Unit 6 Business Decision Making Sample Assignment

Programme	Diploma in Business
Unit Number and Title	Unit 6 Business Decision Making
QFC Level	Level 5

INTRODUCTION

This assignment consists of 4 broad tasks relating to Business Decision Making to hone the skills relating to:

• relevant data collection and constructive usage of the collated data, as well as
• developing skills in information technology, which would be appropriate to the needs of manipulation of crucial data and
• how to effectively present meaningful information, based on the background research carried out andin order to make timely and error-free business decisions.

Task 1

P1/2.Creationof plan for the collection of data for research on Sainsbury’ sand present the survey methodology and sampling frame used

To begin with, any research aims at discovery of facts or relationships, hitherto unknown or not recognised. Collecting relevant data would always be the cornerstone of a valid research proposal. The question requires one to plan suitable methodology and technique with the view to validate certain research questions on Customer satisfaction levels relating to Sainsbury, the well-established retail chain in the UK. The specific focus would be to bring out the Values, Culture, Commitment to operational excellence, Customer service quality, and fairness in prices that Sainsbury’s ostensibly boasts of maintaining high standards in.
Since theaims are clearly defined, planning an appropriate survey methodology should enable coverage of, as large a population base as possible, in order to ensure a widespread representation.
Primary data collection is mostly carried out through surveysusing Questionnaires and Interviews.  Unlike interviews I think, using a questionnaire in this research, would generate a higher level of objective and concise data, over all areas of scrutiny within the research.
Also, since various qualitative aspects relating to customer satisfaction levels of Sainsbury’s, client perception on price level maintenance and cultural and value upholding, are being researched about, a questionnaire would render itself to intelligent, well designed and close-ended questioning.  In order to reduce respondent impatience, some techniques used were:

• Dichotomous question inclusion of the Yes/No variety
• Relative ranking and ranking scales
• Naming customer preferences etc.

At all points, the ease with which data collected could lend itself to useful analysis and valid conclusions, was kept in mind.
A sampling frame refers to the population or units from which the sample respondents are drawn. While Random Sampling would have made the exercise truly objective, it would be better if a Stratified Sample were to beused, for a homogeneous, segmental representation.
For the purpose, the UK Electoral roll voter listing will be utilised. While this listing has approximately around 46 million voters, the same would be stratified in the following manner, to make a suitable frame:

• The Female: Male ratio would be kept at 8:10 within the sample respondents, similar to the national ratio
• 5 large sized outlets of Sainsbury would be chosen for the survey and the voters within their catchment area would be shortlisted, from the above
• From this smaller gender-wise list, a random number generator would be used to bring down the sample size of each to make up a total sample size of 100 per outlet.

The advantage of the electoral voting list was the fact that it would be an up-to-date list minimising blind ends, having current contact information and demographic details such as age, contact details etc. would be available for in-depth analysis, if need be, at a later stage of research.

P3.Design of Questionnaire

Questionnaire

Name of Respondent: __________________ (Optional)

City: ________________                   Gender: Male / Female                        Age:____years (Optional)

(e.g. Food, clothing, Toys & Games, CDs & books etc.

1 Highest expense
2 Second highest
3 Third highest

Q4. Tick the applicable statement(s)

1. I shop is any supermarket I find convenient
2. I usually go to the nearest supermarket
3. I buy some items, specific to a particular supermarket
4. I am specific about shopping mainly at Sainsbury’s
5. I rarely go to any other supermarket other than Sainsbury’s
6. None of the above

Q8.How would you rate the decor and ambience while shopping in this Sainsbury’s? (Highest rating = 1)

Q11. Can you please rank the following in order of importance to you? (Very important to me = 1)

Q12. Any other comments?

                        Thank you for your time and feedback. Hope you have a great day!

