Performance Analysis And Recommendations For Festive Restaurants

Summary Report

The case that has been provided in the question is that Feastive restaurant is a full service casual themed restaurant across Australia. Being the vice operational president of the restaurant, it has been asked to provide an analysis in regards to the performance of the restaurant. The analysis has been carried out with the help of the spreadsheets. The utilization of the spreadsheets for carrying out the essential performance report of the restaurant has proved to be quite efficient. The computations like the average annual sales and average restaurant age has been easy to calculate due to the facilitation of the different mathematical functions by the spreadsheets.

	Victoria	NSW	Queensland	SA Save Time On Research and Writing Hire a Pro to Write You a 100% Plagiarism-Free Paper. Get My Paper	WA	NT	Tasmania	ACT
Total Annual Sales	$ 7,61,68,595	$ 12,27,20,339	$ 5,10,33,306	$ 4,41,18,238	$ 3,88,94,552	$ 1,28,71,940	$ 1,07,13,373	$ 1,44,65,808
Total number of Seats	7373	11043	5038	4208	4173	1374	1187	1425
Average Annual Sales	$ 21,76,246	$ 23,15,478	$ 21,26,388	$ 21,00,868	$ 18,52,122	$ 18,38,849	$ 17,85,562	$ 20,66,544
Average Restaurant Age (years)	31.4	32.0	31.8	33.2	31.9	27.1	29.1	30.6
Total number of Restaurants	35	53	24	21	21	7	6	7
Total number of advertising Restaurants	32	43	18	19	13	3	4	6

	City	Metro	Country
Total Annual Sales	$ 6,32,86,529	$ 12,81,57,025	$ 17,95,42,597
Total number of Seats	6014	11663	18144
Average Annual Sales	$ 21,82,294	$ 22,48,369	$ 20,40,257
Average Restaurant Age (years)	31.6	31.5	31.7
Total number of Restaurants	29	57	88
Total number of advertising Restaurants	20	47	71

	Small	Medium	Large	Huge
Total Annual Sales	$ 19,38,327	$ 12,71,41,957	$ 21,31,69,307	$ 2,87,36,560
Total number of Seats	411	15140	18473	1797
Average Annual Sales	$ 6,46,109	$ 17,41,671	$ 23,95,161	$ 31,92,951
Average Restaurant Age (years)	30.7	31.3	31.8	32.2
Total number of Restaurants	3	73	89	9
Total number of advertising Restaurants	1	51	79	7

Q.4
Sum of Annual Sales ($)	Column Labels
Row Labels	ACT	NSW	NT	QLD	SA	TAS	VIC	WA	Grand Total
Large	7026183	88690004	4226406	26621643	18486064	5022000	43213638	19883369	213169307
Grand Total	7026183	88690004	4226406	26621643	18486064	5022000	43213638	19883369	213169307

Highest Sales by Region	Column Labels
Row Labels	NSW	Grand Total
Large	88690004	88690004
Grand Total	88690004	88690004

Lowest Sales by Region	Column Labels
Row Labels	NT	Grand Total
Large	4226406	4226406
Grand Total	4226406	4226406

Average of Profit ($)	Column Labels
Row Labels	TAS	WA	Grand Total
Small	114786.0575	220922.13	185543.4392
Grand Total	114786.0575	220922.13	185543.4392

Average of Profit ($)	Column Labels
Row Labels	TAS	WA	Grand Total
Small	114786.0575	220922.13	185543.4392
Grand Total	114786.0575	220922.13	185543.4392

Row Labels	Max of Profit per square metre ($)
Small	45.60431367
Country	45.60431367
Metro	37.59114904
Grand Total	45.60431367

The area, which has the highest Profit per square meter for ‘Medium’ size restaurant is Metro

Row Labels	Min of Profit per square metre ($)
Small	35.9882448
Country	45.60431367
Metro	35.9882448
Grand Total	35.9882448

Q.4.g:
	Column Labels
	Sum of Annual Sales ($)	Sum of Seats per Restaurant	Total Sum of Annual Sales ($)	Total Sum of Seats per Restaurant
Row Labels	Medium	Medium
VIC	26289778	3217	26289778	3217
Grand Total	26289778	3217	26289778	3217

