OM Report Formatted Final

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Biopharma Laboratories Ltd:Forecasting Sales and

Managing Inventory

Prepared For:

Md. IftekharAlam (Course Instructor)

Course: Operations Management

Prepared By:

Group-3

ShanilShazab, ZR-01

NavidSarwar ZR-57

Tashfeen F. Saeed ZR-64

BBA 16th Batch

Date of Submission:

November 28th, 2010

Institute of Business Administration (IBA)

University of Dhaka (DU)



1

November 28, 2010

Md. IftekharAlam

Course Instructor

Institute of Business Administration

University of Dhaka

Dear Sir:

Here is the Term Paper on forecasting and inventory management that you asked us to prepare as a

course requirement.

This Term paper contains our study of Biopharma Laboratories Ltd. in terms of Sales Forecast for

Year 2011 for Raw Materials Inventory Management. Our results reflect the forecasted yearly sale

for 2011 under the most suitable method called Time Series Decomposition and the optimum order

strategy in terms of Economic Order Quantity and Reorder Point for each Raw Material.

Preparing this report has been an important experience for us, as we have successfully applied the

techniques of forecasting and inventory management which was one of the objectives of our

coursework.

Please note that this report has been prepared under your supervision. Under no circumstances, will

this report be produced for any other IBA course. No part of this report will be shared or republished

without your authorization.

Sincerely,

_____________________________

Shanil Shazab, ZR 01

_____________________________

Navid Sarwar, ZR-57

_____________________________

Tashfeen Ferdous Saeed, ZR-64



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Table of Contents1. Introduction .................................................................................................................................... 3

1.1 Background ................................................................................................................................... 3

1.2 Identification of Inventory ............................................................................................................ 3

1.3 Method of Data Collection ............................................................................................................ 3

1.4 Assumptions .................................................................................................................................. 3

1.5 Limitations ..................................................................................................................................... 4

2. Forecasting ...................................................................................................................................... 4

2.1 Simple Average ....................................................................................................................... 4

2.2 Weighted average ................................................................................................................... 5

2.3 Simple Moving Average .......................................................................................................... 7

2.4 Weighted Moving Average ..................................................................................................... 8

2.5 Exponential Smoothing ........................................................................................................... 9

2.6 Linear Regression .................................................................................................................. 11

2.7 Time Series Decomposition .................................................................................................. 12

2.8 Comparison of CV........................................................................................................................ 13

3. Inventory Management ................................................................................................................ 13

3.1 Obtaining the annual demand (Z) ............................................................................................... 14

3.2 Obtaining the carrying cost ......................................................................................................... 15

3.3 Obtaining the ordering cost ........................................................................................................ 16

3.4 Obtaining the Lead time, Reorder point and Economic Order Quantity (EOQ) ......................... 16

3.5 Optimum Ordering Strategy ....................................................................................................... 17

4. Conclusion ..................................................................................................................................... 17

5. Appendix ....................................................................................................................................... 19

5.1 Simple Average ........................................................................................................................... 19

5.2 Weighted Average................................................................................................................. 20

5.3 Simple Moving Average ........................................................................................................ 22

5.4 Weighted Moving Average ................................................................................................... 24

5.5 Exponential Smoothing ......................................................................................................... 26

5.6 Linear Regression .................................................................................................................. 28

5.7 Time Series Decomposition .................................................................................................. 30



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1. Introduction

This report has been compiled based on Biopharma Laboratories Ltd. and therefore this section

includes the background, identification of major inventory, methodologies, assumptions and

limitations of the report.

1.1 Background

Biopharma Laboratories Ltd. is a reputed pharmaceutical manufacturing company based in

Bangladesh producing a wide range of biological pharmaceutical products in different dosage forms

and presentations including tablets, capsules, syrups, suspensions, ointments and injectable

preparations, among others.The vision of this company is to be regarded globally as a quality

pharmaceutical manufacturer through the best quality pharmaceutical products. By virtue of the

highest quality of drugs, the company has already obtained the confidence and trust of doctors andpatients all over Bangladesh and earned an excellent reputation in the market through introducing

new dosage forms in many therapeutic areas.

1.2 Identification of Inventory

An interview with the top management of Biopharma Laboratories Ltd. revealed the business

process of the company. According to the management the critical raw materials are imported from

foreign manufacturers. Several raw materials are then assembled in the manufacturing plant to

develop the product.

Raw material are continuously transformed into finished goods in the manufacturing process, hence

there is no work-in-progress. This report focus on the raw materials required to manufacture

Omeprazole, which is sold under the brand name Inprocapsule.

1.3 Method of Data Collection

Primary data was collected from a scheduled interview with the production manager. Secondary

data required for the report was assembled from a variety of sources including the company

website, sales records of the company and the text books for the course.

1.4 Assumptions

Lead Time is constant.

