Forecasting Avari Hotel, Lahore

Group Members

Syed Shaheryar Raza Rizvi

Muhammad Zaid Ashfaq

Izza Adnan

Ahmed Abbas

Ali Danish

Syed Khawaja Anser Mahmood

DISC-230

Group 5 (1)

Abstract: The Avari group is basically a family business with its core interests in the hospitality business. The company is currently operating under Mr. Byram D Avari (chairman) and his sons Dinshaw and Xerxes. The Avari hotel Lahore has a long and proud history of playing host to a diverse clientele for almost 36 years. In 1988 the Avari group entered into a franchise agreement with Ramada Renaissance Hotels international which ended in 1994, our source in the management regards this period as the peak of employee training on international standards. The hotel was renamed “Avari hotel” in 1994, and as of date the name has become a brand of a hospitable hotel chain with amenities that confine with international standards. At present the hotel faces competition mainly from Pearl Continent Hotel, which is located in its vicinity and offers almost the same standards as the Avari.

Overview:The Director Sales and Marketing, Mr. Syed Kazim Rizvi stressed in our correspondence that different factions of their clientele require different services and amenities to ensure the maximum value for their money and preference in Avari hotels. He maintains that the management has divided the clientele into leisure and corporate categories. The leisure category includes mainly tourists and walk in visitors while the corporate category hosts corporate guests visiting the city for meetings, lectures and other business proceedings. To clarify what differing value chains mean in practical application he asserted that, “with corporate clients it’s all about timing, they are usually on a tight schedule and we must ensure they are given a wakeup call on the dot, their clothes are ironed and ready the water is hot and running, their breakfast is crisp and steaming and their car is waiting and the receptionist and driver welcome them with a smile ..” as for their leisure clients “ they have time and they want to make the best of it,” for them we have to focus on in house amenities like a gym, a bakery, a pool , shopping stalls tour guides etc. “ The management is well aware of the value chain and there is clear integration of corporate strategy in all the departments. The head of the Accounting department gave figures that showed a 90% corporate clientele and 10% leisure clientele. This justifies the Marketing figures of 70% promotion budget spent on attaining and maintaining corporate clients and 30% on leisure clients. The management is well aware that the value created by human inventory is immense, hence a very sophisticated computerized system of employee appraisal is maintained to ensure the customer’s stay is as comfortable as possible. The appraisal system in play incorporates customer feedback, manager ratings as well as international standards. Another major aspect of the value chain is the quality of in house amenities such as room service and restaurants. To this end the kitchen is open for customers to visit to ensure hygiene and quality. The department head also does random checks on food being supplied to customers in terms of presentation, taste as well as the time it takes to reach them.

The nature of the industry is such that even though no visible production is taking place, an efficient inventory management system needs to be in place for the business to function. Inventory management is decentralized and divided according to departments and are under the

Group 5 (2)

direct control of the departmental heads that use various techniques they think fit. The restaurant and the room service department according to company policy need to be well stocked so no customer has to wait too long or denied a particular dish. The manager of operations, food and catering, Mr. Hamza Khaan shares that with experience he has come up with a simple formula he and his teams follow,” every customer that complains he had to wait too long and every customer who is denied a dish because its unavailable is on average ten more customers to our competitors….” He also has a mix of just in time and partial inventory systems as he told us that basic dietary dishes that we are sure will be ordered are partially prepared to reduce cooking time when ordered, however, specialties and rare dishes like lobster are prepared from scratch once ordered. He however stressed that one days partially prepared food stuff even though edible is disposed at days end because “serving customers fresh food is what we promise and we keep our promises.” The managers operations, room cleaning, Mr. Zain Khawaja also has to maintain inventory of soaps, shampoo, tissues etc. He emphasizes an optimistic approach and maintains enough inventories to provide for the entire 188 rooms for at-least two weeks. He justifies this by explaining the cost advantage in bulk buying, the available storage space as well as reduced risk of customer dissatisfaction. He stated that “people come here to get away from the constant thought of having to clean the house every day and the anguish when someday they realize they are out of toiletries, we ensure that are cleaning staff is fast, efficient and well equipped with their mops, brooms, clean sheets and shampoos etc. before they knock ur door.

As mentioned above, for the purposes of marketing, accounting and other amenities the customer base is divided into leisure and commercial categories. There is also a further subdivision of these categories. The leisure category consists of L1, L2 and L3. L1 being frequent customers L2 being seasonal customer that for eg come one every winter and L3 which are basically either first timers or walk ins. The commercial category is sub divided into detailed segments. C1 consists of renowned companies that have signed contracts with the hotel, they are given amenities like free airport transport, preference in bookings, don’t have to offer a collateral or down payment for their booking are offered a flat below market rate in return for a promise of at least 700-800 room nights per contractual year.C2 companies consist of companies that use the hotel services less frequently, avail at last 300 hotel nights , they are however offered a contract with discounted rates and are given second preference on advance bookings. C3 are a group of companies which are either alien or very infrequent customers. They are usually not under contract, are given a third degree preference on bookings and usually have to offer an advance payment on bookings. It is also interesting to note that LUMS comes under C2 companies and Avari is set to play host to around 50 foreign and local dignitaries that are scheduled to give lectures at LUMS.

