improving cash to cash cycle by improving demand forecasting techniques
TRANSCRIPT
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ACKNOWLEDGEMENT
Words are not substitute for thoughts and feeling. I take this opportunity to thank one
and all, whose contribution to this project cannot be forgotten.
I express my sincere thanks to Dr. Gururaj H Kidiyoor , Dean (Student Affairs), TAPMI,
for his encouragement and valuable suggestions on this project work.
I am grateful to Mr. Ramesh N.Chandra, Vice President Operations, CEMA Electric
Lighting Products India Pvt Ltd., who helped me all along the project period with directions for
learning. I am also indebted to Mr. P V Jose, Sales Manager, CEMA Electric Lighting Products
India Pvt Ltd., who was ready to offer the required assistance and practical insights into a wide
array of topics as and when needed.
I gratefully remember the cooperation and assistance of my project guide and usher Dr.
Ajith Kumar, without whom this project would not have taken shape. I also thank the other
faculty members of TAPMI for their assistance and help. I wish to thank them with profound
reverence not only for having initiated me to come out with this project, but also for giving their
mental and oral support throughout this project work and for solving my problems.
At this juncture, I also wish to thank my beloved friends from Placement committee for
providing me a great learning opportunity.
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About the Company:
CEMA ELECTRIC LIGHTING PRODUCT INDIA PVT. LTD.
CEMA Electric Lighting is among the top 5 lighting solutions companies in India. The
company offers a full range of lighting products and accessories and has a major presence
across India catering to around 2 lakh retail outlets through its network of over 600 distributors
and 15 branch warehouses.
The company manufactures and markets a wide variety of lighting products including
Compact Fluorescent Lamps (CFL), Tubular Fluorescent Lamps (FTL), High Intensity Discharge
Lamps (HID) and Metal Halide Lamps (MH), Domestic & Commercial Light Fixtures.
CEMA owns the CEMA brand and also possesses a license from General Electric Corp. to
manufacture and market consumer lighting products under the GE brand name in India, Sri
Lanka, Bangladesh, Nepal, Bhutan and Maldives. Both the CEMA and GE brands have a high
equity and acceptability in the Indian lighting market.
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About the Project:
The project was to find the scope of improving Cash to Cash Cycle by Improving
Demand Forecasting Techniques. This part aimed at finding the amount that can be effectively
saved if the forecasting errors are removed at each and every branch. The second part of the
project was to find the right focus for each and every branch, which in turn for the company as
a whole. CEMA recently purchased forecasting software (Forecast Pro), and wants to review its
performance after a year
Objectives:
Objective1:
To find the scope for improvement in Cash to Cash Cycle by studying the current performance
of the forecasting system, this included Identifying the areas which can be improved Identifying the factors in selected areas Studying the performance selected factors Suggesting improved methods Finding out how much money that could be saved
Objective 2:
To find the current focus for each and individual branch and company as a whole, this included
Product performance analysis Studying product movement within a branch Studying product movement within a region Suggesting the right focus for the branch Suggesting the areas of concern and branches to be taken care of
Things Provided:
Forecast and Sales data of various SKUs for all the branches for two years Supplier details such as location, lead time etc., Stock at close for each and every month Selling price of all the SKUs
Tools Used:
Microsoft Excel
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Summary
The project deals with improving the Cash to Cash cycle of the organization as a whole,
which was achieved by studying the historical Forecast-Sales variation of various product
portfolios across 15 sales hubs of the company allover India.
Improved forecast accuracy leads to many downstream improvements in a variety of
business areas such as customer service and asset management. Understanding and predicting
the elements that make up the final SKU forecast forms the basis for improving Cash to Cash
Cycle, first phase of the project focused on finding the variables that directly affect the sales
and focus of each branch.
With more than 300 SKUs in consumer, commercial, roadway and industrial lighting, the
first and foremost variable that was found to affect the sales of individual branches was
identified as the Focus. To identify the right focus area for each and every branch a Product
performance analysis was done in a national scale and compared it with regional and individual
branch performances. A list of Top 20 SKUs and Bottom 20 SKUs with respect to sales
revenue and no of units was done for regional level and individual branches and compared with
each other, from this study the areas of concerns, which should be given more importance and
poor performing SKUs which should be removed from individual branch or region as a whole
were identified.
With over 25 suppliers and services catering to around 2 lakh retail outlets through its
network of over 600 distributors, the second most important factor affecting the organizationsales and increasing the Cash Cycle was identified as logistical lag. A detailed study about the
forecast report period and lag in delivery was done and the average sales loss for every branch
due to logistical lag was calculated. Comparing the branch location and the supplier location
new forecast report date was advised for individual SKUs which were problematic.