Ordering Cost is fixed.

Ordering Cost is distributed equally among all the raw materials.

Carrying Cost is distributed equally among all the raw materials.



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1.5 Limitations

According to the management the lead time varies to a large extent and hence calculations of the

reorder point may lack practical usefulness.

2. Forecasting

Forecasting has been done using the Simple Average, Weighted Average, Simple Moving Average,

Weighted Moving Average, Exponential Smoothing, Linear Regression and Time Series

Decomposition.Error Values for each method (in terms of MAD, Bias, MAPE and CV) and details of

each method along with calculations are given below:

2.1 Simple Average

Date Sales (Taka) Forecast

Jan-08 305,212

Feb-08 308,921 305,212

Mar-08 312,326 307,067

Apr-08 323,952 308,820

May-08 326,432 312,603

Jun-08 331,930 315,369

Jul-08 339,042 318,129

Aug-08 345,019 321,116

Sep-08 352,312 324,104

Oct-08 385,010 327,238

Nov-08 389,669 333,016

Dec-08 388,689 338,166

Jan-09 370,214 342,376

Feb-09 365,442 344,518

Mar-09 371,276 346,012

Apr-09 385,098 347,696

May-09 389,566350,034

Jun-09 383,784 352,359

Jul-09 389,655 354,105

Aug-09 386,489 355,976

Sep-09 396,568 357,502

Oct-09 398,656 359,362

Nov-09 395,888 361,148

Dec-09 399,669 362,659

Jan-10 429,856 364,201

Feb-10 430,685 366,827

Mar-10 455,663 369,283



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Feb-09 365,442 357,279

Mar-09 371,276 358,299

Apr-09 385,098 359,741

May-09 389,566 362,724

Jun-09 383,784365,550

Jul-09 389,655 367,286

Aug-09 386,489 369,523

Sep-09 396,568 371,065

Oct-09 398,656 373,191

Nov-09 395,888 375,405

Dec-09 399,669 377,044

Jan-10 429,856 378,720

Feb-10 430,685 382,653

Mar-10 455,663 386,084

Apr-10 426,595 390,723

May-10 469,255 393,197

Jun-10 469,873 398,104

Jul-10 466,350 402,453

Aug-10 483,665 406,447

Sep-10 490,358 410,989

Oct-10 482,560 415,398

Nov-10 493,559 419,236

Dec-10 505,565 423,254

Jan-11 427,475

Feb-11 427,709

Mar-11 427,920

Apr-11 428,111

May-11 428,298

Jun-11 428,467

Jul-11 428,621

Aug-11 428,771

Sep-11 428,908

Oct-11 429,034Nov-11 429,158

Dec-11 429,271

MAD BIAS MAPE CV

36,670 36,670 0.08546316 9.1417%



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2.3 Simple Moving Average


Jan-08 305,212Feb-08 308,921

Mar-08 312,326

Apr-08 323,952 308,820

May-08 326,432 315,066

Jun-08 331,930 320,903

Jul-08 339,042 327,438

Aug-08 345,019 332,468

Sep-08 352,312 338,664

Oct-08 385,010 345,458Nov-08 389,669 360,780

Dec-08 388,689 375,664

Jan-09 370,214 387,789

Feb-09 365,442 382,857

Mar-09 371,276 374,782

Apr-09 385,098 368,977

May-09 389,566 373,939

Jun-09 383,784 381,980

Jul-09 389,655 386,149

Aug-09 386,489 387,668

Sep-09 396,568 386,643

Oct-09 398,656 390,904

Nov-09 395,888 393,904

Dec-09 399,669 397,037

Jan-10 429,856 398,071

Feb-10 430,685 408,471

Mar-10 455,663 420,070

Apr-10 426,595 438,735

May-10 469,255 437,648

Jun-10 469,873 450,504

Jul-10 466,350 455,241

Aug-10 483,665 468,493

Sep-10 490,358 473,296

Oct-10 482,560 480,124

Nov-10 493,559 485,528

Dec-10 505,565 488,826

Jan-11 493,895

Feb-11 497,673Mar-11 499,044



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Apr-11 496,871

May-11 497,863

Jun-11 497,926

Jul-11 497,553

Aug-11 497,781

Sep-11 497,753

Oct-11 497,696

Nov-11 497,743

Dec-11 497,731

MAD BIAS MAPE CV

14,518 11,377 3.572483% 3.570319%

2.4 Weighted Moving Average


Jan-08 305,212

Feb-08 308,921

Mar-08 312,326

Apr-08 323,952 309,882

May-08 326,432 317,458

Jun-08 331,930 322,867

Jul-08 339,042 328,685

Aug-08 345,019 334,386

Sep-08 352,312 340,608

Oct-08 385,010 347,470

Nov-08 389,669 367,202

Dec-08 388,689 380,800

Jan-09 370,214 388,247

Feb-09 365,442 379,648

Mar-09 371,276 371,523

Apr-09 385,098 369,313

May-09 389,566 377,020

Jun-09 383,784 384,568

Jul-09 389,655 385,781

Aug-09 386,489 387,876

Sep-09 396,568 386,898

