Operations Management: Capacity Management and Forecasting Demand

This document discusses capacity management and forecasting demand in operations management. It covers the concepts of design capacity, effective capacity, utilization, and efficiency. It also explores short-term and long-term strategies for Dough Bakery. Additionally, it provides insights into forecasting techniques and recommendations for demand forecasting.

OPERATIONS MANAGEMENT
CASE STUDY ASSIGNMENT
Dough Bakery

1
Table of Contents
Introduction:..................................................................................................................2
Part A: Capacity Management and Forecasting demand............................................2
1.2 Definition and explanation:..................................................................................2
1.3 Calculation and explanation:...............................................................................4
1.4. Short term and long term strategies for Dough Bakery:....................................4
Question 2: FORECASTING AND DEMAND...............................................................4
2.1 Purpose of Forecasting.......................................................................................4
2.2 Simple Moving Average (3 months)....................................................................4
2.3 Line Charts of data..............................................................................................6
2.4 Forecasting Error.................................................................................................7
2.5 Recommendation................................................................................................8
PART B: Production Planning and Supply chain management...................................9
Question 3: Productivity................................................................................................9
3.1 Single Factor Productivity...................................................................................9
3.2 Multi factor productivity.......................................................................................9
3.3 Overall productivity..............................................................................................9
Question 4: INVENTORY MANAGEMENT..................................................................9
4.1 Strategic importance of Inventory Management:................................................9
4.2 Overview of ABC analysis.................................................................................10
4.3 EOQ MODEL.....................................................................................................14
Question 5: Material Resource Planning:...................................................................15
Benefits for the implementation of Material Resource Planning for Dough Bakery15
Question 6: Integrated Supply chain management....................................................16
Integrated supply chain and inventory management for Dough Bakery:................16
Conclusions:...............................................................................................................17
References:................................................................................................................18
Appendix:....................................................................................................................19

2
Introduction:
Operation management has become an essential factor in attaining success for
sustaining in ling rum. However, the nature of the organization has gone through
several phases of shifts and changes to integrate the contemporary operation
management policies and practices for better performance and improved efficiency
to attain competitive advantage in the market. The study has incorporated initially
with the concept of capacity management followed by the supply chain and inventory
management process and determination using some real-life example as extracted
from the case study of Dough Bakery.
Part A: Capacity Management and Forecasting demand
1.1
Capacity management refers to the measurement of the company regarding the
exact capacity of production and delivery of the services. Therefore, capacity
management forecasts the production amount that the company would be capable in
producing and deliver to its customers. In the opinion of Harris, Intelligence &
Healthcare (2017), capacity management also assists the production department of
a company to restrict the production according to the capacity of generating products
and services along with warehousing those products for future sales. Moreover,
capacity management also assists the operational team to trim down the production
cost through reducing wastage of material and producing excess and idle products.
Managing capacity of an organization is an essential skill to improve efficiency in
terms of maximizing profitability against the minimal or optimal investment of the
materials and finance.
1.2 Definition and explanation:
Design capacity:
The Design capacity is the maximum output that a system would generate against
certain inputs in the presence of a standard condition for the production. In most of
the organizations, the design capacity is straight forward in nature. Design capacity
sometimes includes the process of capacity planning as it defines the design of the
system to determine the maximum capacity of a system in producing output based
on the inputs including labor, power, materials, and parts. In case improving capacity
is not always a simple concept of increasing input as executing so would overload
the production leading to reduce the quality of the output.
Effective capacity:
Unlike the design capacity, the effective capacity refers to the expected productivity
or output of a system based on its current operating constraints. In a system of an
organization, the effective capacity is expected to be less than the design capacity
as the facility may have been designed for the earlier version of the products rather
than designing for the latest version of the products and services. It is always
observed that comparatively less capacity and production in a system possesses the
highest efficiency rather than engaging the system in producing the highest
maximum output.