The cost structure typically consists of a mixture of fixed and variable costs. The major fixed costs are depreciation, salaries etc. and basically sunk costs of the premises fixtures and fittings etc. and variable costs include bonuses, maintenance, inventories for the restaurant etc. However the accounting department at Avari treats all costs fixed as forecasted at 80% hotel occupancy.

Group 5 (3)

The head of the accounting department believes through experience that this number is an overall average of costs when linked to occupancy. Although the demand and hence costs may be higher or lower during several months he believes that in a yearly time frame the deviances average out and hence the budget is prepared using all costs as fixed operating at 80% occupancy.

Demand generation is subject to economic conditions, security concerns as well as seasonal factors such as the weather, events etc. Economic conditions and security concerns effect the demand in the long run, the deteriorating state of the local economy and the rising inflation is to blame for leisure demand to fall from 35 to 10 percent over a period of 10 years compared to the corporate clientele. The alleviated security risk has led to an overall decrease in demand as foreign dignitaries and tourist numbers flowing into the country have sharply declined. The hotel Industry growth rate which was 9.7% in 2005-06 is now below 5% owing to the political and economic instability. The weather is a major determinant of demand, as the graphs in Exhibit show they hotel demand has a cyclical trend, with its peak during the spring season. The management also mentioned that the worst month for business is usually the holy month of Ramadan as occupant numbers fall, this can be seen in occupancy decline in the month of August. They however maintain that the budget is not disturbed as during the month income from Iftaar buffets and outside catering are at the rise. The graph in exhibit A also shows nose dips in demand during the December-January periods, the management says that this is because corporate employees usually avail their holidays at this time and as Avari s main clientele is corporate its demand falls. The trend line in Exhibit is increasing even though the economy and security conditions are deteriorating. The root cause of the upward trend is not tourism but increased business opportunities. Following the elections the government has signed numerous MOUs with friend nations like China, Turkey, Iran and Saudia and the foreign dignitaries visiting the country have increased. The increased number of foreign businessmen following the new incentives offered by the government, increased foreign workers from countries like China to oversee their projects are the main reason for the upward trend for Avari’s demand. It is important to note that the demand trend for the hospitality industry, although increasing is not as fast as Avari’s because even though corporate clients are increasing the leisure demand is falling.

Capturing the Forecasting Procedure of Avari:Avari has a forecasting mechanism that provides the departments with the expected goals, demand and budget for the upcoming year. The data for the forecast is gathered from internal historical data budgeted and actual, competitors demand and forecasts from secret sources and data from PTDC (Pakistan Tourism Development Corporation) on tourism trends, both foreign and local. This data is not simply extrapolated to the future; weights are assigned to factors such as security conditions, visa policy, transport services, event calendars, economic conditions, corporate contracts, new competition etc. The weights attached are unanimously agreed upon in an annual meeting of all department heads. The adjustments made to the forecast are unanimous nonetheless subjective.

Group 5 (4)

The forecasting method used by Avari involves a great degree of subjectivity. Adding to this point as the group heads unanimously decide what weights to attach to different factors problems such as group think, dis-agreement etc. might lead to a faulty forecast. The forecasting method used is also questionable in terms of applicability as the historical data used to generate the forecast dates back three years and arrives at a corrupt average occupancy rate because it uses seasonalised data. Hence, we would recommend the moving average technique. As depicted in Figure 9 the MAD, MSE and MAPE of method used currently by Avari is much higher than the MAD, MSE and MAPE of the method we recommend. This method would not only resolve the issue of applicability but also smooth line the data and decrease the seasonal variations and arrive at an average close to reality.