The third major problem was found in the forecast itself. Due to nature of some SKUs
they were over forecasted (optimistic forecasting error) while some SKUs were under
forecasted (pessimistic forecasting error) and the company was found ignoring the seasonal
changes in their forecasting process. The average inventory carryover cost due to optimisticforecasting, seasonal errors and logistics along with loss in sales due to pessimistic forecasting,
seasonal errors, and logistics was computed and a weighted average score was given in terms of
loss incurred by every branch was given. This can be used to identify the important areas of
concern in each and individual branch along with branches to be taken care immediately.
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Studies Conducted:
Product Performance Analysis Logistical lag study Forecasting bias Seasonal product movement
Product Performance Analysis:
Objective of the study:
This study was conducted to find the products which require more focus and things that
should be removed out of the portfolio for overall good of the company. This study was also
conducted to compare branch wise product performances and find the reasons which resulted
in top SKUs of other branches fail miserably in few places.
Method Used:
First individual sales data for each and every branch was consolidated in terms of sales
revenue and sales units. Top and bottom twenty SKUs of each and individual branch and region
were found in terms of SKUs and in terms of sales revenue. This list was compared with all other
branches to find how the branch was performing, if a branch was different from all others, it
was selected for further study. The second part of the study involved in studying deeply in to
Weightage associated with each and individual product in terms of sales and no. of SKUs sold.
This helped me to identify the products which should be given more importance/focus and the
products where focus should be removed.
Shortcomings:
The study fails to find the reasons for any failure or problem that is associated with the
product/branch. This study shows only that there exists a problem associated with such and
such product and with the branch. This study did not take into account of the lost opportunity
of various products due to forecast and logistical errors.
Logistical Lag study:
Objective of the study:
For a company which sources 100% of its final products from outside suppliers with
almost all of the CFL and GLS (which totally accounts for 90% of sales) procured from the North
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region, logistical lag should be minimized, keeping this in mind, the average loss in sales, in turn
resulting in excess inventory was to be found to improve its Cash Cycle.
Method Used:
By taking the shipment in transit, which was a result of late forecast-reporting, which inturn resulted in loss of sales and excess inventory, the exact value lost in terms of sales profit
and carryover cost was computed for each and every branch.
Seasonal product movement:
Objective of the study:
This study was conducted to identify any seasonal or cyclical behavior within the
product sales movement.
Method Used:
Graphical method was used to identify the cyclical movements. Sales movements of
various products for the last 3 years were plotted together to identify the cyclic movements. If
the cyclic movement of the product was not accounted, the amount which could have been
saved by avoiding that mistake was calculated and accounted for improvements.
Forecast Bias and Seasonal errors:
Objective of the study:
This study was done to find the exact value of excess inventory which was more than the
normal level to service 95% of the cases (95% service levels), loss in sales due to pessimistic
forecasting of some products and loss in sales in excess inventory due to seasonal changes,
which was not taken into account while calculating the forecasts.
Method Used:
First the inventory levels as a function of last five month sales, required for 95% service
levels, as a historical trend of different product groups were calculated and this number was
compared with the inventory levels and the causes for deviations, if any, was categorized into
the known error terms. The error terms were then categorized as Pessimistic forecasting error,
Optimistic forecasting error, Cyclic/Seasonal error and the Logistical Lag error.
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Study Results and Conclusions:
Based on the study carried out, the performance of each and every branch is reported to
the company on various parameters. The performance is compared with its regional peers and
the national average.
Since its not possible to include all the parameters and all the branches within the given
word limit of the project, only important parameters for three of one branch of the East region,
is explained here to illustrate the structure of the results given to the company. Summary for all
the 15 branches is given in the end.
Results for Branch wise Study:
Branch: Kolkata
Region: East
Kolkata is an average branch in terms of sales, occupies 2nd
position in terms of sales in
eastern region and 10 in national level. Kolkata accounts for 4.07% of national sales and 2.30%
of all units sold in the country by CEMA. The branch is having 120 active SKUs and
approximately 2 crores in sales for the financial year 2010-2011. Out of 175 active SKUs of
CEMA, Kolkata focuses only on 120, but still the last twenty SKUs accounts for less than 0.5% of
the overall sales of the branch in both Sales volume classification and in Sales units
classification.