Oct-09 398,656 392,162

Nov-09 395,888 395,596

Dec-09 399,669 396,854

Jan-10 429,856 398,332

Feb-10 430,685 414,006



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Mar-10 455,663 424,233

Apr-10 426,595 443,008

May-10 469,255 436,133

Jun-10 469,873 453,739

Jul-10 466,350461,032

Aug-10 483,665 467,988

Sep-10 490,358 475,712

Oct-10 482,560 483,549

Nov-10 493,559 485,120

Dec-10 505,565 489,619

Jan-11 497,362

Feb-11 499,062

Mar-11 499,853

Apr-11 499,118

May-11 499,327

Jun-11 499,370

Jul-11 499,307

Aug-11 499,330

Sep-11 499,331

Oct-11 499,326

Nov-11 499,328

Dec-11 499,328

MAD BIAS MAPE CV

12,883 9,728 3.159219% 3.168375%

2.5 Exponential Smoothing


Jan-08 305,212 359,546

Feb-08 308,921 337,812

Mar-08 312,326 326,256

Apr-08 323,952 320,684

May-08 326,432 321,991

Jun-08 331,930 323,767

Jul-08 339,042 327,032

Aug-08 345,019 331,836

Sep-08 352,312 337,109

Oct-08 385,010 343,190

Nov-08 389,669 359,918



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MAD BIAS MAPE CV

15,881 11,785 3.915464% 3.732739%

Dec-08 388,689 371,819

Jan-09 370,214 378,567

Feb-09 365,442 375,226

Mar-09 371,276 371,312

Apr-09 385,098371,298

May-09 389,566 376,818

Jun-09 383,784 381,917

Jul-09 389,655 382,664

Aug-09 386,489 385,460

Sep-09 396,568 385,872

Oct-09 398,656 390,150

Nov-09 395,888 393,553

Dec-09 399,669 394,487

Jan-10 429,856 396,560

Feb-10 430,685 409,878

Mar-10 455,663 418,201

Apr-10 426,595 433,186

May-10 469,255 430,549

Jun-10 469,873 446,032

Jul-10 466,350 455,568

Aug-10 483,665 459,881

Sep-10 490,358 469,395

Oct-10 482,560 477,780

Nov-10 493,559 479,692

Dec-10 505,565 485,239

Jan-11 493,369

Feb-11 493,370

Mar-11 493,370

Apr-11 493,370

May-11 493,370

Jun-11 493,370

Jul-11 493,370

Aug-11 493,370Sep-11 493,370

Oct-11 493,370

Nov-11 493,370

Dec-11 493,370



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2.6 Linear Regression


Jan-08 305,212 306,037

Feb-08 308,921 311,319

Mar-08 312,326 316,600

Apr-08 323,952 321,882

May-08 326,432 327,164

Jun-08 331,930 332,445

Jul-08 339,042 337,727

Aug-08 345,019 343,009

Sep-08 352,312 348,291

Oct-08 385,010 353,572

Nov-08 389,669 358,854

Dec-08 388,689 364,136

Jan-09 370,214 369,417

Feb-09 365,442 374,699

Mar-09 371,276 379,981

Apr-09 385,098 385,262

May-09 389,566 390,544

Jun-09 383,784 395,826

Jul-09 389,655 401,108

Aug-09 386,489 406,389Sep-09 396,568 411,671

Oct-09 398,656 416,953

Nov-09 395,888 422,234

Dec-09 399,669 427,516

Jan-10 429,856 432,798

Feb-10 430,685 438,080

Mar-10 455,663 443,361

Apr-10 426,595 448,643

May-10 469,255 453,925

Jun-10 469,873 459,206

Jul-10 466,350 464,488

Aug-10 483,665 469,770

Sep-10 490,358 475,051

Oct-10 482,560 480,333

Nov-10 493,559 485,615

Dec-10 505,565 490,897

Jan-11 496,178

Feb-11 501,460

Mar-11 506,742



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MAD BIAS MAPE CV

10,623 0 2.603924% 2.666066%

2.7 Time Series Decomposition

Year Quarter QuarterlySales

Forecast

2008 1 926,459 927,428

2 982,314 979,283

3 1,036,373 1,026,207

4 1,163,368 1,091,310

2009 1 1,106,932 1,129,468

2 1,158,448 1,179,268

3 1,172,712 1,207,690

4 1,194,213 1,267,474

2010 1 1,316,204 1,320,229

2 1,365,723 1,370,370

3 1,440,373 1,395,778

4 1,481,684 1,457,475

2011 1 1,510,9892 1,561,472

3 1,583,867

4 1,647,476

MAD BIAS MAPE CV

26,274 -598 2.159527% 2.197962%

Apr-11 512,023

May-11 517,305

Jun-11 522,587

Jul-11 527,869

Aug-11 533,150

Sep-11 538,432

Oct-11 543,714

Nov-11 548,995

Dec-11 554,277



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Assumptions used for the calculations:

The demand which was forecasted using the time series decomposition method, is held

constant

No shortage (stock outs) is allowed

Lead time for the receipt of order is constant and independent of demand

The order quantity is received all at once

A more detailed brief on how the calculations were performed have been shown below.

