Introduction:
As part of business studies, we must need to have knowledge on this subject. Today business environment are very dynamic, competitive and even complex and in order to survive and run a business successfully in this climate. we need to have sufficient experience and knowledge in term of management accounting which are related to business. And as part of it we need to develop focusing and need to go through all of the following.
TASK-01
1.1.1 A total cost statement for guildhall Ltd given below with different types of cost:
sale
315.840
Direct cost
Raw materials
75280
Wages of production workers
69180
Royalties paid to the designer of product
15110
Total direct cost
159750
Overhead
Salaries of maintenance staff
30950
Depreciation of plant and machinery
5000
electricity
4160
Sundry factory expenses
3020
43130
Total production cost
202880
Administration
Rent and rates
10290
Salaries of office staff
38250
Depreciation of office equipment
2400
Sundry of office expenses
1590
52350
Total cost
(255230)
Profit
60610
[P1]
1.1.2. The need for, and operation of, different costing methods:
Basically two main costing methods are unavailable under the operation of different costing methods:
Marginal Cost:
An accounting system in which is variable cost units and fixed cost are into also bed into cost units but whiten out in the profit and loss account of the period to which they volute
Industrial Costing:
Accounting system in which cost units are coasted into one main product there are deferent types of methods below
Process costing
Bath process costing
Service costing
Job costing
Contract costing
Different costing method
CC comment Corspotroration Batch process cost this industry is into manufacturing of batches of products.
Bengal oil refries:
Process costing- No of Batches
Cost
=Batch cost
Price 1 Price-2
In taut *** Out taut Nab *** Now on
H/M *** Op-1 Off ***
Nab *** Op-2
Off ***
Panther Pickles
Batch prepossess Marfa costing industry
3.
Selling price per unit= £210
Variable cost:
Labour (14Ã-6.8)=95.2
Royalties=9
Materials(20Ã-3.2)=64
A) Total variable cost per unit=168.2
Fixed cost=72000
Say number X unit need to produce to earn the organization a profit of £44000.
210X -168.2X-72000=44000
=) 41.8X=116000
=)X=2775.1196
X≈2775 UNIT.
B)
210Ã-41200-(168.2Ã-41200+72000)
=8652000-7001840
=1650160 [P2]
Work in Progress
cost
Completed toys
toys
% completed
Equvelent unit
Total Equvelent unit
Cost per toys
WIP valuation
Completed with valuation
Total cost per production
Direct materials
11500
20000
5000
100%
5000
25000
0.46
2300
9200
11500
Direct Labour
9000
20000
5000
50%
2500
22500
0.4
1000
8000
9000
Production O/D
18000
20000
5000
50%
2500
22500
0.8
2000
16000
18000
Total
38500
1.66
5300
33200
385001.1.3 Calculate costs using appropriate techniques: Work in progress valuation:
Cost per toy is 1.66
Valuation in progress is 5300
[P3]
1.1.4 Collect, analyse and present data using appropriate techniques:
Analysis of data is a process of inspecting, cleaning, transforming, and modelling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.
Data mining is a particular data analysis technique that focuses on modelling and knowledge discovery for predictive rather than purely descriptive purposes. Business intelligence covers data analysis that relies heavily on aggregation, focusing on business information. In statistical applications, some people divide data analysis into descriptive statistics, exploratory data analysis, and confirmatory data analysis. EDA focuses on discovering new features in the data and CDA on confirming or falsifying existing hypotheses. Predictive analytics focuses on application of statistical or structural models for predictive forecasting or classification, while text analytics applies statistical, linguistic, and structural techniques to extract and classify information from textual sources, a species of unstructured data. All are varieties of data analysis.
Data integration is a precursor to data analysis, and data analysis is closely linked to data visualization and data dissemination. The term data analysis is sometimes used as a synonym for data modelling, which is unrelated to the subject of this article.