Table 1.1
Branch Average SalesSales Contribution to
the country %Ranks
Portfolio
Portfolio Rank
Units Amount Units Amount Units Amount Size %Rank
Kolkata 579879 19449341 2.30% 4.07% 11 10 120 68.5 9
Contribution of Top
20
Contribution of Bottom
20
Units Amount Units Amount
91.74% 86.75% 0.14% 0.19%
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Top SKUs of the branch:
Top20 by sales revenue:
Table 1.2
By Sales Amount(Yearly Fig)
Top20 by sales value
Name SV SUSV%Within
Branch
SU%Within
Branch
CEMA CFL ENDURA T4 15W 2U 65K B22 3086955.7 39205 15.87% 6.76%
CEMA CFL ENDURA T4 20W 3U 65K B22 2743141.0 28499 14.10% 4.91%
CEMA CFL WHIRLITE T3 23W SPIRAL 65K B22 1880791.9 16452 9.67% 2.84%
CEMA FTL TC3 4 40W T12 1860012.5 68142 9.56% 11.75%
CEMA HYPHEN-D T-5 batten 28w 818640.0 2508 4.21% 0.43%
CEMA GLS CLEAR 100W 230V BC CL/150PK 711017.4 114989 3.66% 19.83%
CEMA CFL ENDURA T4 11W 2U 65K B22 695958.5 8646 3.58% 1.49%
CEMA CFL TINY T3 5W 2U 65K B22 621654.6 7989 3.20% 1.38%CEMA CFL TINY T3 8W 3U 65K B22 537143.8 6456 2.76% 1.11%
CEMA GLS CLEAR 60W 230V BC CL/150PK 510916.7 85771 2.63% 14.79%
CEMA CFL ENDURA T4 23W 3U 65K B22 463350.8 3823 2.38% 0.66%
CEMA CFL ENDURA T4 30W 4U 65K B22 396673.9 2500 2.04% 0.43%
CEMA CFL WHIRLITE T4 27W SPIRAL 65K B22 393910.7 2580 2.03% 0.44%
CEMA Trende T-8 36w Elec. Batten 362340.0 1647 1.86% 0.28%
CEMA CFL ENDURA T4 36W 4U 65K B22 347229.3 2027 1.79% 0.35%
CEMA FTL FSU STARTER 20/40W 230-250V 341860.0 75480 1.76% 13.02%
CEMA CFL WHIRLITE T4 32W SPIRAL 65K B22 271472.5 1413 1.40% 0.24%
CEMA Prajjwal 36/40w FTL ballast 214345.0 3263 1.10% 0.56%CEMA CFL WHIRLITE T3 15W SPIRAL 65K B22 209909.8 1810 1.08% 0.31%
CEMA CFL BIGLITE T5 65W 4U 65K B22 203307.4 527 1.05% 0.09%
CEMA FTL ENERGY SAVER 36W 202440.0 8040 1.04% 1.39%
86.75% 83.08%
As we can see, 16% of the top SKUs in terms of sales value results in around 87% of sales
in terms of volume and they result in 83% of all the units sold in the branch. The company
wants to find out the missing links in some of the poor performing SKUs which are performing
well in other branches.
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Top20 by sales units:
Table 1.3
Top20 by sales units
Name SV SUSV%Within
Branch
SU%Within
Branch
CEMA GLS CLEAR 100W 230V BC CL/150PK 711017.4 114989 3.66% 19.83%
CEMA GLS CLEAR 60W 230V BC CL/150PK 510916.7 85771 2.63% 14.79%
CEMA FTL FSU STARTER 20/40W 230-250V 341860.0 75480 1.76% 13.02%
CEMA FTL TC3 4 40W T12 1860012.5 68142 9.56% 11.75%
CEMA CFL ENDURA T4 15W 2U 65K B22 3086955.7 39205 15.87% 6.76%
CEMA GLS CLEAR 40W 230V BC CL/150PK 192657.0 32550 0.99% 5.61%
CEMA CFL ENDURA T4 20W 3U 65K B22 2743141.0 28499 14.10% 4.91%
CEMA CFL WHIRLITE T3 23W SPIRAL 65K
B221880791.9 16452 9.67% 2.84%
CEMA GLS 25W 230V BC CL /150 pk 78927.0 13350 0.41% 2.30%
CEMA CFL ENDURA T4 11W 2U 65K B22 695958.5 8646 3.58% 1.49%
CEMA FTL ENERGY SAVER 36W 202440.0 8040 1.04% 1.39%
CEMA CFL TINY T3 5W 2U 65K B22 621654.6 7989 3.20% 1.38%
CEMA CFL TINY T3 8W 3U 65K B22 537143.8 6456 2.76% 1.11%
CEMA GLS CLEAR 200W 250V BC CL 69000.0 5520 0.35% 0.95%
CEMA CFL ENDURA T4 23W 3U 65K B22 463350.8 3823 2.38% 0.66%
CEMA NIGHT LAMP 15W 250V BC YELLOW 22593.4 3306 0.12% 0.57%
CEMA Prajjwal 36/40w FTL ballast 214345.0 3263 1.10% 0.56%
CEMA NIGHT LAMP 15W 250V BC RED 19944.0 2880 0.10% 0.50%
CEMA CFL WHIRLITE T4 27W SPIRAL 65K
B22 393910.7 2580 2.03% 0.44%
CEMA NIGHT LAMP 15W 250V BC MILKY 17289.0 2510 0.09% 0.43%
CEMA HYPHEN-D T-5 batten 28w 818640.0 2508 4.21% 0.43%
79.60% 91.74%
As we can see, like all other northern branches, GLS is completely absent from the top
SKUs by sales list even though we can see many of those SKUs feature in the Top20 by sales
units list. One interesting fact to be noted is that the top 20 SKUs of the branch accounts for
85% and 92% of all its sales revenue and the units sold respectively.