Group 5 (5)

EXHIBIT A

Jul Aug Sep Oct Nov Dec Jan Feb March Apr May Jun0

5001000150020002500300035004000

Business Cycle 2010-11 Rooms

Figure 1 Business Cycle 2010-11 Rooms (Total Rooms Available per Month)

Jul Aug Sep Oct Nov Dec Jan Feb March Apr May Jun0

50010001500200025003000350040004500

Business Cycle 2011-12 Rooms

Figure 2 Business Cycle 2011-12 Rooms (Total Rooms Available per Month)

Group 5 (6)

Jul Aug Sep Oct Nov Dec Jan Feb March Apr May Jun0

1000

2000

3000

4000

5000

6000

Business Cylce 2012-13 Rooms

Figure 3 Business Cycle 2012-13 Rooms (Total Rooms Available per Month)

July

September

November

January

March MayJuly

September

November

January

March MayJuly

September

November

January

March May0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

f(x) = 37.4327033764623 x + 2969.93424296896R² = 0.582104587409997

Rooms Occupied Plot By Deseasonalized Data and Line of Best Fit

Figure 4: Showing the Plot of Deseasonalised Room Demand over the Months along with the trend-line

Group 5 (7)

Jul - 1

3

S ep-13

Nov- 13

Jan- 1

4

Mar-

14

May-1

4

Jul - 1

4

S ep-14

Nov- 14

Jan- 1

5

Mar-

15

May-1

5

Jul - 1

5

S ep-15

Nov- 15

Jan- 1

6

Mar-

16

May-1

60

1000

2000

3000

4000

5000

6000

7000

Forecasted Demand For Next Years (Seasonally Adjusted)

Figure 5: Forecasted Demand of Rooms for the Coming periods (Seasonally Adjusted)

Group 5 (8)

Jul

Sep Nov

JanMarch May Jul

Sep Nov

JanMarch May Jul

Sep Nov

JanMarch May

0

2000

4000

6000

8000

10000

12000

Average Room Rates 2010-13

Figure 6: Average Room Rates form July 2010 to June 2013 in PKR

Jul9%

Aug6%

Sep 7%

Oct9%

Nov8%

Dec8%Jan

9%

Feb10%

March10%

Apr9%

May7%

Jun8%

Revenue 2010-11

Figure 7: Revenue Spread over the Months in 2010-11

Group 5 (9)

Avari Hotel Lahore (Actual Data)

Description Jul Aug Sep Oct Nov Dec Jan Feb March Apr

Available Rooms2010-11 5828 5828 5640 5828 5640 5828 5828 5264 5828 56402012-13 5828 5828 5640 5828 5640 5828 5828 5452 5828 56402012-13 Forecasted 5828 5828 5640 5828 5640 5828 5828 5264 5828 56402012-13 Actual 5828 5828 5640 5828 5640 5828 5828 5264 5828 56402013-14 Forecasted 5828 5828 5640 5828 5640 5828 5828 5264 5828 5640

Occupied %2010-11 61.26 37.99 43.85 57.36 54.5 51.96 58.77 68.01 61.67 58.552011-12 65.48 31.73 58.46 60.59 62.38 53.35 65.7 74.61 71 72.72012-13 Forecasted 60.05 40.07 68 71.47 70.92 62.03 68.03 77.03 75 74.02

2012-13 Actual60.0034

339.0356

964.5390

1 66.472272.6595

772.3232

763.5037

782.4278

182.6527

181.5070

2013-14 Forecasted

49.75978

54.90734

75.35461

78.07138

81.56028

78.92931

72.32327

85.48632 84.9348

85.1063

Occupied Rooms2010-11 3570 2214 2473 3343 3074 3028 3425 3580 3594 33022011-12 3816 1849 3297 3531 3518 3109 3829 4068 4138 41002012-13 Forecasted 3500 2335 3835 4165 4000 3615 3965 4055 4371 41752012-13 Actual 3497 2275 3640 3874 4098 4215 3701 4339 4817 45972013-14 Forecasted 2900 3200 4250 4550 4600 4600 4215 4500 4950 4800

Revenue2010-11 30738 19693 22355 29630 28238 27541 30483 32075 33879 318992011-12 33117 16653 29366 31543 31880 28616 34386 39804 40500 391992012-13 Forecasted 34843 23250 38350 43316 41600 37596 41236 42780 46114 444642012-13 Actual 33431 20965 34026 37451 40704 40971 36315 44367 49558 494132013-14 Forecasted 30160 33280 45509 50505 51060 50140 46365 49950 55688 54000

Figure 8: Actual Data

Group 5 (10)

MAD (Avari) 273.1538462MSE (Avari) 121442.0833MAPE (Avari) 6.618844955 percent

MAD, MSE and MAPE calculated by applying MA3 and MA4 on the Deseasonalised Data

MAD (By MA3) 243.2930354MSE (BY MA3) 108954.7168MAPE (BY MA3) 6.472728604 percent

MAD (By MA4) 246.9806862MSE (By MA4) 109108.3227MAPE (By MA4) 6.497692926 percent

Figure 9: MAD, MSE and MAPE

J u l y

Au gu s t

S ep t emb er

Oc t o b er

No v emb er

D ec emb er

J an u a r y

F eb r u a r y

Ma r c h

Ap r i lM

ayJ u n e

0

1000

2000

3000

4000

5000

6000

Comapriti ve Forecasted Methods

Figure 10: Comparison between Avari’s and Our Forecast Methods