The process of data analysis
Data analysis is a process, within which several phases can be distinguished:
Data cleaning
Initial data analysis (assessment of data quality)
Main data analysis (answer the original research question)
Final data analysis (necessary additional analyses and report)
Data cleaning
Data cleaning is an important procedure during which the data are inspected, and erroneous data are -if necessary, preferable, and possible- corrected. Data cleaning can be done during the stage of data entry. If this is done, it is important that no subjective decisions are made. The guiding principle provided by Adèr (ref) is: during subsequent manipulations of the data, information should always be cumulatively retrievable. In other words, it should always be possible to undo any data set alterations. Therefore, it is important not to throw information away at any stage in the data cleaning phase. All information should be saved (i.e., when altering variables, both the original values and the new values should be kept, either in a duplicate dataset or under a different variable name), and all alterations to the data set should carefully and clearly documented, for instance in a syntax or a log.[2]
Initial data analysis
The most important distinction between the initial data analysis phase and the main analysis phase, is that during initial data analysis one refrains from any analysis that are aimed at answering the original research question. The initial data analysis phase is guided by the following four questions:[3]
Quality of data
The quality of the data should be checked as early as possible. Data quality can be assessed in several ways, using different types of analyses: frequency counts, descriptive statistics (mean, standard deviation, and median), normality (skewness, kurtosis, frequency histograms, and normal probability (plots), associations (correlations, scatter plots).
Other initial data quality checks are:
Checks on data cleaning: have decisions influenced the distribution of the variables? The distribution of the variables before data cleaning is compared to the distribution of the variables after data cleaning to see whether data cleaning has had unwanted effects on the data.
Analysis of missing observations: are there many missing values, and are the values missing at random? The missing observations in the data are analyzed to see whether more than 25% of the values are missing, whether they are missing at random (MAR), and whether some form of imputation (statistics) is needed.
Analysis of extreme observations: outlying observations in the data are analyzed to see if they seem to disturb the distribution.
Comparison and correction of differences in coding schemes: variables are compared with coding schemes of variables external to the data set, and possibly corrected if coding schemes are not comparable.
The choice of analyses to assess the data quality during the initial data analysis phase depends on the analyses that will be conducted in the main analysis phase.[4] by Philip kotler
Quality of measurements
The quality of the measurement instruments should only be checked during the initial data analysis phase when this is not the focus or research question of the study. One should check whether structure of measurement instruments corresponds to structure reported in the literature.
There are two ways to assess measurement quality:
Confirmatory factor analysis
Analysis of homogeneity (internal consistency), which gives an indication of the reliability of a measurement instrument, i.e., whether all items fit into a one-dimensional scale. During this analysis, one inspects the variances of the items and the scales, the Cornbrash's α of the scales, and the change in the Cornbrash's alpha when an item would be deleted from a scale.
Initial transformations
After assessing the quality of the data and of the measurements, one might decide to impute missing data, or to perform initial transformations of one or more variables, although this can also be done during the main analysis phase.
Possible transformations of variables are
Square root transformation (if the distribution differs moderately from normal)
Log-transformation (if the distribution differs substantially from normal)
Inverse transformation (if the distribution differs severely from normal)
Make categorical (ordinal / dichotomous) (if the distribution differs severely from normal, and no transformations help)
Did the implementation of the study fulfil the intentions of the research design?
One should check the success of the randomization procedure, for instance by checking whether background and substantive variables are equally distributed within and across groups.
If the study did not need and/or use a randomization procedure, one should check the success of the non-random sampling, for instance by checking whether all subgroups of the population of interest are represented in sample.
Other possible data distortions that should be checked are:
dropout (this should be identified during the initial data analysis phase)
Item nonresponse (whether this is random or not should be assessed during the initial data analysis phase)
Treatment quality (using manipulation checks).[8]
Characteristics of data sample
In any report or article, the structure of the sample must be accurately described. It is especially important to exactly determine the structure of the sample (and specifically the size of the subgroups) when subgroup analyses will be performed during the main analysis phase.
The characteristics of the data sample can be assessed by looking at:
Basic statistics of important variables
Scatter plots
Correlations
Cross-tabulations[9]
Final stage of the initial data analysis
During the final stage, the findings of the initial data analysis are documented, and necessary, preferable, and possible corrective actions are taken.
Also, the original plan for the main data analyses can and should be specified in more detail and/or rewritten.