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Bottom SKUs of the branch:
Bottom 20 by Sales:
Table 1.4
Bottom20
Name SV SU SV%Within Branch SU%WithinBranch
CEMA Candle Clear 25W B22 412.5 50 0.00% 0.01%
CEMA Candle Clear 40W B22 825.0 100 0.00% 0.02%
CEMA Candle Clear 60W B22 825.0 100 0.00% 0.02%
CEMA CFL WHIRLITE T3 9W SPIRAL 27K B22 1079.1 10 0.01% 0.00%
CEMA Candle Coated 25W E14 1202.5 130 0.01% 0.02%
CEMA Candle Coated 25W E14 1202.5 130 0.01% 0.02%
CEMA Candle Clear 25W E14 1268.8 145 0.01% 0.03%
CEMA Classic Round Clear 40W E14 1312.5 150 0.01% 0.03%
CEMA Maxlite CFL ballast 10-13w 240v 1550.0 25 0.01% 0.00%CEMA Classic Round Clear 60W E14 1750.0 200 0.01% 0.03%
CEMA Classic Round Coated 40W E14 1850.0 200 0.01% 0.03%
CEMA Classic Round Coated 40W E27 1850.0 200 0.01% 0.03%
CEMA HPSV 70 E 2090.0 11 0.01% 0.00%
CEMA Classic Round Clear 40W E27 2187.5 250 0.01% 0.04%
CEMA Classic Round Clear 60W E27 2187.5 250 0.01% 0.04%
CEMA Candle Coated 60W E27 2312.5 250 0.01% 0.04%
CEMA Candle Clear 40W E27 2362.5 270 0.01% 0.05%
CEMA Candle Coated 40W E27 2682.5 290 0.01% 0.05%
CEMA HPSV 150 T 2700.0 12 0.01% 0.00%CEMA Candle Coated 40W E14 2775.0 300 0.01% 0.05%
CEMA Classic Round Coated 60W E14 2775.0 300 0.01% 0.05%
0.19% 0.58%
The real concern is with the bottom SKUs of the branch. The last 30 of the branch
accounts for only 0.5 % of the branchs sales and no of units sold. Some particular SKUs product
categories like CEMA HPSV and CEMA Whirl light etc. can be removed from the portfolio as they
account for less than 0.1% of the sales. The inventory charges of HPSV and Whirl light will
certainly exceed the profit margins. Though Whirl light is categorized under CFL retrofit, it can
be seen that it is failing miserably. One interesting thing to note is that CFL Tiny and Maxlite
having some of SKUs which are not having any sales, while some of its peers are doing well in
the same region. These inactive Tiny/Maxlite pair carries on some amount of inventory
throughout cycle period.
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Bottom 20 by Sales Units:
Table 1.5
Bottom20
Name SV SU SV%Within Branch SU%WithinBranch
CEMA MH IBU 70w 3680.0 8 0.02% 0.00%
CEMA CFL MAXLITE-D 18W/2700K 2 Pin 0.0 10 0.00% 0.00%
CEMA CFL WHIRLITE T3 9W SPIRAL 27K B22 1079.1 10 0.01% 0.00%
CEMA HPSV 70 E 2090.0 11 0.01% 0.00%
CEMA HPSV 150 T 2700.0 12 0.01% 0.00%
CEMA HPSV 150 E 3480.0 12 0.02% 0.00%
CEMA 400W MH SE-Tubular-E40 8730.0 18 0.04% 0.00%
CEMA Maxlite CFL ballast 10-13w 240v 1550.0 25 0.01% 0.00%
CEMA CFL WHIRLITE T3 23W SPIRAL 65KE27
4292.8 30 0.02% 0.01%
CEMA CFL WHIRLITE T3 23W SPIRAL 27K
B224370.0 30 0.02% 0.01%
CEMA HPSV 70 T 4311.0 35 0.02% 0.01%
CEMA Candle Clear 25W B22 412.5 50 0.00% 0.01%
CEMA FTL T5 28W/827 3000.0 50 0.02% 0.01%
CEMA CFL TINY T3 5W 2U 2700K E27 3900.0 50 0.02% 0.01%
CEMA CFL TINY T3 8W 3U 27K E27 4185.9 50 0.02% 0.01%
CEMA CFL WHIRLITE T3 15W SPIRAL 27K
B225950.0 50 0.03% 0.01%
CEMA CFL WHIRLITE T3 15W SPIRAL 65KE27
7059.6 60 0.04% 0.01%
CEMA CFL WHIRLITE T3 9W SPIRAL 65K E27 7679.1 70 0.04% 0.01%
CEMA HYPHEN-E T-5 batten 14w 19600.0 70 0.10% 0.01%
CEMA Maxlite CFL ballast 5-11w 240v 4875.0 75 0.03% 0.01%
CEMA Maxlite CFL ballast 18w 240v 4975.0 75 0.03% 0.01%
0.50% 0.14%
Problematic areas:
The overall study indicates that forecasting errors accounts for most of the problems in
the branch. With almost 40% of the excess inventory and 40% in loss of sales is due to
forecasting errors. This excess inventory is calculated by calculating the excess inventory which
was more than the safety stock required for 95% service levels.
