Perfume Store

Case Statement:​

Your client is a luxury perfume chain. The client is facing fluctuating demand in his store in Mumbai. They want to diagnose the cause of the fluctuating demand and recommend a solution for the same

C: To begin with the problem, I would like to understand our client’s business better. Do we have information on the stores' location and the region's competitive landscape? Also what kind of products are available at the store? Is the product line limited to perfumes or other luxury skincare products?

I: Sure, the information I have on the client is that the store in focus is situated in a mall in Mumbai. There are 2-3 similar stores in the region. The primary product segment is perfume, with other products like skincare.

C: Since when have they seen a fluctuation in demand? Also, do we have some customer reviews of other stores in the region which can suggest that our competitors are also facing the same issue?

I: The client has been facing this problem for the last six months. On the second question, there is no such mention of the inability of competitors to make the product available to the consumer. They seem to be having the correct quantities at the right time.

C: So, as I see it, I should be focusing my attention on our store and the factors which are causing fluctuation in demand

I: Yes, that should be the way to go.

C: Thank you. There are two factors to consider here; first, Is the forecasting method the client is using unable to capture demand correctly? Second; Are the sales and marketing efforts out of sync with the purchase cycles of consumers

I: Good question. Over the past data, we have seen that our forecasting models are consistently off from the actual demand plots.  

C: That is a helpful piece of information. We can narrow down our scope to the forecasting models. Are we seeing this mismatch for all products or only for specific products?

I: The problem appears to be hampering all products.

C: Now, I would like to focus on the forecasting model. Any model will have 

Following attributes to it: Customer demographics, product characteristics, competitor characteristics, and regulatory changes, if any. Has there been a change in any of the following factors?

I: That’s thought well put; rest aside, the client has been launching a new line of products continuously to appeal to his luxury customer segment. 

C: That, I guess, will be an inherent trait of the segment client is catering to; exclusivity drives the sale of this segment, and new products on continuous basis help do the same.

I: Yes, correct! I think we have found the issue; what can you recommend to the client so that they optimize their forecasting method?

C: Yes, sure; since the client has been in the business for a long time, for every segment, historical data will be available. The client can use historical data to calculate the expected mean value of orders to maximize profits. The model will also include the cost of underordering and over-ordering as well.

I: Yeah, that seems to be an idea that can work. We can close the case now. It was great talking to you!

Background Information:

Client: Luxury perfume retailer

Competitor: No major changes

Time Frame: A few months

Geography : Store is in Mumbai

Case recommendations:

The case here required to have some basic understanding of how forecasting models work. One way to approach such cases which are dependent on internal factors is to scope the problem down. It helps you make headways into understand the root cause of the problem