3
Utilization:
Following the previous two definitions and concepts, utilization would be referred to
as the actual input of the production constraints, incorporated in producing the
optimal output. In other words, utilization would be referred to as the employment of
material in its actual amount and means to generate the expected and maximum
output projected. In most of the cases, utilization would be determined as the ratio of
design capacity.
Utilization = Actual output / Design capacity
Moreover, utilization would also be termed as the ratio of the design capacity where
the expression would be represented as Utilization = (hours actually worked /.
Available hours) X 100%
Efficiency:
Efficiency is also accounted as the measure for the production to determine the
capability of a facility to generate output. According to Dolinayova, Kanis & Loch
(2016), efficiency refers to the parameters of an organization to determine the
capacity efficacy of an enterprise in the production and delivery of the products and
services. Efficiency would also be termed in the form of expected capacity
represented as follows:
Efficiency = Actual Output / effective capacity
Thus, efficiency in the capacity means would also be termed as the actual output as
a percentage of effective capacity and thus, represented further as
Efficiency = (Actual rate of production / standard rate of production) X 100%
These determinations are important for the production manager and operation
manager to gather knowledge on the expected output of a facility or the process.
1.3 Calculation and explanation:
a) Company is using 80% efficiency in the year 2017
Efficiency = Actual Output / effective capacity
80% = 1,242,920 / effective capacity
Effective capacity = 1,242,920 X 100 / 80
= 1553650
Utilisation = Actual output / Design capacity
= 1,242,920 / 1553650 = 80%
b) Efficiency = Actual Output / effective capacity
= 113,067 / 129471 = 87.33%
According to the given information the efficiency has been calculated on the 2018
data. Here, the increasing of capacity would impact on the productivity of the

4
company based on the effective capacity. The current problem has been arisen due
to increase in capacity of production, as better use of machineries has been
executed trough reducing the product quality. The increasing demand of loaves has
been enforced to plan producing 1400 unit per day and therefore, reduced the quality
of the products.
1.4. Short term and long term strategies for Dough Bakery:
In the case of the short term strategy, Dough Bakery would develop good reward
management to reduce the staff turnover during the transformation phase in terms of
increasing capacity.
Moreover, in the case of the long term suggestions, a hike in capacity in production
will be the strategies to be adopted to gain a competitively better position in the
market.
Question 2: FORECASTING AND DEMAND
2.1 Purpose of Forecasting
The main aim of forecasting or anticipating is to predict the trend of sales or demand
so that the forecast planner can provide the relevant information to the other
departments of the organization. This technique utilizes historical or past data for
predictive analysis to estimate and allocate future expenses. The techniques used
for this purpose are moving averages, exponential smoothing, trend analysis, etc.
2.2 Simple Moving Average (3 months)
The Simple moving average is the most common technique of forecasting, where the
sales data or the demands are taken based on moving average. Here, for Dough
bakery for May, the sales are forecasted by taking the average sales of February,
March, and April. The sales figure or Feb 2018 is forecasted.
3 weeks moving average
Month Sales
Forecas
t
Feb 87319
Mar 90092
Apr 92140
May 100137 89850
June 103087 94123
July 104026 98455
Aug 105896 102417
Sep 108084 104336
Oct 109579 106002
Nov 111300 107853
Dec 112193 109654
Jan 113067 111024
Feb 112187

5
b) the Weighted moving average is another technique of demand forecasting. Here,
the given weights are assigned to the actual sales data. In the question, the weights
are given as 0.5, 0.3 and 0.2. The maximum weighted is assigned to the most recent
month or year. For forecasting the sales of May, 0.5 weight is assigned to the sales
data of April, 0.3 is assigned to march, and so on.
3 Months weighted moving Average
Month Sales
Forecas
t
Feb-17 87319
Mar-17 90092
Apr-17 92140
May-17
10013
7 90561
Jun-17
10308
7 95729
Jul-17
10402
6 100013
Aug-17
10589
6 102967
Sep-17
10808
4 104773
Oct-17
10957
9 106616
Nov-17
11130
0 108394
Dec-17
11219
3 110141
Jan-18
11306
7 111402
Feb-18 112451
2.3 Line Charts of data
3 Months simple moving average

6
Feb Mar Apr MayJune July Aug Sep Oct Nov Dec Jan Feb
0
20000
40000
60000
80000
100000
120000
Sales
Forecast
3 Months Weighted Moving average
Feb-17
Mar-17
Apr-17
May-17
Jun-17
Jul-17
Aug-17
Sep-17
Oct-17
Nov-17
Dec-17
Jan-18
Feb-18
0
50000
100000
150000
200000
250000
Forecast
Sales
2.4 Forecasting Error
a) The main objective behind the error forecasting is to identify the deviations
between the actual data and the forecasted data. It is obtained by using the formula
(At- Ft), that is actual data less forecasted data.
b) Mean Actual Deviation (MAD) is the average of the actual deviations. The
summation of (At- ft) is divided by the number of years or months taken for the
calculation. It is ascertained using the formula (At- Ft)/n.
MAD for 3 months simple average
Month Sales
Forecas
t Error
Feb 87319
Mar 90092
Apr 92140