As far as logistics as considered the branch is below par than its peers and has to be
focused on.
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Seasonal Changes:
Seasonal changes in products such as CEMA Maxlite and CEMA HPSV in all the volt
ranges are not considered buy the company. This resulted in excess inventory in the branch for
most of the time in the last two years.
Logistical Problems:
Logistical problems are observed with the GLS suppliers form Noida and Delhi, so it is
advised for the branch to revise their lead time estimates and change their order placing cycle
to avoid further delays in from areas.
Monthly Savings that can be achieved:Table 1.6
Branch Name Kolkata
Sales as a % of national sales Weightage 4.07%Average sales Rs 1620778.39
Average excess stock at close Rs 2490725.57
Average deficit in stock Rs 583577.82
Average inventory in excess due to
forecast errorsRs 1245362.79
Cost of capital WACC% (industrial average) 11.00%
Error type
Forecast Pessimistic 40.00%
Optimistic 40.00%Seasonal 5.00%
Logistics 7.00%
Savings that can be made if errors are corrected
Unrealized profit=Profitmargin*avg deficit in
stock*pessimistic28011.74
Savings from reduced inventory by
correcting optimistic forecast
=optimistic*avg excess inventory
excess to req safety stock
inventory*WACC+Holding cost
79703.22
Savings from reduced inventory by
correcting optimistic forecastSavings from improved logistical
services
=optimistic*avg excess inventory
excess to req safety stockinventory*WACC+Holding cost 7540.05
Savings from correcting seasonal
changes5385.75
Total Gain/month 120640.75
As we can see there is a lot of space for improvement in this branch and we can save as
much as 120640 Rupees per month from this branch.
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Results for Branch wise Study:
Region: East
East region consists of Kolkata, Guwahati and Ranchi. This is the smallest region, both in
terms of number of branches and in terms of sales. Last year the region accounted for 5.3Crores in sales. The region holts 120 portfolios and accounts for 5.5% of overall sales in terms of
units sold and 11.2% in terms of value of sales. Though it governs only 68% of the active SKUs of
CEMA, the sales in the region are highly skewed. The 16% of the top products accounts for 83%
and 91% in terms of number of units and value sold.
Table 2.1
Branch Average SalesSales Contribution
to the country %Ranks Portfolio
Units Amount Units Amount Units Amount Size % RankEast 1395661 53487360 5.55% 11.19% 4 4 120 68 4
Contribution of Top
20
Contribution of Bottom
20
Units Amount Units Amount
83.34% 91.32% 0.07% 0.28%
Guwahati is the top performer in the branch, followed by Kolkata and Ranchi. Due to
less number of branches in the region and presence of poor performers like Ranchi in the list of
branches, this region is not having much impact on the overall performance of the company.
Due to less importance, these branches are not given required attention, there
by the logistical lags in the branch as a whole is high, and the geographical disadvantage
magnifies it.
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Top SKUs of the Region:
Top20 by sales revenue:
Table 2.2
Top20
Name SV SU SV%WithinBranch
SU%WithinBranch
CEMA CFL ENDURA T4 15W 2U 65K B22 13574517.2 173770 25.38% 12.45%
CEMA CFL ENDURA T4 20W 3U 65K B22 9824542.0 107929 18.37% 7.73%
CEMA CFL ENDURA T4 11W 2U 65K B22 3418573.2 42654 6.39% 3.06%
CEMA CFL WHIRLITE T3 23W SPIRAL 65K
B223144677.6 31179 5.88% 2.23%
CEMA FTL TC3 4 40W T12 3054891.5 110236 5.71% 7.90%
CEMA CFL TINY T3 8W 3U 65K B22 2115961.2 25698 3.96% 1.84%
CEMA GLS CLEAR 100W 230V BC CL/150PK 2103244.3 327988 3.93% 23.50%
CEMA CFL TINY T3 5W 2U 65K B22 1980321.0 25740 3.70% 1.84%
CEMA GLS CLEAR 60W 230V BC CL/150PK 1475889.8 238959 2.76% 17.12%
CEMA HYPHEN-D T-5 batten 28w 1171940.0 3588 2.19% 0.26%
CEMA CFL ENDURA T4 23W 3U 65K B22 1065834.9 8820 1.99% 0.63%
CEMA CFL WHIRLITE T4 27W SPIRAL 65K
B22860909.4 5690 1.61% 0.41%
CEMA CFL BIGLITE T5 65W 4U 65K B22 735169.6 1906 1.37% 0.14%
CEMA CFL ENDURA T4 30W 4U 65K B22 667557.5 4220 1.25% 0.30%
CEMA CFL WHIRLITE T4 32W SPIRAL 65K
B22651789.9 3430 1.22% 0.25%
CEMA CFL BIGLITE T5 45W 4U 65K B22 587710.3 2056 1.10% 0.15%
CEMA CFL ENDURA T4 36W 4U 65K B22 576325.0 3372 1.08% 0.24%
CEMA Trende T-8 36w Elec. Batten 509740.0 2317 0.95% 0.17%
CEMA CFL TINY T3 15W 3U 65K B22 477141.7 4833 0.89% 0.35%
CEMA CFL WHIRLITE T3 15W SPIRAL 65K
B22476265.7 4225 0.89% 0.30%
CEMA FTL ENERGY SAVER 36W 369685.0 14650 0.69% 1.05%
91.32% 81.92%
As we can see, 16% of the top SKUs in terms of sales value results in around 91% of sales
in terms of volume and they result in 82% of all the units sold in the branch. Though this region
is not been advertised well the top performers all over the country are having a good presence
in this region. The GLS sector is absent in the region as a whole, which is a point to note as the
sales are fully driven by the CFL sector.
