(÷3) and (x3) for Buy and Sell

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We hope that this Food for Thought finds you well and that you are experiencing continuing success.


As a famous myth goes - if you hope to get a relatively honest answer on how many dates has a man/woman had in their life, you should divide by 3 based on the man’s figure and multiply by 3 the woman’s figure. In the similar way, when we get a number for a market size or a company value, we should not take it at face value.


Exaggerated market size often misleads clients to make acquisitions of little vale when entering new markets. Maybe this also explain us why 50% of the M&A are unprofitable? In the case we worked on, based on processing of import and export data of 52 models of a product of interest from 5 countries for the last 3 years, our figures showed that the accurate market size is only half of the perceived market size. At the end, our findings helped our client realize: what's the point to make the acquisition because of that product, on account of the 50% market size, and especially when it's just a side-product?


Underestimated market size often limits clients in imagination, thinking or achieving big in any market. In one research, KateChanResearch findings showed that the accurate market size of our client is much bigger than their existing perception from other intelligence reports. However, instead of using basic intelligence approach, KateChanResearch chose methodologies of data processing, went through approximately 300 lines of data, using data mining and data interpretation. At the end, our results helped our client realize: why had we positioned ourselves in a place where numerous but mainly small deals lied, while there are places having relatively smaller number of deals but which are bigger in size?


We wonder if we could also apply the similar formula when we buy and sell, i.e. should we take published figure on market size and divide it by 3 or some other coefficient for acquisition or multiply it when we want to invest in business development?


Thank you so much for your constant support!  We hope that you found this Food for Thought helpful.  In case you would like to work with us, please feel free to let us know.  We are delighted to hear from you. 


Thank you and best regards,


Specializing in Strategy-oriented Research, Data Mining and Data Interpretation.

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12-06 16:03