Dear friends,
Recently, a client approached me for streamlining demand for their product. The brief about the client is given below.
Client buys imported Palmolive oil. However, it is in crude form. Client refines it and sells it to the traders. Traders sell the refined oil to the end users who are retail customers, shopkeepers, caterers, hoteliers etc. The problems with the client is that his customers i.e. traders do not have any uniformity in their demand pattern. Sometimes all of them place their demand occasionally he loses his sale. On the contrary, sometimes nobody places demand and capacity remains idle.
To avoid cost of stock-out, he is unable to store the inventory of refined oil. The price of the Palmolive oil at commodity exchange is fluctuating. Should the oil is bought at higher price and later if the prices fall then there is risk of incurring losses. Corollary of this is that oil could be bought at lower price and it can be sold at higher price also. In such case, sale could give higher profits. However, client is risk averse and does not want to deal with the fluctuations in the oil prices.
The additional restrictions are because of total lead time. Total import cycle consist of time required for import, time for process and time for delivery to the client.
In addition to the use of traditional mathematical tools like moving average, weighted moving average, regression analysis, can you suggest some other solution?
Thanks,
Dinesh Divekar
From India, Bangalore
7879Recently, a client approached me for streamlining demand for their product. The brief about the client is given below.
Client buys imported Palmolive oil. However, it is in crude form. Client refines it and sells it to the traders. Traders sell the refined oil to the end users who are retail customers, shopkeepers, caterers, hoteliers etc. The problems with the client is that his customers i.e. traders do not have any uniformity in their demand pattern. Sometimes all of them place their demand occasionally he loses his sale. On the contrary, sometimes nobody places demand and capacity remains idle.
To avoid cost of stock-out, he is unable to store the inventory of refined oil. The price of the Palmolive oil at commodity exchange is fluctuating. Should the oil is bought at higher price and later if the prices fall then there is risk of incurring losses. Corollary of this is that oil could be bought at lower price and it can be sold at higher price also. In such case, sale could give higher profits. However, client is risk averse and does not want to deal with the fluctuations in the oil prices.
The additional restrictions are because of total lead time. Total import cycle consist of time required for import, time for process and time for delivery to the client.
In addition to the use of traditional mathematical tools like moving average, weighted moving average, regression analysis, can you suggest some other solution?
Thanks,
Dinesh Divekar
From India, Bangalore
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
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
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 extend each factor influences the customer's demand that you need to find out. Accuracy of demand enhances when you accurately predict the percentage of influencing factors. To do this one has 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 year old and lot of changes have happened since then, its utility does not diminish even now also.
Thanks,
Dinesh Divekar
From India, Bangalore
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 extend each factor influences the customer's demand that you need to find out. Accuracy of demand enhances when you accurately predict the percentage of influencing factors. To do this one has 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 year old and lot of changes have happened since then, its utility does not diminish even now also.
Thanks,
Dinesh Divekar
From India, Bangalore
Dear Dinesh, you are right. Though some of the techniques are very old their utility is still valid. For example, I learnt 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
I had not checked the date of publication of the article. Thanks for the information.
From United Kingdom
We can fulfill your needs and demands. However, we need detailed information regarding this subject. Kindly contact us mail ID: sriwidh@gmail.com, Mobile: +91 9944000090 for further details.
To your unlimited success,
Jayaraman.K
From India, Madras
To your unlimited success,
Jayaraman.K
From India, Madras
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.
Pl 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 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 loosing any business.
With specific issues related to the Palmolein oil sector, your client also needs to keep track of the offtake of OTHER oils & during festivals, the demand prospects of ghee too......basically competitive oils.
Rgds,
TS
From India, Hyderabad
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.
Pl 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 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 loosing any business.
With specific issues related to the Palmolein oil sector, your client also needs to keep track of the offtake of OTHER oils & during festivals, the demand prospects of ghee too......basically competitive oils.
Rgds,
TS
From India, Hyderabad
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