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Top20 by sales units:
Table 2.3
Top20
Name SV SUSV%Within
Branch
SU%Within
Branch
CEMA GLS CLEAR 100W 230V BC CL/150PK 2103244.3 327988 3.93% 23.50%
CEMA GLS CLEAR 60W 230V BC CL/150PK 1475889.8 238959 2.76% 17.12%
CEMA CFL ENDURA T4 15W 2U 65K B22 13574517.2 173770 25.38% 12.45%
CEMA FTL TC3 4 40W T12 3054891.5 110236 5.71% 7.90%
CEMA CFL ENDURA T4 20W 3U 65K B22 9824542.0 107929 18.37% 7.73%
CEMA FTL FSU STARTER 20/40W 230-250V 357500.0 78920 0.67% 5.65%
CEMA GLS CLEAR 40W 230V BC CL/150PK 353475.5 57897 0.66% 4.15%
CEMA CFL ENDURA T4 11W 2U 65K B22 3418573.2 42654 6.39% 3.06%
CEMA CFL WHIRLITE T3 23W SPIRAL 65K
B223144677.6 31179 5.88% 2.23%
CEMA CFL TINY T3 5W 2U 65K B22 1980321.0 25740 3.70% 1.84%
CEMA CFL TINY T3 8W 3U 65K B22 2115961.2 25698 3.96% 1.84%
CEMA GLS 25W 230V BC CL /150 pk 113244.8 18893 0.21% 1.35%
CEMA FTL ENERGY SAVER 36W 369685.0 14650 0.69% 1.05%
CEMA GLS CLEAR 200W 250V BC CL 124625.0 9970 0.23% 0.71%
CEMA CFL ENDURA T4 23W 3U 65K B22 1065834.9 8820 1.99% 0.63%
CEMA NIGHT LAMP 15W 250V BC RED 46188.0 6620 0.09% 0.47%
CEMA NIGHT LAMP 15W 250V BC YELLOW 45537.4 6546 0.09% 0.47%
CEMA CFL WHIRLITE T4 27W SPIRAL 65K
B22860909.4 5690 1.61% 0.41%
CEMA NIGHT LAMP 15W 250V BC MILKY 36693.0 5250 0.07% 0.38%
CEMA CFL TINY T3 15W 3U 65K B22 477141.7 4833 0.89% 0.35%
CEMA NIGHT LAMP 15W 250V BC FROSTED 32058.0 4720 0.06% 0.34%
83.34% 93.64%
In number of units sold, the region is following the similar trend as the top performers in
terms of sales volume. It clearly indicates that 84% of the products merely accounts for 7
percent of the units sold. The company should take this into account and decide whether it
should keep those SKUs or should they change their sales strategy for these products.
Bottom SKUs of the region:
Bottom 20 by Sales:
The real concern is with the bottom 70 SKUs of the branch. The last 50 of the branch
accounts for only 3 % of the branchs sales and no of units sold. The bottom 30 of the branch
accounts for only 0.5% of the sales. Some SKUs product categories like CEMA HPSV and CEMA
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Whirl light, CFL Tiny, CFL Candle light, Maxlite, Classic round etc, Can be shelved so that the
Nagpur can focus on other areas.