Data protection issues and Ethical considerations relating to the research:

In the UK, the Data Protection Act 1998 imposes a legal obligation on people to protect handled personal data and identities. Further, in line with the provisions of the Act, it would be required to make participants aware of the identity of the researcher, purpose of the research, any potential disclosure of data collected and explicit consent for the same needs to be obtained from them. Such information could be shared with respondents as an introduction or be part of surveys such as questionnaires.
The researcher also bears the burden of representing information published in the research, in a truthful manner. He or she should not misrepresent or hide observed phenomena, but must report observations even if it contradicts the research intent and hypothesis. A high degree of openness in conducting the research would enable the researcher to benefit from divergent views, which would only add depth and high credibility to the emerging conclusions, making the research defensible and robust.  These are the ethical expectations from high quality papers, which reflects on the organisations and behaviour or individual’s reputation, within the academic community.

Task 2

P4/5/6/12. Summarization of DataUsing Representative Values and Measures of Dispersion

Averages are considered to be a meaningful method of identifying representative values in a data set and are also measures of central tendency. The most useful among the averages include the Arithmetic Mean, Median and the Mode. In case of the performance highlights of the 2 competitors i.e. Sainsbury’s and Tesco, the various averages can be summarised as follows:           

(£ m)

Sales	Arithmetic Mean	Median
Sainsbury’s	14,760	16,061
Tesco	36,312	33711.5
Operating Profit
Sainsbury’s	591	656
Tesco	2,091	2,091

Here, since almost all Sales and Operating profit figures are unique in every year in both companies, there is no real sense in looking at Mode (most frequent value) as a representation for the data set.Sales or the top line in a company is the leading indicator of growth of business event. With turnovers almost 2.5 times that of Tesco’s, Sainsbury’s leads the field enjoying a higher market share than Tesco.
Sales or the top line in a company is the leading indicator of growth of business. With turnovers almost 2.5 times that of Tesco’s, Sainsbury’s leads the field enjoying a higher market share than Tesco.
When the Operating profit is compared with the Sales of the company by looking at the Operating Profit margin, the picture shows:

Company	Operating profit margin    (Whole period 1988 to 2012)	Operating profit margin (Comparable 16 years - 1997 to 2012)
Sainsbury’s	4.00%	3.33%
Tesco	5.76%	5.76%

The above numbers indicate that while Sainsbury’s may command a higher market segment, Tesco shows a greater profitability, i.e. higher return on sales, better cost control over the historical period tracked.
Measures of dispersion refer to various indices which tell you how spread out (or dispersed) a data population or sample is, in a quantitative manner. Most commonly used indices are Standard Deviation, Range and the IQR or Interquartile range.
The summary of data on the basis of means of dispersion, is given below:
Range being the simplest measure, it gives a very basic idea of dispersion in a data set.

Range (£ m)	Sales	Opr. Profit
Sainsbury’s	17,293	1,025
Tesco	49,555	774

It can be concluded that in Sales, Tesco shows greater dispersion than Sainsbury’s while in Operating Profit Sainsbury’s has a wider range compared to Tesco. However, it must be kept in mind that the number of years being compared are not the same (25 for Sainsbury’s as against 16 for Tesco) and one cannot meaningfully conclude a trend from this. When the same 16 year period is compared:

Range (£ m)	Sales	Opr. Profit
Sainsbury’s	7,982	1,025
Tesco	49,555	774

Here, one can reasonably conclude that Tesco’s Sales have grown exponentially compared to Sainsbury’s, while Sainsbury’s operating profits have done commendably better than Tesco’s. This does not say anything about the industry-wise comparison, however, but only relative performance of the two companies.

Standard Deviation	Sales	Opr. Profit
Sainsbury’s	4,866	230
Tesco	16,386	1,113

Standard deviation is a measure of how concentrated the data is around the mean and in many cases, the smaller the standard deviation the better the performance, as for example in case of a manufacturing outfit which measures quality of its products through repeated data measures which may confirm quality standards or failures leading to rejections. However, in this study, when comparing performance or growth over many period of years, a small figure would basically indicate stagnation or lack of growth and not found to be desirable.

