Question 2

Describe analytics models and data that could be used to make good recommendations

to the retailer. How much shelf space should the company have, to maximize their sales

or their profit?

Of course, there are some restrictions for each product type, the retailer imposed a

minimum amount of shelf space required, and a maximum amount that can be devoted;

and of course, the physical size of each store means there's a total amount of shelf space

that has to be used. But the key is the division of that shelf space among the product

types.

For the purposes of this case, I want you to ignore other factors - for example, don't

worry about promotions for certain products, and don't consider the fact that some

companies pay stores to get more shelf space. Just think about the basic question asked

by the retailer, and how you could use analytics to address it.

As part of your answer, I'd like you to think about how to measure the effects. How will

you estimate the extra sales the company might get with different amounts of shelf

space and, for that matter, how will you determine whether the effect really exists at

all? Maybe the retailer's hypotheses are not all true - can you use analytics to check?

Think about the problem and your approach. Then talk about it with other learners, and

share and combine your ideas. And then, put your approaches up on the discussion

forum, and give feedback and suggestions to each other.

You can use the {given, use, to} format to guide the discussions: Given

{data}, use {model} to {result}. 3 pages is good enough for the lengths

of answer

(*The sample answer is attached)

One of the key issues in this case will be data in this case, thinking about the data

might be harder than thinking about the models.