Dear friends,
Recently, a client approached me to streamline the demand for their product. The brief about the client is given below.
The client purchases imported Palmolive oil in crude form. They refine it and sell it to traders, who then sell the refined oil to end-users such as retail customers, shopkeepers, caterers, and hoteliers. The issue the client faces is that their customers, the traders, do not have uniformity in their demand patterns. Sometimes, all of them place their orders at once, leading to potential sales loss. Conversely, there are times when no orders are placed, leaving the capacity idle.
To avoid the cost of stock-outs, the client is unable to store an inventory of refined oil. The price of Palmolive oil at the commodity exchange fluctuates. Purchasing the oil at a higher price poses the risk of losses if prices fall later. Conversely, buying at a lower price and selling at a higher price could result in increased profits. However, the client is risk-averse and prefers not to deal with fluctuations in oil prices.
Additional restrictions stem from the total lead time. The total import cycle includes the time required for import, processing, and delivery to the client.
Apart from traditional mathematical tools like moving averages, weighted moving averages, and regression analysis, could you suggest other solutions?
Thanks,
Dinesh Divekar
From India, Bangalore
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8032Recently, a client approached me to streamline the demand for their product. The brief about the client is given below.
The client purchases imported Palmolive oil in crude form. They refine it and sell it to traders, who then sell the refined oil to end-users such as retail customers, shopkeepers, caterers, and hoteliers. The issue the client faces is that their customers, the traders, do not have uniformity in their demand patterns. Sometimes, all of them place their orders at once, leading to potential sales loss. Conversely, there are times when no orders are placed, leaving the capacity idle.
To avoid the cost of stock-outs, the client is unable to store an inventory of refined oil. The price of Palmolive oil at the commodity exchange fluctuates. Purchasing the oil at a higher price poses the risk of losses if prices fall later. Conversely, buying at a lower price and selling at a higher price could result in increased profits. However, the client is risk-averse and prefers not to deal with fluctuations in oil prices.
Additional restrictions stem from the total lead time. The total import cycle includes the time required for import, processing, and delivery to the client.
Apart from traditional mathematical tools like moving averages, weighted moving averages, and regression analysis, could you suggest other solutions?
Thanks,
Dinesh Divekar
From India, Bangalore
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Dear Dinesh,
There is not enough information about how long the firm has been in business and whether it has any records, etc. I came across this HBR article on the web http://prof.usb.ve/nbaquero/03%20-%2...%20-%20HBR.PDF. Kindly see if it's of any use.
From United Kingdom
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There is not enough information about how long the firm has been in business and whether it has any records, etc. I came across this HBR article on the web http://prof.usb.ve/nbaquero/03%20-%2...%20-%20HBR.PDF. Kindly see if it's of any use.
From United Kingdom
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Dear Mr. Simhan,
To make your demand forecasting accurate, one has to study the factors on which the customers' demand depends. Once you identify those factors, to what extent each factor influences the customer's demand, you need to find out. The accuracy of demand enhances when you accurately predict the percentage of influencing factors. To do this, one has to master regression analysis with multiple variables. However, it is much easier said than done.
Thanks for sharing the article from HBR. Though it is more than 21 years old and a lot of changes have happened since then, its utility does not diminish even now.
Thanks,
Dinesh Divekar
From India, Bangalore
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To make your demand forecasting accurate, one has to study the factors on which the customers' demand depends. Once you identify those factors, to what extent each factor influences the customer's demand, you need to find out. The accuracy of demand enhances when you accurately predict the percentage of influencing factors. To do this, one has to master regression analysis with multiple variables. However, it is much easier said than done.
Thanks for sharing the article from HBR. Though it is more than 21 years old and a lot of changes have happened since then, its utility does not diminish even now.
Thanks,
Dinesh Divekar
From India, Bangalore
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Dear Dinesh,
You are right. Though some of the techniques are very old, their utility is still valid. For example, I learned queuing theory 40 years ago, and the same, I was teaching a few years ago. I had not checked the date of publication of the article. Thanks for the information.
From United Kingdom
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You are right. Though some of the techniques are very old, their utility is still valid. For example, I learned queuing theory 40 years ago, and the same, I was teaching a few years ago. I had not checked the date of publication of the article. Thanks for the information.
From United Kingdom
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We can fulfill your needs and demands. However, we need detailed information regarding this subject. Kindly contact us via email at sriwidh@gmail.com or by phone at +91 9944000090 for further details.
To your unlimited success,
Jayaraman.K
From India, Madras
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To your unlimited success,
Jayaraman.K
From India, Madras
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Hello Dinesh Divekar,
This is the typical scenario for all retail products, especially so for those products that depend predominantly on imports.
But more inputs would be better, like the geographic area(s) being covered by your client, do they have a distributor network, the typical sale volumes/quantum per year, etc.
Please note that factors like the commodity exchange fluctuations, import lead times, etc., are all part of the game in this sector. Ways would need to be figured out to address them; that's the only way for anyone in this sector.
However, one way to figure out the lack of demand planning/forecast from their customers can be tackled by having a reasonably good distributor network who would then work hand-in-hand with the traders within their geographic areas much closer than your client can hope to do realistically.
Most companies that are in similar lines of business adopt this model for the simple reason that the demand varies from location to location, except when it comes to important festivals/occasions where the demand can be comfortably predicted.
A distributor network also helps to have buffer stocks distributed with many rather than one single entity—your client. This spreads out the stocking costs as well as leverages on the stocks across multiple locations from one stockist to another without the fear of losing any business.
With specific issues related to the Palmolein oil sector, your client also needs to keep track of the offtake of other oils and during festivals, the demand prospects of ghee too—basically competitive oils.
Regards,
TS
From India, Hyderabad
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This is the typical scenario for all retail products, especially so for those products that depend predominantly on imports.
But more inputs would be better, like the geographic area(s) being covered by your client, do they have a distributor network, the typical sale volumes/quantum per year, etc.
Please note that factors like the commodity exchange fluctuations, import lead times, etc., are all part of the game in this sector. Ways would need to be figured out to address them; that's the only way for anyone in this sector.
However, one way to figure out the lack of demand planning/forecast from their customers can be tackled by having a reasonably good distributor network who would then work hand-in-hand with the traders within their geographic areas much closer than your client can hope to do realistically.
Most companies that are in similar lines of business adopt this model for the simple reason that the demand varies from location to location, except when it comes to important festivals/occasions where the demand can be comfortably predicted.
A distributor network also helps to have buffer stocks distributed with many rather than one single entity—your client. This spreads out the stocking costs as well as leverages on the stocks across multiple locations from one stockist to another without the fear of losing any business.
With specific issues related to the Palmolein oil sector, your client also needs to keep track of the offtake of other oils and during festivals, the demand prospects of ghee too—basically competitive oils.
Regards,
TS
From India, Hyderabad
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