Q.4.h:
	Column Labels
	Huge		Total Max of Annual Sales ($)	Total Average of Square Metres per Restaurant
Row Labels	Max of Annual Sales ($)	Average of Square Metres per Restaurant
NSW	3579194	5955	3579194	5955
Grand Total	3579194	5955	3579194	5955

Q.4.i:
Sum of Annual Sales ($)	Column Labels
Row Labels	TAS	Grand Total
Hobart Harbourside	2637013	2637013
Grand Total	2637013	2637013

Q.4.j:
Row Labels	Sum of Profit ($)	Sum of Annual Sales ($)
NSW	26753285.29	122720339
Richmond	306818.19	1461039
Dubbo	251030.60	1540065
Bankstown	402222.60	1547010
Nowra	323828.40	1619142
Albury	364798.50	1658175
Camden	436447.96	1678646
Broken Hill	297391.37	1749361
Orange	297841.53	1752009
Hornsby	412672.44	1794228
Watsons Bay	379042.23	1804963
Kiama	317467.18	1867454
Wagga Wagga	412701.30	1875915
Newcastle Beach	355044.89	1983491
Coogee	496857.75	1987431
Cronulla	505681.50	2022726
Batesmans Bay	426529.74	2031094
Armidale	431104.09	2062699
Palm Beach	549049.02	2111727
Campbelltown	550907.50	2118875
Grafton	335401.29	2122793
Bathhurst	444890.78	2128664
Griffith	472267.40	2146670
Bondi Junction	513988.38	2150579
Forbes	444820.91	2191236
Leeton	372365.62	2216462
Sydney City George Street	342472.95	2283153
Cootamundra	457518.80	2287594
Surry Hills	573485.00	2293940
North Sydney	577421.28	2405922
Randwick	607321.25	2429285
Lismore	415501.61	2429834
Sutherland	633860.24	2437924
Wollongong	512907.57	2442417
Bondi Beach	590640.96	2461004
Sydney City Darling Harbour	386086.13	2467004
Hurstville	605403.58	2471035
Newcastle City	473522.99	2485685
Penrith Riverfront	635595.84	2604901
Yass	508705.08	2608744
Chatwswood	637132.13	2627349
Narooma	486162.77	2671224
Sydenham	655231.44	2730131
Manly	707732.50	2830930
Blacktown	711694.81	2863963
North Sydney Bridge	690797.52	2878323
Penrith	695487.68	2885841
Ryde	699538.66	2926940
Parramatta City	721540.93	2945065
Sydney City Wooloomooloo	511696.44	2949259
Parramatta Racecourse	727407.94	2969012
Sydney City Circular Quay	543803.22	3021129
Byron Bay	684438.26	3111083
Pymble	859006.56	3579194
Grand Total	26753285.29	122720339

Row Labels	Sum of Annual Sales ($)	Sum of Restaurant Age (years)
NSW	122720339	1695.805613
Bondi Beach	2461004	28.61875428
Hornsby	1794228	28.89801506
Blacktown	2863963	28.92539357
Palm Beach	2111727	29.02121834
Manly	2830930	29.02121834
Wollongong	2442417	29.30595483
Campbelltown	2118875	29.42368241
Chatwswood	2627349	29.44284736
Cronulla	2022726	29.57700205
Bankstown	1547010	29.57700205
Hurstville	2471035	29.74948665
Richmond	1461039	29.86173854
Sydney City Darling Harbour	2467004	29.94113621
Albury	1658175	29.99863107
Sydney City George Street	2283153	30.01779603
Watsons Bay	1804963	30.19028063
Camden	1678646	30.2477755
Coogee	1987431	30.72689938
Narooma	2671224	31.12936345
Ryde	2926940	31.12936345
Lismore	2429834	31.18685832
North Sydney	2405922	31.20602327
Penrith	2885841	31.321013
Grafton	2122793	31.35934292
Randwick	2429285	31.37850787
Sydney City Circular Quay	3021129	31.57015743
Byron Bay	3111083	31.60848734
Batesmans Bay	2031094	31.62765229
Leeton	2216462	31.78097194
Bondi Junction	2150579	31.8384668
Bathhurst	2128664	32.10677618
Kiama	1867454	32.18069815
Sydenham	2730131	32.20260096
Newcastle City	2485685	32.37508556
Armidale	2062699	32.58590007
Surry Hills	2293940	32.79123888
Sutherland	2437924	32.85420945
Yass	2608744	32.91170431
Broken Hill	1749361	33.00752909
Wagga Wagga	1875915	33.10335387
North Sydney Bridge	2878323	33.12251882
Newcastle Beach	1983491	33.18275154
Parramatta City	2945065	33.29774127
Parramatta Racecourse	2969012	33.40999316
Penrith Riverfront	2604901	33.96577687
Pymble	3579194	34.65297741
Orange	1752009	34.71868583
Forbes	2191236	34.85831622
Cootamundra	2287594	35.10746064
Griffith	2146670	37.44832307
Dubbo	1540065	38.13552361
Sydney City Wooloomooloo	2949259	38.68856947
Nowra	1619142	39.41683778
Grand Total	122720339	1695.805613