3.1 Obtaining the annual demand (Z)

In order to calculate this, the total demand of the product for 2011 was obtained. The time series

decomposition method was used to forecast the sales of 2011. The annual demand of the raw

material was deduced from the total sales of 2011. The table below shows how the annual demand

of the number of Omeprazole boxes was obtained.

Annual Demand for Omeprazole (BDT) 6036042.76

Market Price of Omeprazole (1 box with 20

tablets)

140

No. of units sold (Box) 43114.59114

Name of Raw

Material

Annual Demand

(Z) in grams

Ordering

Cost/Order (BDT)

Carrying Cost Per

Raw Material

(C*Cc) in BDT

Lead

Time

(days)

EOQ (units

in grams)

Reorder Point

(units in grams)

Omeprazole

Pallet (8.5%)

34491.67292 11491.66667 0.0125 30 251831 2835

EHG (Empty

Hearth Gelatin)

Shell

30180.2138 11491.66667 0.014285714 12 220352 992

Inner Carton 1940.156601 11491.66667 0.222222222 10 14165 53

Blister Foil 2155.729557 11491.66667 0.2 10 15739 59

Aluminum Foil 29102.34902 11491.66667 0.014814815 10 212482 797

Leaflet 3449.167292 11491.66667 0.125 5 25183 47



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The economic order of quantity is determined using Annual Demand of Raw Material (Z), Ordering

Cost (Cr) and Carrying Cost.

3.5 Optimum Ordering Strategy

Name of Raw Material EOQ (X) units in grams Reorder Point (R*) units in grams

Omeprazole Pallet (8.5%) 251831 2835

EHG (Empty Hearth Gelatin) Shell 220352 992

Inner Carton 14165 53

Blister Foil 15739 59

Aluminum Foil 212482 797

Leaflet 25183 47

The basic interpretation of the data is illustrated below:

Name of Raw Material Interpretation

Omeprazole Pallet

(8.5%)

The operating doctrine would be to order 251831 grams when the stocks

on hand reaches 2835 grams

EHG (Empty Hearth

Gelatin) Shell

The operating doctrine would be to order 220352 grams when the stocks


Inner Carton The operating doctrine would be to order 14165 grams when the stocks


Blister Foil The operating doctrine would be to order 15739 grams when the stocks


Aluminum Foil The operating doctrine would be to order 212482 grams when the stocks


Leaflet The operating doctrine would be to order 25183 grams when the stocks


4. ConclusionOur study reflects the possible forecasted sales figures and optimum order strategy for Biopharma

Laboratories Ltd. These results and strategies can provide a handy reference for pre-strategies and

decision making.



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Seven different forecasting methods were used to calculate future sales for 2011. According to the

error estimates under each method, CV was lowest for Time Series Decomposition method, leading

us to deduce that this would be the most accurate method of forecasting for Biopharma

Laboratories Ltd.

The lead time was variable based on the type of raw material. The reorder point is thus at different

levels of the inventory. According to the management, this was a better method to reflect the true

reorder points.

Similarly, the order strategy has been developed under fixed lead time and fixed ordering cost

assumptions. Slight changes in these costs would not affect strategy drastically in real life.



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5. Appendix

All the detailed calculations under each forecasting method are provided below along with the

relevant graphs and figures:

5.1 Simple Average

Date Sales (Taka) Forecast Di-Fi |Di-Fi| |Di-Fi|/Di

Jan-08 305,212

Feb-08 308,921 305,212 3,709 3,709 0.012006306

Mar-08 312,326 307,067 5,260 5,260 0.016839776

Apr-08 323,952 308,820 15,132 15,132 0.046711653

May-08 326,432 312,603 13,829 13,829 0.042364872

Jun-08 331,930 315,369 16,561 16,561 0.049894255

Jul-08 339,042 318,129 20,913 20,913 0.061683115

Aug-08 345,019 321,116 23,903 23,903 0.069279

Sep-08 352,312 324,104 28,208 28,208 0.080064687

Oct-08 385,010 327,238 57,772 57,772 0.150052091

Nov-08 389,669 333,016 56,653 56,653 0.145388522

Dec-08 388,689 338,166 50,523 50,523 0.129983331

Jan-09 370,214 342,376 27,838 27,838 0.075193897

Feb-09 365,442 344,518 20,924 20,924 0.057257955Mar-09 371,276 346,012 25,264 25,264 0.068046028