In order to do this, several decisions about the main data analyses can and should be made:
In the case of non-normal: should one transform variables; make variables categorical (ordinal/dichotomous); adapt the analysis method?
In the case of missing data: should one neglect or impute the missing data; which imputation technique should be used?
In the case of outliers: should one use robust analysis techniques?
In case items do not fit the scale: should one adapt the measurement instrument by omitting items, or rather ensure comparability with other (uses of the) measurement instrument(s)?
In the case of (too) small subgroups: should one drop the hypothesis about inter-group differences, or use small sample techniques, like exact tests or bootstrapping?
In case the randomization procedure seems to be defective: can and should one calculate propensity scores and include them as covariates in the main analyses?[10]
Analyses
Several analyses can be used during the initial data analysis phase:[11]
Univar ate statistics
Bivariate associations (correlations)
Graphical techniques (scatter plots)
It is important to take the measurement levels of the variables into account for the analyses, as special statistical techniques are available for each level:[12]
Nominal and ordinal variables
Frequency counts (numbers and percentages)
Associations
circumambulations (cross tabulations)
hierarchical log linear analysis (restricted to a maximum of 8 variables)
log linear analysis (to identify relevant/important variables and possible confounders)
Exact tests or bootstrapping (in case subgroups are small)
Computation of new variables
Continuous variables
Distribution
Statistics (M, SD, variance, skewness, kurtosis)
Stem-and-leaf displays
Box plots
Age group
Current account
Ordinary deposit account
High interest deposit account
0-24
522
207
---
25-44
1020
271
92
45-59
989
470
162
60-over
628
410
229
Total
3159
1358
483
(3159Ã-100)/5000
=63.18%
(1358Ã-100)/5000
=27.16%
(483Ã-100)/5000
=9.66%
From the above information we can see that maximum number of customer using current account and minimum number of customer using high interested deposit account. [P4]
TASK-02
1.2.1 Routine cost report for Guildhall Toys plc for four weeks in November 2009:
1.
Details
Week-1
Week-2
Week-3
Week-4
Sale
240000
300000
330000
360000
Actual unit produced
16000
20000
22000
24000
Budgeted unit produced
15500
19000
20000
21000
Variance
500
1000
2000
3000
Cost
120000
150000
190000
210000
ROCE
16%
100%
135.71%
140%
Hours worked
4000
4700
4850
5150
Capital employed
1500000
1500000
1500000
1500000
1.2.2 Calculate and evaluate indicators of productivity, efficiency and effectiveness:
2.
Efficiency
Production volume ratio:
formula
Week-1
Week-2
Week-3
Week-4
(Actual outflow / budgeted outflow)Ã-100
16000 Ã-100
15500
=103.22%
20000Ã-100
19000
=105.2%
22000Ã-100
2000
=110%
24000Ã-100
21000
=114.29%
Productivity
formula
Week-1
Week-2
Week-3
Week-4
Productivity=output / hour worked
16000
4000
=4 unit
20000
4700
=2.26 unit
22000
4850
=4.54 unit
24000
5150
=4.66 unit
Effectiveness
Budgeted
Actual
Week-1
15500÷4000=3.875
16000÷4000=4
Week-2
19000÷4700=4.043
20000÷4700=4.25
Week-3
20000÷4850=4.124
22000÷4850=4.536
Week-4
21000÷5150=4.078
24000÷5150=4.66
In terms of effectiveness we can say the company being effective in every week as the actual unit is bigger than budgeted. [P5, P6]
3.
1.2.3 The principles of quality and value, and identify potential improvements:
"A quality management principle is a comprehensive and fundamental rule / belief, for leading and operating an organisation, aimed at continually improving performance over the long term by focusing on customers while addressing the needs of all other stake holders".
The eight principles are-
1. Customer-Focused Organisation
2. Leadership
3. Involvement of People
4. Process Approach
5. System Approach to Management
6. Continual Improvement
7. Factual Approach to Decision Making and
8. Mutually Beneficial Supplier Relationships.
Potential improvement: Guildhall toys plc increase their sale by selling more unit of toys with a good quality. Minimizing the work hour of labours can decrease the cost and at the same time increase the profit. If Guildhall Toys plc can control their cost of production in a proper and systematic way they can make more profit.
