. 0 1. 3351GH Storage bin small 25 1 6 3. 0 8. 3382KN Round mixing bowl 800 25 80 40. 0 20. 421KN Pasta jar 1 3 5 2. 5 0. 4444GH Wall hook 200 86 60 30. 0 6. 7472GH Dustbin + lid 300 3 10 5. 0 60. 0506BR Soap holder 10 9 20 10. 0 1. 0Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management , fifth edition,Instructor’s Manual120© Nigel Slack, Stuart Chambers & Robert Johnston 2007 As discussed earlier in Q1, the shaded areas in the table show that two products out of 20(10%) are out of stock as at 2nd January. In addition, there are three products at very lowinventory levels (baby bath, storage bin (small), and dustbin and lid), all of which have stocks of less than two weeks’ usage.
This indicates that stock levels for about 25% of the SKUs are lowor zero, putting supply at risk. Conversely, four out of the 20 products have a stock turn of 1. 0 or less. This is tying up workingcapital and space. This analysis suggests that control of inventory for nearly half the product range isunsatisfactory (too high or too low). 5. Using Pareto analysis, categorize the products into Classes A, B, C, based on usagevalue. Would this approach be useful for categorizing and controlling stock levels of all the products at TEP?
Students will have to prepare a table (ideally in MS Excel) such as that shown in Table 3 below(actually shown here in Word table format), to calculate all the annual usage values. Table 3 Calculation of usage values Product referencenumber* Description Unit manufacturing variablecost (Euro)Last 12 months’ sales(000s)Physical inventory 2 Jan(000s)Re-order quantity (000s)Usage value? 000 (cost * sales) 016GH Storage bin large 2. 40 10 0 5 24033KN Storage jar + lid 3. 60 60 6 4 216041GH 10-litre bucket 0. 75 2200 360 600 1650062GD Grecian-style pot 4. 50 40 15 20 180080BR Bathroom mirror 7. 50 5 6 5 37101KN 1-litre jug 0. 0 100 22 20 90126KN Pack (10) bag clips 0. 45 200 80 50 90143BB Baby bath 3. 75 50 1 2 187169BB Baby potty 2. 25 60 0 4 135188BQ Barbecue table 16. 20 10 8 5 162232GD Garden bird bath 3. 00 2 6 4 6261GH Broom head 1. 20 60 22 20 72288KN Pack (10) clothes pegs 1. 50 10 17 50 15302BQ Barbecue salad fork 0. 30 5 12 8 2351GH Storage bin small 1. 50 25 1 6 37382KN Round mixing bowl 0. 75 800 25 80 600421KN Pasta jar 3. 00 1 3 5 3444GH Wall hook 0. 75 200 86 60 150472GH Dustbin + lid 9. 00 300 3 10 2700506BR Soap holder 1. 20 10 9 20 12Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management fifth edition,Instructor’s Manual121© Nigel Slack, Stuart Chambers & Robert Johnston 2007 This can then be ranked by usage value, and cumulative usage value calculated, as shown inTable 4. Table 4 Ranked and cumulated usage value Product referencenumber* Description Unit manufacturing variablecost (Euro)Last 12 months’ sales(000s)Physical inventory 2 Jan(000s)Usagevalue? 000 (cost * sales)Cumulativeusagevalue% of Cumusagevalue ABC Category. 472GH Dustbin + lid 9. 00 300 3 2700 2700 42. 4 A041GH 10-litre bucket 0. 75 2200 360 1650 4350 68. 3 A382KN Round mixingbowl0. 75 800 25 600 4950 77. 7 A033KN Storage jar + lid 3. 0 60 6 216 5166 81. 1 A143BB Baby bath 3. 75 50 1 187 5353 84. 1 B062GD Grecian-style pot 4. 50 40 15 180 5533 86. 9 B188BQ Barbecue table 16. 20 10 8 162 5695 89. 4 B444GH Wall hook 0. 75 200 86 150 5845 91. 8 B169BB Baby potty 2. 25 60 0 135 5980 93. 9 B101KN 1-litre jug 0. 90 100 22 90 6070 95. 3 B126KN Pack (10) bagclips0. 45 200 80 90 6160 96. 7 C261GH Broom head 1. 20 60 22 72 6232 97. 9 C080BR Bathroom mirror 7. 50 5 6 37 6269 98. 4 C351GH Storage bin small 1. 50 25 1 37 6306 99. 0 C016GH Storage bin large 2. 40 10 0 24 6330 99. 4 C288KN Pack (10) clothespegs1. 50 10 17 15 6345 99. 6 C506BR Soap holder 1. 0 10 9 12 6357 99. 8 C232GD Garden bird bath 3. 00 2 6 6 6363 99. 9 C421KN Pasta jar 3. 00 1 3 3 6366 100. 0 C302BQ Barbecue saladfork0. 30 5 12 2 6368 100. 0 C This illustrates that four ‘A’ items account for 81% of annual usage value. These items shouldbe the focus of management’s attention in respect of ensuring that forecasting is donethoroughly, and that inventory levels are controlled tightly without prejudice to service levels of 100%. Conversely, the 10 ‘C’ items account for very little (298,000 Euro) of the total annual costs (6. 3million Euro), so risk of stock-outs can be minimized by making batches, hich satisfy (say) atleast three months’ demand (i. e. costing around 75,000 Euro for the sample of 10 C items). Thus EBQ may not be appropriate here, and low stock turns are acceptable. Simple two-bin or Kanban arrangements could be used to ensure availability. Nigel Slack, Stuart Chambers & Robert Johnston, Operations Management , fifth edition,Instructor’s Manual122© Nigel Slack, Stuart Chambers & Robert Johnston 2007 6. What overall recommendations would you make to Francis Lamouche about theproposed investment in the warehouse extension? The earlier analyses indicate that inventory is very badly planned and managed.
Before pursuing the development of the warehouse extension, Francis must be sure that better systems are in place to ensure that no large excesses of inventory exist, whilst service levelsare improved. A summary of improvements required is as follows: ? Pareto analysis to provide highly visible categorization (ABC) ? Different re-ordering and forecasting requirements for each category ? Use of EBQ for high usage value items, establishing new ROQs ? Remove slow-moving and obsolete stock from warehouse ? Monitor service levels by product category ? Delay warehouse extension decisio