7
May 100137 89850 10287
June 103087 94123 8964
July 104026 98455 5571
Aug 105896 102417 3479
Sep 108084 104336 3748
Oct 109579 106002 3577
Nov 111300 107853 3447
Dec 112193 109654 2539
Jan 113067 111024 2043
Feb 112187 43655
MAD 4365.5
3 months weighted average
Month Sales
Forecas
t Error (At-Ft)
Feb-17 87319
Mar-17 90092
Apr-17 92140
May-17
10013
7 90561 9576
Jun-17
10308
7 95729 7358
Jul-17
10402
6 100013 4013
Aug-17
10589
6 102967 2930
Sep-17
10808
4 104773 3311
Oct-17
10957
9 106616 2963
Nov-17
11130
0 108394 2906
Dec-17
11219
3 110141 2053
Jan-18
11306
7 111402 1665
Feb-18 112451
∑Error =
36774
MAD= 3677.4
2.5 Recommendation
Thus, from the above calculations, it is recommended that Dough Bakery should
follow 3 months weighted moving average method for the demand forecasting
purpose as the Mean Actual Deviation or MAD is less than the Simple average
method.

8

9
PART B: Production Planning and Supply chain management
Question 3: Productivity
3.1 Single Factor Productivity
Single Factor Productivity is the ratio of total output concerning one input factor.
Here, the output is taken as the production capacity, and the energy consumption is
taken as the input. For 2017, the single factor productivity ratio is Labour hours /
Energy, that is 1500/3000 = 50%, and for 2018, it became 1500 /2750, which equals
54.5%. It indicates that the single factor productivity had increased in 2018.
3.2 Multi factor productivity
Multi factor productivity is the ratio of output concerning every input. Thus, by
considering the energy consumption as the input, the multi factor productivity is
shown below:
2017 2018
%
chang
e
Productivit
y 50 55 9.09
Labour 11.7 11.8 1.30
Cap
invested 500 655 30.91
3.3 Overall productivity
If the overall productivity improved 15% or more, then the production is assumed to
go up by 15%, that is the new production for 2018 will be (1500 + 115%), which
equals to 1725. Again, considering energy as the input, single factor productivity will
be 1725/2750, which is 62.5%.
Question 4: INVENTORY MANAGEMENT
4.1 Strategic importance of Inventory Management:
The significance of inventory management is that the inventories are considered as
the most important and valuable asset of the business. It holds more than 50% of the
capital investment. Good inventory management helps in reducing the cost for the
organizations. Again, the inventories can hamper the production process and can
also become the reason for customer loss or dissatisfaction in the situation of stock
outs. Achieving a low-cost strategy is almost impossible without good inventory
management. Every business has planning and control systems, which deal with the
inventories. The companies who deal with the physical products, the decision of
whether to manufacture or to outsource is one of the utmost important. For Dough
bakery, the inventories are the breads and the cakes in which they are deals. The

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functions of inventory management are to protect the organization from the
inflationary effects and also from an upward price change. It also acts as the hedge
against risk. It also helps in grabbing the advantages of quantity discounts as the
bulk purchase helps in reducing the cost per unit or in the delivery charges. Having a
sound inventory management system helps in planning and performing some
production activities both economically and independently. It also helps in
maintaining the smooth flow of production activities. Inventory management is also
important in utilizing existing resources fully. There are four types of inventories,
Namely, Raw material inventory, Work in progress inventory, Maintenance inventory,
and the finished goods inventory. Raw material inventories are those inventories,
which are procured but had not entered in the production process yet. The
mentioned approach is to minimize the variation of suppliers from the view point of
quality, quantity, and delivery time. Decoupling of suppliers from the process of
production can be done through the use of this inventory. Work in progress
inventories are those inventories, which lie in between the raw material phase, and
the finished goods phase. In simple words, those inventories are neither raw
materials nor the finished goods. This inventory exists because of the cycle time.
Maintenance inventories are also known as for repairs and operating inventories.
These inventories are necessary for keeping the process and the machineries
productive. They exist as the maintenance time and repair timing of some
equipments under uncertainty. Lastly, the finished goods inventories are the final
inventories, which are market ready and awaiting shipment. These inventories can
also be stored in warehouses due to the uncertain market demand. Therefore, the
overall objective of managing inventory is for maintaining and balancing inventory
and customer services. Holding inventory also aims at availing the advantage of
price fluctuations.
4.2 Overview of ABC analysis
a) ABC analysis stands for Always Better Control analysis. It divides the hands-on
inventories into three categories based on the annual turnover. The analysis is an
inventory application, which is based on the Pareto 20-80 rule. The inventory policies
are set which focuses critical parts of inventory and not on many insignificant parts.
“A” category inventory is those, which contribute more than 75% of total turnover
values by using only 10-15% of the total items. “B” category inventory are those
inventories which contributes near about 15% of total revenue by using 35-40%
items and “C” category are those goods which contribute 10% of total revenues
utilizing more than 50% of inventories.
For A category goods, strict handling policy, and timely reviews are required. For B
category goods, average restriction and medium frequency of monitoring are
needed, and for C category inventories, casual monitoring or infrequent visit is
enough. The percentages may not match exactly; the main objective is to segregate
the important from the less important objectives. The two benefits of ABC analysis
are:
It helps the inventory planners in forecasting the demands and can accordingly
manage the stock level
ABC analysis also helps in framing the strategic pricing policies as the most valuable
products can be sorted out.