The success of a biennial budget cycle would depend on whether lawmakers were able to separate budget and no budget issues in the way that proponents envision. Various practical hurdles could make separating the two types of issues difficult.
Biennial budgeting could make two major improvements to the budget process. First, it might give lawmakers and agency officials time to evaluate federal programs more effectively and help them carry out the requirements of the Government Performance and Results Act of 1993 (GPRA). Second, it could help ease the annual logjam of budget legislation that has contributed to recent difficulties in the annual appropriation process.
A biennial budget cycle would not come without costs. Members would need to weigh the potential gains from more time for oversight and a more efficient appropriation process against the potential drawbacks of weakened Congressional control of the budget, less accountable federal agencies, and a budget process that might be less responsive to changing conditions. [P7]
TASK-03
1.3.1 The purpose and nature of the budgeting process:
Business budgeting is a basic and essential process that allows businesses to attain many goals in one course of action. There are several goals that many businesses seek to achieve (or should be trying to work toward) when they create and implement a budget. These goals include control and evaluation, planning, communication, and motivation.
Control and Evaluation
Control and evaluation is the most important purpose of budgeting. Budgeting gives a chance to a company to have a certain degree of control over costs, such as avoiding many types of expenses to take place if they were not budgeted for, or assigning responsibility for these expenses. A budget also gives a company a benchmark by which to evaluate business units, departments, and even individual managers.
Planning
Planning is another primary purpose of budgeting. Budgeting allows a business to take stock of revenue and expenses from the previous period, and judge where the business will be in future periods. It also helps the business to add and remove products and services from its plan for the future period. The budgeting process of large organization may be completed by individual business units and compiled to form a master budget for the organization. Which will help the management to see the company's actual position and according to that a company can plan better.
Communication and Motivation
Another very important purpose of budgeting is communication and motivation. It allows management to communicate goals and to promote goal congruence so resources can be coordinated and focused in key areas. By involving employee in budgeting a company also can motivate its employee. While top-down budgeting does not accomplish this goal very effectively, participative budgeting can be motivating. When an employee is involved in creating his or her department's budget, that person will be more likely to strive to achieve that budget. In budgeting process we need to collect some information as well. They are-
Need to invest some time to create a realistic budget.
Collect historical information on sales and costs from last year if they are available only as a guide.
Create realistic budgets by using historical information, business plan and any changes in operations or priorities to budget for overheads and other fixed costs.
It's best to ask staff with financial responsibilities to provide with estimates of figures for your budget. [P8]
1.3.2 Appropriate budgeting methods and its needs:
Net budget: this budget is than the Gross Budget. It is the budget that spends the property tax. It does not include non-property tax revenue.
Labour budget: this is a Schedule for expected labour cost. Expected labour cost is dependent upon expected production volume (production budget)
Overhead budget: this budget shows the expected cost of all production costs other than direct materials and direct labour
Control budget:. he exercise of control in the organization with the help of budgets is known as budgetary control or control budget.