Apr-09 385,098 347,696 37,402 37,402 0.097122291

May-09 389,566 350,034 39,532 39,532 0.101477028

Jun-09 383,784 352,359 31,425 31,425 0.081880923

Jul-09 389,655 354,105 35,550 35,550 0.091233983

Aug-09 386,489 355,976 30,513 30,513 0.078948526

Sep-09 396,568 357,502 39,066 39,066 0.09851047

Oct-09 398,656 359,362 39,294 39,294 0.098565705

Nov-09 395,888 361,148 34,740 34,740 0.087751403

Dec-09 399,669 362,659 37,010 37,010 0.092602389

Jan-10 429,856 364,201 65,655 65,655 0.15273768

Feb-10 430,685 366,827 63,858 63,858 0.148270778

Mar-10 455,663 369,283 86,380 86,380 0.189569755

Apr-10 426,595 372,482 54,113 54,113 0.126847869

May-10 469,255 374,415 94,840 94,840 0.202107748

Jun-10 469,873 377,685 92,188 92,188 0.196197109

Jul-10 466,350 380,758 85,592 85,592 0.183535542

Aug-10 483,665 383,519 100,146 100,146 0.20705607

Sep-10 490,358 386,649 103,709 103,709 0.211496945



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Oct-10 482,560 389,791 92,769 92,769 0.192242447

Nov-10 493,559 392,520 101,039 101,039 0.2047152

Dec-10 505,565 395,407 110,158 110,158 0.21789127

Jan-11 410,882 398,467

Feb-11 410,882 398,802

Mar-11 410,882 399,120

Apr-11 410,882 399,422

May-11 410,882 399,708

Jun-11 410,882 399,981

Jul-11 410,882 400,240

Aug-11 410,882 400,488

Sep-11 410,882 400,724

Oct-11 410,882 400,950

Nov-11 410,882 401,166

Dec-11 401,372

5.2 Weighted Average

Date Sales (Taka) Weight Weight*Sales Forecast Di-Fi |Di-Fi| |Di-Fi|/Di

Jan-08 305,212 1 305,212

Feb-08 308,921 1 308,921 305,212 3,709 3,709 0.012006306

Mar-08 312,326 1 312,326 307,067 5,260 5,260 0.016839776

Apr-08 323,952 2 647,904 308,820 15,132 15,132 0.046711653

May-08 326,432 2 652,864 314,873 11,559 11,559 0.035411357

Jun-08 331,930 2 663,860 318,175 13,755 13,755 0.041438599

Jul-08 339,042 3 1,017,126 321,232 17,810 17,810 0.052530693

0

100,000

200,000

300,000

400,000

500,000

600,000

J a n / 0 8

A p r / 0 8

J u l / 0 8

O c t / 0 8

J a n / 0 9

A p r / 0 9

J u l / 0 9

O c t / 0 9

J a n / 1 0

A p r / 1 0

J u l / 1 0

O c t / 1 0

J a n / 1 1

A p r / 1 1

J u l / 1 1

O c t / 1 1

Sales (Taka)

Forecast



22

5.3 Simple Moving Average


Jan-08 305,212

Feb-08 308,921

Mar-08 312,326

Apr-08 323,952 308,820 15,132 15,132 0.046711653

May-08 326,432 315,066 11,366 11,366 0.034817869

Jun-08 331,930 320,903 11,027 11,027 0.033219856Jul-08 339,042 327,438 11,604 11,604 0.034225848

Aug-08 345,019 332,468 12,551 12,551 0.036377707

Sep-08 352,312 338,664 13,648 13,648 0.038739337

Oct-08 385,010 345,458 39,552 39,552 0.102730665

Nov-08 389,669 360,780 28,889 28,889 0.074136425

Dec-08 388,689 375,664 13,025 13,025 0.033510939

Jan-09 370,214 387,789 -17,575 17,575 0.047473443

Feb-09 365,442 382,857 -17,415 17,415 0.047655533

Mar-09 371,276 374,782 -3,506 3,506 0.009442212

Apr-09 385,098 368,977 16,121 16,121 0.041861206

May-09 389,566 373,939 15,627 15,627 0.040114726

Jun-09 383,784 381,980 1,804 1,804 0.004700561

Jul-09 389,655 386,149 3,506 3,506 0.008996848

Aug-09 386,489 387,668 -1,179 1,179 0.003051402

Sep-09 396,568 386,643 9,925 9,925 0.025028074

Oct-09 398,656 390,904 7,752 7,752 0.019445336

Nov-09 395,888 393,904 1,984 1,984 0.005010676

Dec-09 399,669 397,037 2,632 2,632 0.006584615

Jan-10 429,856 398,071 31,785 31,785 0.073943367

0

100,000

200,000

300,000

400,000

500,000

600,000

J a n / 0 8

M a r / 0 8

M a y / 0 8

J u l / 0 8

S e p / 0 8

N o v / 0 8

J a n / 0 9

M a r / 0 9

M a y / 0 9

J u l / 0 9

S e p / 0 9

N o v / 0 9

J a n / 1 0

M a r / 1 0

M a y / 1 0

J u l / 1 0

S e p / 1 0

N o v / 1 0

J a n / 1 1

M a r / 1 1

M a y / 1 1

J u l / 1 1

S e p / 1 1

N o v / 1 1

Sales (Taka)

