Phase III - D.P. definition travails

Update:
Hi all,

Another Q I got asked recently which, I think, bears wider dissemination.

1. The 40 slide limit is the upper bound. Feel free to have a lower #slides in your deliverable. No problem.

2. The amount of work Phase III may take, by my estimate would be about 15-20 person hours in all. Say about 3 hours per group member. Anything much more than that and perhaps you are going about it the wrong way. The project is the high point of applied learning in MKTR_125. So yes, 3-4 hours of effort on the project is not an unfair amount of load. Besides, effort correlates well with learning, in my experience.

3. Do allow yourself to have fun with the project - its not meant to be some sooper-serious burden, oh no. Keeping a light disposition, a witty touch, a sense of optimism and the big-picture in mind helps with flexibility, creativity, out-of-box and all those nice things, in my experience. Whats more, if you enjoyed doing the project, rest assured it *will* show in the output.

Hopefully that allays some concerns about workload expectations etc. relating to Phase III.

Sudhir

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Folks,

The example PPTs putup don't have a D.P. explicitly written down because I had given the D.P. in project 2009. In Project 2011 however, you have been given the flexibility to come up with a D.P. of your own, consistent with the project scope. This is both a challenge and an opportunity.

I got some Qs on whether the handset section responses can be ignored because client is primarily a service provider. Well, the handset section contains important information about emerging trends in the consumer's mindspace, the mobile application space and the mobile-related brands' perception space. A telecom service provider would dearly like to know how many target segment people have/are switching to smartphones, which apps they use most often so that the carrier can emphasize those apps more and so on. So yes, the handset section should not be ignored, IMHO.

Hope that clarified.

Sudhir

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Got an email outlining whether such-and-such was a good D.P. - R.O. combo.

Now, I can;t share what the D.P. itself was but my response to that team had generalities which might do with some dissemination within the class.

Hi R and team,


Looks good. However, I don't quite see what the decision problem is. Step 1 seems to state more an R.O. than a D.P.

Sure, sometimes a D.P. maps exactly onto a single R.O. and that may well be the case here. But such a D.P. would perhaps be overly narrow considering the project scope initially outlined.

I'd rather you state a broader D.P. and break it down into 3 R.O.s each corresponding to the S, T and P parts of S-T-P.

Well, that's my opinion, you don't necessarily have to buy into it. What you do is ultimately your call.

Do email with queries as they arise.

Good luck with the project and happy learning.
Sudhir

More miscell Q&A:

Dear Sir,


While running the factor analysis on the pychographic questions, do we re-label the levels of agreement and disagreement as 1-5? Will this help us in any way?

Another way out could be to label the responses as 1 and 0 where 1 is for a level of agreement and 0 for disagreement. In the Ice-Cream Survey HW the responses to these psychographic questions were binary which actually helped in the analysis.

A quick response will be really helpful. Our approach is to first segment the consumers using factor analysis and then find some interesting insights into usage based on these segments.

Cheers,

S

My response:

Hi S,
1-5 (or 1-7 in case of a 7 point scale) is the conventional practice. Safe to go with conventional practice.

You might as well choose to go with something else but may need to justify why.

Alternately, copy the data columns of interest onto a new sheet, and reduce the #responses to three (-1 for disagree, 0 for neither and +1 for agree), re-run factor analysis and see if the variance explained, factor structure etc that you now get is better than with 1-5.

Idea is that as and when you approach specific problems, you think up of neat, creative ways to negotiate it and move on. Therein lies the learning in the analysis portion for MKTR. :)

Hope that helped. Do write in with more queries should they arise.

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Dear Sir,

We are facing an issue with regard to clubbing the dataset with Q48 (in terms of Rank) into the final data set that was uploaded earlier. The following are the discrepancies:

• The new Data set for Q48 does not have serial no’s to link it with earlier set

• The no of rows (entries) in the new data set for Q48 are more than the original one

• There should be ranks from 1 to 3 but we see that some data entries up to rank 9

It would be beneficial for all the groups to have a final data set with Q48(in terms of ranks) extracted from Qualtrics.

Looking forward for a quick response from your end.

Regards,

M

My response:

Hi M,

The respondent ID that is there (leftmost column in the Q48 dataset) can be used to match (via VLOOKUP func in excel) with the same rows in the original dataset. The blogpost made a mention of this specifically.

Once you match the Q48 dataset entries to the original dataset ones, the problem regarding #responses less or more in Q48 dataset also goes away.

The ranks 1 to 3 alone are relevant. Some people ranked more than the top 3 items, so you may get upto 9 but that we can ignore, if need be.

Hope that clarifies.

Sudhir
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Received this email today fro group "J":

Dear Sir,

We have the following analysis for our MKTR project:

Decision problem: Foreign handset player wants to enter the Indian market
Research Object: Wants to identify the most lucrative segment to enter.

This would make some of the questions about service provision irrelevant. Do you think we are on the right track?
Regards,

My response:

Hi Team J,


The project scope was designed from the viewpoint of a large Indian telecom service provider.
So a purely handset-maker's perspective would be limiting, I feel and perhaps not entirely consistent with the original project scope document.

My suggestion is you consider modifying the D.P. such that the data on service provider characteristics can also be integrated and used in some manner. For instance, a handset maker looking to ally with a service provider, perhaps.

In general, the D.P. should not be so limiting as to banish a good part of the data we have collected from analysis. There is plenty of scope to creatively come up with D.P.s that while focussing on the handset side of the story also use telecom carrier data.

Hope that clarifies.

Sudhir