1.3.3 The budgets accounting to the chosen budgeting method:
Part A:
Month-1
Month-2
Month-3
Unit
Unit
Unit
Unit
Unit
Unit
Budget sells
5,000
5,200
5,400
Closing stock
1,250
1,300
1,400
Opening stock
1,200
50
1,250
50
1,300
100
5,050
5,250
5,500
Part B
Month 1
Month 2
Month 3
Production
5100
5250
5400
0.05kg
(5100*0.05)
(5250*0.05)
(5400*0.05)
255
262.50
272.50
Add opening stock
262.50
272.50
250
Less opening stock
250
262.50
272.5
Purchase KG
267.50
272.50
250
Material cost
500
500
500
133750
136250
12500
Part C
Direct labour budget
Month 1
Month2
Month3
Labour units
5100
5250
5450
Per unit
0.5
0.5
0.5
5100*0.5
5250*0.5
5450*0.5
2550
2625
2725
Part D:
Hour per month 2240 the overtime hour
Month 1
(2525 - 2240)
285
Month 2
(2625 - 2240)
385
Month 3
(2750 - 2240)
510
Month-1
Month-2
Month-3
Ordinary
285
(2,240 Ã- 10) =
22,400
385
(2,240 Ã- 10) =
22,400
570
(2,240 Ã- 10) =
22,400
Overtime
15
4,275
15
5,775
15
7,650
26,675
28,175
30,050
Part E
Budget overhead interest rate for each month
Month1=12500/5100
Etch month per units =2.45
Month2=12500/5250
Etch month per units = 2.58
Month 3= 12500/5100
Etch month per units = 2.29 [P9, P10]
1.3.4 Cash budget for guildhall traders:
Details
January
February
March
April
May
June
Inflow
Cash sale
Sale of machinery
Loan
30000
32000
50000
34000
36000
35000
38000
40000
Total inflow(A)
30000
82000
34000
71000
38000
40000
Out flow
Salaries
Purchase
Rent
Electricity and other utilities
Machinery payment
Loan payment
5000
5000
1000
5000
6000
1000
1000
5000
7000
1000
60000
4000
5000
8000
1000
1000
4000
5000
9000
1000
4000
5000
10000
1000
1000
4000
TOTAL OUT FLOW(B)
11000
13000
77000
19000
19000
21000
NET CASH FLOW(A-B)
19000
69000
(43000)
52000
19000
19000
ADD OPENING CASH BALANCE
8453
27453
96453
53453
105453
124453
CLOSING BALANCE
27453
96453
53453
105453
124453
143453
[P11]
Task-04
1.4.1 Variance, possible cause and corrective action of the cash flow of guildhall Books Limited given below:
Actual (£)
Budget(£)
Total variance(£)
Possible cause
Recommendation
Receipts from debtors
106000
132000
-26000
Week debt collection
Need to strong debt collection department
Payment to supplier
(79000)
(70000)
-9000
Production wages
(17500)
(17000)
-500
Production hours was more than budget
Need to control production hours
Production expenses
(1500)
(1000)
-500
More expense on production line, waste etc.
Need to control production line properly.
Selling expenses
(3400)
(3600)
200
Keep it up.
Administration cost
(4100)
(4100)
0
Good control on administration cost
Dividend
(20000)
-20000
It wasn't budgeted
Any kind of possible cash flow should be budgeted.
Net cash flow
(19500)
36300
-16800
This figure is negative because most of the figure of actual was more than budgeted.
Need to have a good control between and budgeted and actual inflow and outflow.
Opening cash balance
10000
10000
0
Closing cash balance
(9500)
46300
-36800
Because of having negative actual net cash flow.
[P12]
1.4.2 An operating Statements reconciling budgeted and actual results:
Details
Amount(£)
Budgeted Closing cash balance
46300
Less receipt from debtors
(26000)
Less payment to supplier
(9000)
less Production wages
(500)
Less Production expenses
(500)
Add Selling expenses
200
Less Dividend
(20000)
Actual closing balance
(9500)
[P13]
1.4.3 Report findings to management in accordance with identified responsibility centres:
Managerial accounting, or management accounting, is a set of practices and techniques aimed at providing managers with financial information to help them make decisions and maintain effective control over corporate resources. For example, managerial accounting answers such questions as: The practical role of managerial accounting is to increase knowledge within an organization and therefore reduce the risk associated with making decisions. Accountants prepare reports on the cost of producing goods, expenditures related to employee training programs, and the cost of marketing programs, among other activities. These reports are used by managers to measure the difference, or "variance," between what they planned and what they actually accomplished, or to compare performance to other benchmarks.
For example, an assembly line supervisor might be interested in finding out how efficient his/her line is in comparison to those of fellow supervisors, or compared to productivity in a previous
Time period. An accounting report showing inventory waste, average hourly labour costs, and overall per-unit costs, among other statistics, might help the supervisor and superiors to identify and correct inefficiencies. A detailed report might evaluate the assembly line data and estimate trends and the long-term effects of those trends on the overall profitability of the organization. [P14]