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b) Ranking Table
Items
cost per
item
Sales
units
Annual
turnover
% of annual
turnover Rank
White bread 5 1083745 5418725 79.8 1
Wholemeal
bread 6.5 91089 592078.5 8.72 2
French bread 7 27882 195174 2.87 3
Nazareth Bread 8 9584 76672 1.13 7
Coffee cake 28 3796 106288 1.57 6
Chocolate cake 35 5537 193795 2.85 4
Banana cake 26 5166 134316 1.98 5
Muffins 4 5579 22316 0.33 9
Cup cakes 6 5455 32730 0.48 8
Scones 3.5 5087 17804.5 0.26 10
TOTAL 6789899 100.0

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ABC analysis
Items in order of
rank
Item
number
%of total
items Value
%of
total cum val
Cum
%
% of total
value
Categor
y
White bread 5418725 79.81
541872
5 79.81
Wholemeal
bread 3 30
592078.
5 8.72
601080
4 88.53
French bread 195174 2.87
620597
8 91.40
6205978 91.4 A
Chocolate cake 193795 2.85
639977
3 94.26
Banana cake 3 30 134316 1.98
653408
9 96.24
Coffee cake 106288 1.57
664037
7 97.80
0.00 97.80
434399 6.40 B
Nazarath bread 76672
671704
9
Cup cakes 32730 0.48
674977
9 98.28
Muffins 4 40 22316 0.33
677209
5 98.61
Scones 17804.5 0.26
678989
9 98.88
149522.
5 2.20 C
Total 10 100 6789899 100.0

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As the manger of Dough bakery, the products which fall under category A are to be monitored and managed more closely as it is
observed that those products contribute more than 90% of the total revenue. Thus for Dough bakery, White bread, Wholemeal
bread, and French bread are the most valuable products.

14
4.3 EOQ MODEL
a) EOQ is that string where both the costs, ordering and carrying, intersect each
other. At the time of calculating the total cost, the carrying cost is charged on half of
EOQ.
The objectives of EOQ are:
i) EOQ helps in balancing the two conflicting the cost, that is carrying cost, which
arises out of the bulk purchase and the not carrying cost, which arises out of the
frequent and small purchase.
ii) It aims in setting the order quantity which will be economically viable.
iii) Another aim of the EOQ model is its Robustic nature. It provides almost
satisfactory answers even with the substantial variation in its parameters.
The two assumptions of EOQ model are:
Stock-outs can be avoided if the order can be placed in right time
Lead time is certainly known and is consistent.
b) Annual demand (given)= 5000 boxes
Cost per box = $10
Holding cost= $ 3
Ordering cost per order= $ 25
EOQ = √2 D S/ H
D= demand = 5000 boxes
S= Set up cost or ordering cost = $25
H= Holding cost = $3, 30%
Therefore, EOQ = 287 boxes approximately.
Number of orders = Annual demand / EOQ
= 5000/287
= 18 orders approx..
Annual ordering cost = (Number of orders * cost per order)
= (18*25) =$ 450
c) Total cost for supplier A = (Demand * cost per unit) + ordering cost per annum +
EOQ /2* carrying cost
(5000*10) + 450+ (287/2)*3 =$ (50000 + 450 + 431) =$ 50,881
If the offer from supplier B is accepted, then EOQ will be