Row Labels	Sum of Annual Sales ($)	Sum of Restaurant Age (years)
TAS	10713373	174.3052704
Launceston	1789855	35.18685832
Hobart City	1469960	30.80355921
Burnie	1832153	30.64750171
Hobart Harbourside	2637013	29.65366188
Richmond	2384987	29.61533196
Strahan	599405	18.39835729
Grand Total	10713373	174.3052704

Row Labels	Sum of Advertising (% sales)	Sum of Profit ($)
Broome	0	729221.82
Byron Bay	0	684438.26
Sutherland	0	633860.24
Sunshine Coast Beach	0	557419.52
Campbelltown	0	550907.50
Palm Beach	0	549049.02
Sydney City Circular Quay	0	543803.22
Geelong City	0	534801.54
Darwin Beach	0	506220.84
Alice Springs City	0	504555.60
Rockhampton	0	501454.08
North Canberra	0	493476.51
Melbourne City West	0	488491.68
Port Hedland	0	477080.16
Griffith	0	472267.40
Bundaberg	0	471578.40
Katherine	0	467517.78
Geraldton	0	448471.37
Camden	0	436447.96
Mt Gambier	0	433445.58
Wagga Wagga	0	412701.30
Cairns	0	410646.24
Ballarat	0	406657.44
Perth City River	0	404207.50
Bankstown	0	402222.60
Perth City North	0	372684.75
Albury	0	364798.50
Brisbane City	0	362357.20
Launceston	0	357971.00
Port Pirie	0	350563.70
Gold Coast Esplanade	0	335093.76
Perth City East	0	311925.00
Hobart City	0	293992.00
Darwin City	0	280516.95
Joondalup	0	225734.85
Manjimup	0	216109.41
Grand Total	0	15992690.67

Q.4.n:
Row Labels	Sum of Advertising (% sales)	Sum of Profit ($)
Manjimup	0	216109.41
Joondalup	0	225734.85
Darwin City	0	280516.95
Hobart City	0	293992.00
Perth City East	0	311925.00
Gold Coast Esplanade	0	335093.76
Port Pirie	0	350563.70
Launceston	0	357971.00
Brisbane City	0	362357.20
Albury	0	364798.50
Perth City North	0	372684.75
Bankstown	0	402222.60
Perth City River	0	404207.50
Ballarat	0	406657.44
Cairns	0	410646.24
Wagga Wagga	0	412701.30
Mt Gambier	0	433445.58
Camden	0	436447.96
Geraldton	0	448471.37
Katherine	0	467517.78
Bundaberg	0	471578.40
Griffith	0	472267.40
Port Hedland	0	477080.16
Melbourne City West	0	488491.68
North Canberra	0	493476.51
Rockhampton	0	501454.08
Alice Springs City	0	504555.60
Darwin Beach	0	506220.84
Geelong City	0	534801.54
Sydney City Circular Quay	0	543803.22
Palm Beach	0	549049.02
Campbelltown	0	550907.50
Sunshine Coast Beach	0	557419.52
Sutherland	0	633860.24
Byron Bay	0	684438.26
Broome	0	729221.82
Grand Total	0	15992690.67

Conclusion

The analysis that has been conducted by the evaluation of the collected data reveals the areas or regions where the business restaurant has been doing well and the particular areas where the revenues earned by the restaurants have not been satisfactory. The different facilities provided by the spreadsheet have made the entire analytical process easy to execute and understand. The pivot tables that have been used in the study help in the proper extraction of the data from a pool of information and facilitate the presentation of the data in the required format so that it can be interpreted and analyzed by the user efficiently (Bodie, Kane & Marcus, 2014).