P7/12. Identification of Quartiles

The 3 significant quartiles of Sales and Operating Profit variables for the two companies are listed below:                                                                        (£ m)

		Lower Quartile (25th)	Median (50th)	Upper Quartile (75th)
Sales	Sainsbury’s	11,224	16,061	18,206
	Tesco	22,169	33,712	48,948
Operating Profit	Sainsbury’s	520	656	756
	Tesco	1,132	1,844	2,886

 

Identification of quartiles help in quantifying scatter of data and is a useful technique in assessing the relative standing of an individual within a group. It can be thought of as a method of ranking and 25^th percentile implies that 25% of the values lie below this level and another 75% above it. The difference between the 75^th and 25^th percentiles signifies the IQR. The median is the half way mark and half the values are spread out on either side of this percentile.
In financial growth within an industry (i.e. like the given data), the quartiles may help is indicating whether the growth over the time frame considered, has been steady or sporadic and may lend itself to competitor comparisons. For example, in case of Sainsbury’s (Sales), the IQR or difference between the successive quartiles are: 4,837 and 2,145 while the same difference in case of Tesco are: 11,542 and 15,237 respectively. This would indicate that there was more consistent growth in case of sales performance by Sainsbury’s and by comparison, small but reducing growth in case of Tesco sales.
Thus dispersion indices also help comparison not only in case of studies within a population group, but also amongst competitors.

1. Estimate the correlation coefficient between sales and operating profit for Sainsbury’s and Tesco respectively. For each business, comment on the possible relationship between these variables.

Correlation coefficient(CC) is a number which can identify if there is a relationship between two sets of data and if so how strong the relationship is and in which direction. Thus if we were to consider  the sales data and its movement vis-a-vis Operating Profit of Sainsbury’s, by calculating this value(CC), we could assess if the two are moving in tandem or in opposite directions or somewhere in between i.e. relative strength or weakness of relationship can be assessed.
The CC of the two variables when estimated shows the following picture:

	Sainsbury’s	Tesco
Correlation Coefficient (CC)	0.32	1.00

• In case of Sainsbury’s, 0.32 neither near 0 nor near  +1 and we may conclude that there exists a very weak positive correlation between the company’s sales figures in relation to its profits, which implies a random indifference between the two company profit figures, otherwise called a non-linear relationship.
• Normally any correlation greater than 0.8, can be called a strong one.
• In case of Tesco however, the CC is exactly 1 indicating that there was perfect correlation between its sales and profits. This implies that Tesco strategy would be looking towards driving up their sales, which would lead to automatic profit generation, in the future. 
• This may also imply that Tesco is running its operations in a very efficient manner and all it has to continue doing is to concentrate on its marketing initiatives and not so much on its operational efficiency / cost control.

Task 3

P8/12. Statistical Graphs

Statistical graph I - scatterplot

• The graph shows a steady increase in the Sales grow of Sainsbury’s, except during the years 2004 to 2006, when there was a fall in sales from around £ 18,000 m to £ 15,000 m (17%), after which there has been a steady recovery till date.

• Operating profits show a more erratic path with major movement both ways (i.e. negative and positive growths) in successive years.
• However, the sales dip during the years 2004 to 2006 is echoed with sympathetic drops to the operating profit as well. This would be natural as adverse sales figures would have a negative influence on profits of the company.

Statistical graph II - histograms

• The Sales figures of Sainsbury’s is graphically plotted in the form of a Histogram. This method of representation helps in understanding the frequency distribution of the underlying data which is a ‘continuous data’ through its shape.
• This kind of graph also allows one to identify any extreme asymmetries or distortions (skewness or outliers).

 

Sainsbury Profit

Tesco Sales

Tesco Profit

 

Statistical graph III – cumulative frequency curve

• Cumulative Frequency Curves are used to study the growth rate of a base data through accumulated frequencies.
• Further, such graphs are useful in estimating the quartiles and the median which help in measuring extent of spreads through rankings and also in identifying and eliminating extreme values, which cause distortions.

P9/12. Create Trend lines for the Sales and Operating Profit and Estimate Sales

Estimation of Sainsbury’s Sales for year ended 2013

Estimated 2013 yearend Sales for Sainsbury’s, based on trend line is £ 23,000 m.