Forecast



23

Feb-10 430,685 408,471 22,214 22,214 0.0515783

Mar-10 455,663 420,070 35,593 35,593 0.078112552

Apr-10 426,595 438,735 -12,140 12,140 0.028457124

May-10 469,255 437,648 31,607 31,607 0.067356412

Jun-10 469,873450,504 19,369 19,369 0.041221068

Jul-10 466,350 455,241 11,109 11,109 0.023821164

Aug-10 483,665 468,493 15,172 15,172 0.031369509

Sep-10 490,358 473,296 17,062 17,062 0.034794987

Oct-10 482,560 480,124 2,436 2,436 0.005047386

Nov-10 493,559 485,528 8,031 8,031 0.016272286

Dec-10 505,565 488,826 16,739 16,739 0.033110151

Jan-11 493,895 493,895

Feb-11 497,673 497,673

Mar-11 499,044 499,044

Apr-11 496,871 496,871

May-11 497,863 497,863

Jun-11 497,926 497,926

Jul-11 497,553 497,553

Aug-11 497,781 497,781

Sep-11 497,753 497,753

Oct-11 497,696 497,696

Nov-11 497,743 497,743

Dec-11 497,731

0

100,000

200,000

300,000

400,000

500,000

600,000

J a n / 0 8

M a r / 0 8

M a y / 0 8

J u l / 0 8

S e p / 0 8

N o v / 0 8

J a n / 0 9

M a r / 0 9

M a y / 0 9

J u l / 0 9

S e p / 0 9

N o v / 0 9

J a n / 1 0

M a r / 1 0

M a y / 1 0

J u l / 1 0

S e p / 1 0

N o v / 1 0

J a n / 1 1

M a r / 1 1

M a y / 1 1

J u l / 1 1

S e p / 1 1

N o v / 1 1

Sales (Taka)

Forecast



24

5.4 Weighted Moving Average


Jan-08 305,212

Feb-08 308,921

Mar-08 312,326

Apr-08 323,952 309,882 14,070 14,070 0.04343329

May-08 326,432 317,458 8,974 8,974 0.02749118

Jun-08 331,930 322,867 9,063 9,063 0.02730455

Jul-08 339,042 328,685 10,357 10,357 0.03054784

Aug-08 345,019 334,386 10,633 10,633 0.03081743

Sep-08 352,312 340,608 11,704 11,704 0.03322027

Oct-08 385,010 347,470 37,540 37,540 0.0975037

Nov-08 389,669 367,202 22,467 22,467 0.0576556

Dec-08 388,689 380,800 7,889 7,889 0.02029669

Jan-09 370,214 388,247 -18,033 18,033 0.04871021

Feb-09 365,442 379,648 -14,206 14,206 0.03887211

Mar-09 371,276 371,523 -247 247 0.00066527

Apr-09 385,098 369,313 15,785 15,785 0.04098853

May-09 389,566 377,020 12,546 12,546 0.03220456

Jun-09 383,784 384,568 -784 784 0.00204177

Jul-09 389,655 385,781 3,874 3,874 0.0099411

Aug-09 386,489 387,876 -1,387 1,387 0.00358846Sep-09 396,568 386,898 9,670 9,670 0.02438472