Table 2.4Bottom20
Name SV SUSV%Within
Branch
SU%Within
Branch
CEMA Candle Clear 25W B22 412.5 50 0.00% 0.00%
CEMA Maxlite CFL ballast 10-13w 240v 1550.0 25 0.00% 0.00%
CEMA Candle Clear 60W B22 1633.5 198 0.00% 0.01%
CEMA Candle Clear 40W B22 1650.0 200 0.00% 0.01%
CEMA Classic Round Clear 60W E14 1925.0 220 0.00% 0.02%
CEMA HPSV 70 E 2090.0 11 0.00% 0.00%
CEMA Candle Clear 25W E14 2318.8 265 0.00% 0.02%CEMA HPSV 150 T 2700.0 12 0.01% 0.00%
CEMA Candle Coated 25W E14 2775.0 300 0.01% 0.02%
CEMA Candle Coated 25W E14 2775.0 300 0.01% 0.02%
CEMA CFL MAXLITE-S 11W/2700K 2Pin 2923.6 80 0.01% 0.01%
CEMA Classic Round Clear 40W E27 3062.5 350 0.01% 0.03%
CEMA MH IBU 70w 3680.0 8 0.01% 0.00%
CEMA Classic Round Clear 60W E27 3937.5 450 0.01% 0.03%
CEMA CFL MAXLITE-S 11W/6500K 4Pin 4033.6 110 0.01% 0.01%
CEMA CFL TINY T3 5W 2U 2700K E14 4038.7 50 0.01% 0.00%
CEMA CFL WHIRLITE T3 15W SPIRAL 27KE27
4638.4 40 0.01% 0.00%
CEMA Maxlite CFL ballast 5-11w 240v 4875.0 75 0.01% 0.01%
CEMA Candle Coated 60W E27 4930.3 533 0.01% 0.04%
CEMA Maxlite CFL ballast 18w 240v 4975.0 75 0.01% 0.01%
CEMA Classic Round Clear 40W E14 4978.8 569 0.01% 0.04%
0.12% 0.28%
As we can see the bottom 20 SKUs by volume accounts for only 0.12% of the sales. But
the companys policy of equally allocating the overheads over the entire product range along
with the advertisement costs will make these products costlier to have it in the overall portfolio,
so the company should take a look into their accounting principles based on this.
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Bottom 20 by Sales Units:
Table 2.5
Bottom20
Name SV SUSV%Within
Branch
SU%Within
Branch
CEMA MH IBU 70w 3680.0 8 0.01% 0.00%
CEMA CFL MAXLITE-D 18W/2700K 2 Pin 0.0 10 0.00% 0.00%
CEMA HPSV 70 E 2090.0 11 0.00% 0.00%
CEMA HPSV 150 T 2700.0 12 0.01% 0.00%
CEMA HPSV 150 E 6180.0 24 0.01% 0.00%
CEMA Maxlite CFL ballast 10-13w 240v 1550.0 25 0.00% 0.00%
CEMA 70W MH DE RX7S-DL 6625.0 25 0.01% 0.00%
CEMA HPSV 400 T 11700.0 36 0.02% 0.00%
CEMA CFL WHIRLITE T3 15W SPIRAL 27K
E274638.4 40 0.01% 0.00%
CEMA HPSV 70 T 5789.0 47 0.01% 0.00%
CEMA 250 W MH SE-Tubular-E40 22080.0 48 0.04% 0.00%
CEMA Candle Clear 25W B22 412.5 50 0.00% 0.00%
CEMA CFL TINY T3 5W 2U 2700K E14 4038.7 50 0.01% 0.00%
CEMA CFL TINY T3 8W 3U 27K E27 5015.9 60 0.01% 0.00%
CEMA CFL WHIRLITE T3 9W SPIRAL 65K E27 7679.1 70 0.01% 0.01%
CEMA Maxlite CFL ballast 5-11w 240v 4875.0 75 0.01% 0.01%
CEMA Maxlite CFL ballast 18w 240v 4975.0 75 0.01% 0.01%
CEMA CFL MAXLITE-S 11W/2700K 2Pin 2923.6 80 0.01% 0.01%
CEMA CFL TINY T3 8W 3U 27K E14 6757.6 80 0.01% 0.01%
CEMA CFL TINY T3 15W 3U 27K B22 8317.6 80 0.02% 0.01%
CEMA 70W MH T G12 DL 49875.0 95 0.09% 0.01%
0.30% 0.07%
The same trend is followed in terms of number of units sold as an average across the
months. The bottom 20 accounts for only 0.3% of overall sales.
Problematic areas:
The overall study indicates that forecasting errors accounts for most of the problems in
the branch. With almost 43.3% of the excess inventory and 46.6% in loss of sales is due to
forecasting errors. This excess inventory is calculated by calculating the excess inventory which
was more than the safety stock required for 95% service levels.
As far as logistics is considered the company is below par than its peers and should be
taken to account.
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Seasonal Changes:
Seasonal changes in products such as CEMA Candle Clear and CEMA Classic Clear in all
the volt ranges are not considered buy the company. This resulted in excess inventory in the
branch for most of the time in the last two years.