The trend line in this case does not pass through quite a few of the plotted points and hence appears to be further away from the group data. In this case the Coefficient of determination (r²) is likely to be low (say below 0.50) which implies that the estimation may not be very successful.

Estimation of Tesco Sales for year ended 2013

Estimated 2013 yearend Sales for TESCO, based on trend line is £ 66,000 m.

As the trend line passes very close to most of the points plotted, the r2 is likely to be > 50% which makes the predictions more reliable and certainly level high.

Estimation of Sainsbury’s Operating Profit for year ended 2013

Estimated 2013 year end Operating Profit for Sainsbury’s, based on trend line is £ 650 m.

This trend line exhibits a great degree of uncertainty with a high number of points appearing to be outliers, making the estimation less certain of proving successful.

Estimation of TESCO Operating Profit for year ended 2013

Estimated 2013 year end Operating Profit for TESCO, based on trend line is £ 4000 m.

This appears to be a very strong trend line in close congruence with most of the points making it very easy to all variations

Sainsbury’s - business report for top management

Key Highlights in performance

• Highest level of Operating profit achieved so far, has been in the year 2012 in excess of £7,500 m
• Return on Equity of 11%
• Debt/Equity as low as 0.67
• Market capture to the tune of 35%

Threats we may face in 2013

• Reduction in consumer spending
• Declining operating efficiency
• Reducing Net Profit Margin of 2.63%
• Competition in pricing
• Lower purchasing power of the £

Opportunities

• Web based advertising
• Cross selling via Finance & Insurance business contacts
• New Suppliers from Africa and Australia
• Relationship building opportunities

Targets set for 5 year period (2013 to 2018)

• New outlets of 500 stores
• Raising market share to 40%
• Diversification into online clothing business
• Increasing Loyalty Schemes’ Memberships

3.2 Business presentation

 

 

 

 

 

 

 

 

 

 

 

 

Task 4

 Part A:

P13. Critical Path

• To begin with the dependencies are created through identification of predecessors:

  Activity network

 

                                 The Critical Path is identified as B-C-F-G

P14/12. Calculation of Cost of Capital/ IRR 

Q2. Estimating IRR by Linear Interpolation

 

Q3.Calculation of internal rate of return using excel

Q4. Memorandum report

 

(Amount is £)	NPV when cost of capital is 10%	NPV when cost of capital is 60%
PROJECT A	45,885	-5,725
PROJECT B	34,161	-16,809

• A project adds wealth to the company and can be accepted only when its Net Present Value is positive.  From this point of view, both the projects have a positive NPV at a discounting rate of 10% and are worthwhile.
• However both Projects’ NPVs turn negative when the discounting rate is higher at 60% and need be rejected at this rate.
• In case of mutually exclusive projects, Project A would be preferred as it has a higher NPV when considering 10% as cost of capital.Based on the above, in the instant case the company would be making the right decision if they chose Project A over Project B as :IRR(A) = 50% > IRR(B) = 34%

Hence I recommend that the company invest in Project A over Project B, if the two are mutually exclusive ones.

Conclusion

The 4 key tasks have been completed in keeping with the requirements of the brief and has made use of appropriate applications such as power point and excel to forecast, present and communicate the emergent findings relating to the various business situations visualised in the assignment.

References

Collis, J & Hussey, R (2003), 2^ndEdn., Business Research- A practical guide for undergraduate and postgraduate students. New York, Palgrave Macmillan.
Coombes, H (2001) Research using IT. New York, Palgrave.
Dawson, C ( 2007), 3^rdEdn,  A practical guide to Research Methods, Oxford, How To Books Ltd.
Easterby-Smith, M, (2002), 2^ndEdn., Management Research –An introduction
Jankowicz, A ( 1991) Business Research Projects for Students, St. Edmunds, St. Edmundsbury Press Ltd.

Lund Statistics (2013) Histograms (Online) https://statistics.laerd.com/statistical-guides/understanding-histograms.php [Accessed on 4th March 2014].