Oct-09 398,656 392,162 6,494 6,494 0.01629049

Nov-09 395,888 395,596 292 292 0.00073708

Dec-09 399,669 396,854 2,815 2,815 0.00704233

Jan-10 429,856 398,332 31,524 31,524 0.07333595

Feb-10 430,685 414,006 16,679 16,679 0.03872598

Mar-10 455,663 424,233 31,430 31,430 0.0689762

Apr-10 426,595 443,008 -16,413 16,413 0.0384749

May-10 469,255 436,133 33,122 33,122 0.07058337

Jun-10 469,873 453,739 16,134 16,134 0.03433779

Jul-10 466,350 461,032 5,318 5,318 0.01140345

Aug-10 483,665 467,988 15,677 15,677 0.03241314

Sep-10 490,358 475,712 14,646 14,646 0.02986777

Oct-10 482,560 483,549 -989 989 0.00204845

Nov-10 493,559 485,120 8,439 8,439 0.01709745

Dec-10 505,565 489,619 15,946 15,946 0.03154075

Jan-11 497,362 497,362

Feb-11 499,062 499,062

Mar-11 499,853 499,853



25

Apr-11 499,118 499,118

May-11 499,327 499,327

Jun-11 499,370 499,370

Jul-11 499,307 499,307

Aug-11 499,330499,330

Sep-11 499,331 499,331

Oct-11 499,326 499,326

Nov-11 499,328 499,328

Dec-11 499,328

Weight

t-3 0.2

t-2 0.3

t-1 0.5

0

100,000

200,000

300,000

400,000

500,000

600,000

J a n / 0 8

A p r / 0 8

J u l / 0 8

O c t / 0 8

J a n / 0 9

A p r / 0 9

J u l / 0 9

O c t / 0 9

J a n / 1 0

A p r / 1 0

J u l / 1 0

O c t / 1 0

J a n / 1 1

A p r / 1 1

J u l / 1 1

O c t / 1 1

Sales

(Taka)



26

5.5 Exponential Smoothing


Jan-08 305,212 359,546 -54,334 54,334 0.178020523

Feb-08 308,921 337,812 -28,891 28,891 0.093523587

Mar-08 312,326 326,256 -13,930 13,930 0.044600321

Apr-08 323,952 320,684 3,268 3,268 0.010088211

May-08 326,432 321,991 4,441 4,441 0.013604235

Jun-08 331,930 323,767 8,163 8,163 0.024591072

Jul-08 339,042 327,032 12,010 12,010 0.035421891

Aug-08 345,019 331,836 13,183 13,183 0.038208636

Sep-08 352,312 337,109 15,203 15,203 0.043151023

Oct-08 385,010 343,190 41,820 41,820 0.108619449

Nov-08 389,669 359,918 29,751 29,751 0.076348758

Dec-08 388,689 371,819 16,870 16,870 0.043403458

Jan-09 370,214 378,567 -8,353 8,353 0.022561902

Feb-09 365,442 375,226 -9,784 9,784 0.026772071

Mar-09 371,276 371,312 -36 36 9.74572E-05

Apr-09 385,098 371,298 13,800 13,800 0.035835787

May-09 389,566 376,818 12,748 12,748 0.032724041

Jun-09 383,784 381,917 1,867 1,867 0.004864466

Jul-09 389,655 382,664 6,991 6,991 0.017941878

Aug-09 386,489 385,460 1,029 1,029 0.002661617Sep-09 396,568 385,872 10,696 10,696 0.026971948

Oct-09 398,656 390,150 8,506 8,506 0.021336006

Nov-09 395,888 393,553 2,335 2,335 0.005899234

Dec-09 399,669 394,487 5,182 5,182 0.012966384

Jan-10 429,856 396,560 33,296 33,296 0.077459328

Feb-10 430,685 409,878 20,807 20,807 0.048310979

Mar-10 455,663 418,201 37,462 37,462 0.082214462

Apr-10 426,595 433,186 -6,591 6,591 0.015449658

May-10 469,255 430,549 38,706 38,706 0.082482982

Jun-10 469,873 446,032 23,841 23,841 0.050739947

Jul-10 466,350 455,568 10,782 10,782 0.023119543

Aug-10 483,665 459,881 23,784 23,784 0.049174696

Sep-10 490,358 469,395 20,963 20,963 0.042751311

Oct-10 482,560 477,780 4,780 4,780 0.009905646

Nov-10 493,559 479,692 13,867 13,867 0.028096015

Dec-10 505,565 485,239 20,326 20,326 0.040204968

Jan-11 493,370 493,369

Feb-11 493,370 493,370

Mar-11 493,370 493,370



28

5.6 Linear Regression

Date Sales (Taka) Period Forecast Di-Fi |Di-Fi| |Di-Fi|/Di

Jan-08 305,212 1 306,037 -825 825 0.0027027

Feb-08 308,921 2 311,319 -2,398 2,398 0.007761215

Mar-08 312,326 3 316,600 -4,274 4,274 0.013685406

Apr-08 323,952 4 321,882 2,070 2,070 0.006389792

May-08 326,432 5 327,164 -732 732 0.00224157

Jun-08 331,930 6 332,445 -515 515 0.001552815

Jul-08 339,042 7 337,727 1,315 1,315 0.003878186

Aug-08 345,019 8 343,009 2,010 2,010 0.005826236

Sep-08 352,312 9 348,291 4,021 4,021 0.011414474

Oct-08 385,010 10 353,572 31,438 31,438 0.081654373

Nov-08 389,669 11 358,854 30,815 30,815 0.079080051

Dec-08 388,689 12 364,136 24,553 24,553 0.063169625

Jan-09 370,214 13 369,417 797 797 0.002151816

Feb-09 365,442 14 374,699 -9,257 9,257 0.02533117

Mar-09 371,276 15 379,981 -8,705 8,705 0.023445575

Apr-09 385,098 16 385,262 -164 164 0.000427126

May-09 389,566 17 390,544 -978 978 0.002510977

Jun-09 383,784 18 395,826 -12,042 12,042 0.031376756

Jul-09 389,655 19 401,108 -11,453 11,453 0.029391649

Aug-09 386,489 20 406,389 -19,900 19,900 0.051489975Sep-09 396,568 21 411,671 -15,103 15,103 0.0380843