The region that has obtained the highest amount of revenue in terms of sales is NSW. However, the region that has obtained the lowest amount of revenue in terms of sales is Tasmania. However, it should be noted here that the total number of seats in the restaurant that has been placed in NSW is 11043, while the total number of seats in the lowest revenue-generating restaurant is 1187. This means that the poor performance by the unit in Tasmania is not only due to the fact that the restaurant in Tasmania has not been functioning efficiently but also that the infrastructure or the capacity of the restaurant is very less. Thus, in order to increase the revenue generation by the Tasmanian unit the number of seats should be increased. Moreover, the number of restaurants in Tasmania has also been the lowest signifying the fact that the number of restaurants in Tasmania should also increase (Grant, 2016).

Another important observation that arises from the analysis is that the number of restaurants that engage in advertisements in NSW is 43 out of a total, of 53. However, the number of advertising restaurants in comparison to the total number of restaurants in the other regions has been high. This particular phenomenon indicates that the success of the restaurants do not depend on extensive advertisement campaigns but on the quality service provided by the facility. It is highly recommended that the business units focus more on the quality of service provided rather than extensive advertisement campaigning by business (Lisboa, Skarmeas & Saridakis, 2016).

However, the restaurants in Tasmania and other relatively low performing units should consider the utilization of the advertising campaigns in order to achieve the fullest utilization of its capacities.

The data quality issue that may arise from this particular analysis project is the availability of a common platform for the evaluation of the performance of the restaurants that belong to different regions. This means that in this study the performance of the restaurants have been analyzed on the basis of the revenue generated. However, increase in the number of restaurants will automatically increase the total revenue that has been derived by the region. On the other hand, the region having less number of restaurants will generate less revenue even if the resources are being optimally utilized. Therefore, a micro looks into the quality aspect of the restaurants belonging to different regions would have strengthened the quality of the results reflected by this report (Takata, 2016).

References

Bodie, Z., Kane, A., & Marcus, A. J. (2014). Investments, 10e. McGraw-Hill Education.

Grant, R.M., 2016. Contemporary strategy analysis: Text and cases edition. John Wiley & Sons.

Lisboa, A., Skarmeas, D., & Saridakis, C. (2016). Entrepreneurial orientation pathways to performance: A fuzzy-set analysis. Journal of business research, 69(4), 1319-1324.

Peregrine, V. G., Popp, J. B., Ishikawa, L., Furtado, J., Michaylov, S., Albright, R. L., … & Zhu, T. (2015). U.S. Patent No. 9,183,529. Washington, DC: U.S. Patent and Trademark Office.

Pindado, J., & Requejo, I. (2015). Family business performance from a governance perspective: a review of empirical research. International Journal of Management Reviews, 17(3), 279-311.

Prajogo, D. I. (2016). The strategic fit between innovation strategies and business environment in delivering business performance. International Journal of Production Economics, 171, 241-249.

Rosemann, M., & vom Brocke, J. (2015). The six core elements of business process management. In Handbook on business process management 1 (pp. 105-122). Springer Berlin Heidelberg.

Schaltegger, S., & Wagner, M. (Eds.). (2017). Managing the business case for sustainability: The integration of social, environmental and economic performance. Routledge.

Skipworth, H., Godsell, J., Wong, C. Y., Saghiri, S., & Julien, D. (2015). Supply chain alignment for improved business performance: an empirical study. Supply Chain Management: An International Journal, 20(5), 511-533.

Takata, H. (2016). Effects of industry forces, market orientation, and marketing capabilities on business performance: An empirical analysis of Japanese manufacturers from 2009 to 2011. Journal of Business Research, 69(12), 5611-5619.

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