15
√2*5000*35 / 3 = 342 boxes
Number of orders = 5000/342 = 15 orders approx.
Annual ordering cost = (35*15)= $ 525
Total cost = (5000*7.5) +(525) + (342/2)*3 = $ 38,538.
Thus, Dough Bakery should go with supplier B as the total cost is less than the cost
of supplier A.
Question 5: Material Resource Planning:
Benefits for the implementation of Material Resource Planning for Dough
Bakery
Material resource planning, which is also known as material requirement planning is
all about the planning of the production through procurement, scheduling, inventory
control system, and monitoring the resource employment in production process.
Therefore, the concept of material resource planning assists a production manager
to identify and determine the resource to be accounted to extract the material for
production and the limit of both procurement and employment in production.
Therefore, concerning the concept of MRP, key components of such material
resource planning are:
Master production schedule determines the production amount required to be
generated along with the schedule of completing the production process.
Bill of materials refers to the list of materials, required for production process along
with the quantity and price for each item
Inventory stocks including the stocks in hand and the stock outstanding
Capacity planning refers to the planning procedure in determining and retaining a
maximum or optimum level of capacity
Purchasing or procurement referred to acquiring materials for production from
suppliers
Referring to the above concepts for Dough Bakery, it could be inferred that material
resource planning would assist the production and operation department of the
company to identify and plan the procurement and extraction of the resources to be
employed in the production process. Therefore, the material resource planning would
reduce the cost of procurement and maximize the wealth of the company in the form
of profitability and revenue generation.
Question 6: Integrated Supply chain management
Integrated supply chain and inventory management for Dough Bakery:
The Supply chain is the network including suppliers, producers, distributors, and
inventory owners to flow the product from the room of suppliers of the raw materials
to the end users to be delivered safely. Here, the length of the supply chain relies on

16
the number of intermediaries present in the supply chain process. Therefore, the
complication of the supply chain is being carried out at the participants, involved in
the supply chain process. The concept of supply chain has been transformed from its
conventional format to the integrated format, including the complications to solve the
critical production and delivery of the products and services. In Dough bakery, the
integrated supply chain management would assist the production process by
identifying the bugs in the process and reduced the same to smoothen the company
process of producing and delivering the requirements. In that case, in the opinion of
Disney, Maltz, Wang & Warburton (2016), inventory management system in a
company plays a significant role in the integrated supply chain to resolve the issues
arisen in the production and delivery process of the products and services. Inventory
management refers to a store of end products before delivery to the end users. In
case of the Dough Bakery, an efficient Integrated Supply Chain Management, in line
with an effective inventory management policies and practices will help in handling
products safely to deliver the same with quality and with all its requirements.
Conclusions:
From the above discussions and analysis of all components of operation
management, it has been observed that each component of the operation
management is essential for an organization to get operational success and thus,
generate sufficient benefits both financial and non-financial. Capacity management is
one of the crucial part to understand the amount that the company can produce to
meet demand of the customer. In that case, effective capacity is an apt concept to
keep the quality as determined with highest possible efficiency. Moreover, inventory
and supply chain are two essentials that follow the capacity determination as to store
and distribute the produced data to destination. In this context, the management of
the company needs to be concerned about own and company efficiency in
optimizing the resources along with the maximizing output indicating growth and
earning prospect of the company in near future.

17
References:
Disney, S. M., Maltz, A., Wang, X., & Warburton, R. D. (2016). Inventory
management for stochastic lead times with order crossovers. European
Journal of Operational Research, 248(2), 473-486.
Dolinayova, A., Kanis, J., & Loch, M. (2016). Social and Economic Efficiency of
Operation Dependent and Independent Traction in Rail Freight. Procedia
Engineering, 134, 187-195.
Harris, T., Intelligence, E., & Healthcare, C. (2017). Predictive Analytics: Proactive
Integrated Capacity Management.
Wang, G., Gunasekaran, A., Ngai, E. W., & Papadopoulos, T. (2016). Big data
analytics in logistics and supply chain management: Certain investigations for
research and applications. International Journal of Production
Economics, 176, 98-110.