Oct-09 398,656 22 416,953 -18,297 18,297 0.045896012

Nov-09 395,888 23 422,234 -26,346 26,346 0.066550203

Dec-09 399,669 24 427,516 -27,847 27,847 0.069675488

Jan-10 429,856 25 432,798 -2,942 2,942 0.006843777

Feb-10 430,685 26 438,080 -7,395 7,395 0.017169264

Mar-10 455,663 27 443,361 12,302 12,302 0.026997473

Apr-10 426,595 28 448,643 -22,048 22,048 0.051683579

May-10 469,255 29 453,925 15,330 15,330 0.032669525

Jun-10 469,873 30 459,206 10,667 10,667 0.022701096

Jul-10 466,350 31 464,488 1,862 1,862 0.003992551

Aug-10 483,665 32 469,770 13,895 13,895 0.028729017

Sep-10 490,358 33 475,051 15,307 15,307 0.031214978

Oct-10 482,560 34 480,333 2,227 2,227 0.004614573

Nov-10 493,559 35 485,615 7,944 7,944 0.016095547

Dec-10 505,565 36 490,897 14,668 14,668 0.029013868

Jan-11 37 496,178

Feb-11 38 501,460

Mar-11 39 506,742



29

Apr-11 40 512,023

May-11 41 517,305

Jun-11 42 522,587

Jul-11 43 527,869

Aug-11 44 533,150

Sep-11 45 538,432

Oct-11 46 543,714

Nov-11 47 548,995

Dec-11 48 554,277

Slope 5281.70592

Intercept 300755.1905

Correlation 0.96825127

0

100,000

200,000

300,000

400,000

500,000

600,000

J a n / 0

8

M a r / 0

8

M a y / 0

8

J u l / 0

8

S e p / 0

8

N o v / 0

8

J a n / 0

9

M a r / 0

9

M a y / 0

9

J u l / 0

9

S e p / 0

9

N o v / 0

9

J a n / 1

0

M a r / 1

0

M a y / 1

0

J u l / 1

0

S e p / 1

0

N o v / 1

0

J a n / 1

1

M a r / 1

1

M a y / 1

1

J u l / 1

1

S e p / 1

1

N o v / 1

1

Sales (Taka)

Forecast



5.7 Time Series Decomposition

Year Quarter

Period

QuarterlySales

ExpectedAverage

Sales

Seasonality

Index

AverageIndexPer

Quarter

Forecast Di-Fi |Di-Fi| |Di-Fi|/Di

2008 1 1 926,459 934,328 0.99 0.99 927,428 -969 969 0.001045482

2 2 982,314 981,796 1.00 1.00 979,283 3,031 3,031 0.003085923

3 3 1,036,373 1,029,264 1.01 1.00 1,026,207 10,166 10,166 0.009808832

4 4 1,163,368 1,076,731 1.08 1.01 1,091,310 72,058 72,058 0.061938702

2009 1 5 1,106,932 1,124,199 0.98 1.00 1,129,468 -22,536 22,536 0.020359222

2 6 1,158,448 1,171,666 0.99 1.01 1,179,268 -20,820 20,820 0.017972054

3 7 1,172,712 1,219,134 0.96 0.99 1,207,690 -34,978 34,978 0.029826709

4 8 1,194,213 1,266,602 0.94 1.00 1,267,474 -73,261 73,261 0.061346478

2010 1 9 1,316,204 1,314,069 1.00 1.00 1,320,229 -4,025 4,025 0.003057876

2 10 1,365,723 1,361,537 1.00 1.01 1,370,370 -4,647 4,647 0.003402606

3 11 1,440,373 1,409,005 1.02 0.99 1,395,778 44,595 44,595 0.030960473

4 12 1,481,684 1,456,472 1.02 1.00 1,457,475 24,209 24,209 0.016338828

2011 1 13 1,503,940 1.00 1,510,989 -1,510,989 1,510,989

2 14 1,551,407 1.01 1,561,472 -1,561,472 1,561,472

3 15 1,598,875 0.99 1,583,867 -1,583,867 1,583,867

4 16 1,646,343 1.00 1,647,476 -1,647,476 1,647,476

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

2,000,000

Quarterly Sales

Forecast

OM Report Formatted Final

Documents

Transcript of OM Report Formatted Final