Logistical Problems:
Logistical problems are observed with the GLS and CFL candle suppliers form
Noida and Delhi, so it is advised for the region to revise their lead time estimates and change
their order placing cycle to avoid further delays in from areas.
Monthly Savings that can be achieved:
Table 1.6
Branch Name East
Sales as a % of national sales Weightage 11.19%
Average sales Rs 4457280.04
Average excess stock at close Rs 4457280.15
Average deficit in stock Rs 1368571.04
Average inventory in excess due to forecast
errorsRs 2476006.11
Cost of capital WACC% (industrial average) 11.00%
Error type
Forecast Pessimistic 43.33%
Optimistic 46.67%
Seasonal 4.33%
Logistics 4.00%
Savings that can be made if errors are corrected
Unrealized profit=Profitmargin*avg deficit in
stock*pessimistic71165.69
Savings from reduced inventory by correcting
optimistic forecast
=optimistic*avg
inventory*WACC+Holding cost
176621.77
Savings from improved logistical services 9911.50
Savings from correcting seasonal changes 10737.46
Total Gain/month 268436.42
As we can see there is a lot of space for improvement in this branch and we can save as
much as 2.6 lakhs Rupees per month from this region.
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Summary:
The consolidated list for each and every branch and regions were studied and the items
which should be given importance/removed from the portfolio were found. The overall
importance that should be given to different issues in each and every branch was highlightedand suggestions were given to the company. Though the forecasting models is found to be not
working in most of the cases, it can be customized based on the suggestions given, ignoring
forecasting models will make the company fail miserably in meeting the demands from the
market. One of the biggest limitations to the study is that it gives the ultimate benchmark after
the occurrence of the event; we cannot say with hundred percent sureties that it can be
achieved by improving the practices. Its like a company with 100% efficiency, a benchmark.
Table 3.1
Branch Average Sales Sales Contribution tothe country %
Ranks Portfolio
Units Amount Units Amount Units Amount Size % Rank
Kolkata 579879 19449341 2.30% 4.07% 11 10 120 68 9
Guwahati 710637 28098542 2.82% 5.88% 10 7 100 57 13
Ranchi 105145 5939478 0.42% 1.24% 15 15 70 40 15
East 1395661 53487360 5.55% 11.19% 4 4 120 68 4
Ahmedabad 5550729 87707115 22.06% 18.36% 1 1 161 92 2
Bhiwandi 4824246 67464610 19.17% 14.12% 2 2 162 92 1
agpur 719848 10256144 2.86% 2.15% 9 14 100 57 13West 11094823 165427869 NA NA NA NA 162 92 NA
Delhi 411416 11139015 1.63% `2.33% 14 12 138 78 6
Ghaziabad 1775446 54777736 7.06% 11.46% 6 3 152 86 3
Jaipur 1197504 26397670 4.76% 5.52% 7 8 119 68 11
Dehradun 448783 10896550 1.78% 2.28% 13 13 120 68 9
Zirkapur 547606 16312311 2.18% 3.41% 12 11 138 78 6
orth 4380755 119523283 NA NA NA NA 152 86 NA
Bangalore 2215606 36024337 8.80% 7.54% 4 5 140 80 5
Cochin 1903223 44301162 7.56% 9.27% 5 4 116 66 12
Chennai 983438 24040231 3.91% 5.03% 8 9 142 81 4
Hyderabad 3191070 35013025 12.68% 7.33% 3 6 127 72 8
South 8293337 139378755 NA NA NA NA 142 81 NA
India 25164576 477817268 105.55% 111.19% NA NA 175 100 NA
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20I i C h t C h C l b i i D d F ti T h i
The overall savings that can be done in a national level is 23 lakhs per month as
consolidated and shown in Table 3.2.
Table 3.2
Branch Name India
Sales as a % of national sales 111.19%
Average sales 44275385.71
Average excess stock at close 42683309.73
Average deficit in stock 13820917.41
Average inventory in excess due to forecast
errors21589020.90
Cost of capital 11.00%
Error type
Forecast 31.74%
46.51%
4.93%
Logistics 9.75%
Savings that can be made if errors are corrected
Unrealized profit 526419.97
Savings from reduced inventory by correcting
optimistic forecast
1536273.56
Savings from improved logistical services 201203.33
Savings from correcting seasonal changes 101749.19
Total Gain/month 2365646.04
Though the analysis is showing promising returns by removing the forecasting errors and
concentrating on the logistical lag along with improved focus, the analysis fails to capture the
important picture, that is some of the SKUs, even if they sell only 2-3 per month, they only form
a correct mixture or a bundle for the product group as a whole, absent of those small product
groups may have a huge impact over other sales, the analysis fails to take a look at that
perspective as, that is way too beyond scope of this study.
Reference:
Consolidated sales Data of CEMA Electric Lighting Products India Pvt. Ltd., for thefinancial year 2010-11
Operations Management, Jae K. Shim, Joel G. Siegel.