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Appendix:
TABLE 1: Dough Bakery Monthly Sales
Products Feb 17 Mar 17 Apr 17 May 17 Jun 17 Jul 17 Aug 17 Sep 17 Oct 17 Nov 17 Dec 17 Jan 18
White Bread 75,656 78,195 80, 006 87,900 90,600 91,450 93,000 94,999 96,263 97,863 98,547 99,266
Wholemeal
Bread
7,105 7,148 7,255 7,350 7,500 7,533 7,680 7,750 7874 7,911 7,982 8,001
French Bread 1,600 1,690 1,730 1,770 1,800 1,798 1,860 1,888 1,891 1,905 1,950 2,000
Nazareth Bread700 726 745 768 780 775 806 825 837 855 876 891
Coffee Cake 259 272 287 295 300 310 330 335 341 346 357 364
Chocolate
Cake
396 403 418 421 434 450 465 481 496 505 527 541
Banana Cale 369 387 396 404 411 420 422 434 465 475 482 501
Muffins 409 415 428 436 444 450 465 487 496 510 515 524
Cupcakes 389 401 412 421 434 450 465 473 489 496 506 519
Scones 436 455 463 372 384 390 403 412 427 434 451 460
Total 87, 319 90,092 92,140 100,137 103,087 104,026 105,896 108,084 109,579 111,300 112,193 113,067

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Table 2: Individual Product Contributions to the Dough Bakery Annual Turnover
Products Cost per Item Sales Quantity Annual Turnover
($)
White Bread $ 5.00 1,083,745 $ 5,418,725. 00
Wholemeal Bread $ 6.50 91,089 $ 592,078.50
French Bread $ 7.00 27,882 $ 195,174.00
Nazareth Bread $ 8.00 9,584 $ 76,672.00
Coffee Cake $ 28.00 3,796 $ 106,288.00
Chocolate Cake $ 35.00 5,537 $ 193,795.00
Banana Cake $ 26.00 5,166 $ 134,316.00
Muffins $ 4.00 5,579 $ 22,316.00
Cupcakes $ 6.00 5,455 $ 32,730.00
Scones $ 3.50 5,087 $ 17,804.50
TOTAL 1,242,920 $ 6,789,899. 00

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TABLE 4 : Forecast Demand - Summary of Simple Moving Average (SMA)
Month Sales Sub-total SMA Error Sub-total MAD
Feb - 17 87,319
Mar - 17 90,092
Apr - 17 92,140
May- 17 100,137 89850 10287 10287
Jun - 17 103,087 94123 8964 8964
Jul - 17 104,026 98455 5571 5571
Aug - 17 105,896 102417 3479 3479
Sep - 17 108,084 104336 3748 3748
Oct - 17 109,579 106002 3577 3577
Nov - 17 111,300 107853 3447 3447
Dec - 17 112,193 109654 2539 2539
Jan - 18 113,067 111024 2043 2043
Feb - 18 ---- 112187 -

21
43655/9
=48
50
TABLE 5 : Forecast Demand - Summary of Weighted Moving Average (WMA) Weightings of 0.5, 0.3 and 0.2
Month Sales Sub-total WMA Error Sub-total MAD
Feb - 17 87,319
Mar - 17 90,092
Apr - 17 92,140
May- 17 100,137 90561 9576 9576
Jun - 17 103,087 95729 7358 7358
Jul - 17 104,026 100013 4013 4013
Aug - 17 105,896 102967 2930 2930
Sep - 17 108,084 104773 3311 3311
Oct - 17 109,579 106616 2963 2963
Nov - 17 111,300 108394 2906 2906

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Dec - 17 112,193 110141 2053 2053
Jan - 18 113,067 111402 1665 1665
Feb - 18 ---- 112451 Total= 36774
MAD= 36774/9 =4086
Table 6: Individual Product Contributions to the Dough Bakery Annual Turnover
Products Cost per Item Sales/Demand Annual Turnover Percentage of
Turnover
Accumulative
Percenta
ge
Classification
White Bread $ 5.00 1,083,745 $ 5,418,725. 00 79.81 79.81 A
Wholemeal Bread $ 6.50 91,089 $ 592,078.50 8.72 88.53 A
French Bread $ 7.00 27,882 $ 195,174.00 2.87 91.40 A
Nazareth Bread $ 8.00 9,584 $ 76,672.00 1
.1 92.5
C
Coffee Cake $ 28.00 3,796 $ 106,288.00 1.57 94.07 B

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Chocolate Cake $ 35.00 5,537 $ 193,795.00 2.85 96.92 B
Banana Cake $ 26.00 5,166 $ 134,316.00 1.98 98.9 B
Muffins $ 4.00 5,579 $ 22,316.00 0.33 99.23 C
Cupcakes $ 6.00 5,455 $ 32,730.00 0.48 99.71 C
Scones $ 3.50 5,087 $ 17,804.50 0.29 100 C
TOTAL 1,242,920 $ 6,789,899. 00

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Assumptions:

25