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Business/Economics homework

Question asked by lab0rratte on Jan 22, 2015
Latest reply on Jan 24, 2015 by szwillinger

Hi everybody,

I have a problem with my homework. Can somebody help me with ideas and a way how to solve the problem?

I'm thinking through solving it with clusters and a buffer that sounds reasonable. Are there also good ways with the network, business or geostatistical analyst?


Thx for any help



Here the problem:



The client is a beverage service distributor undergoing a sales force transformation effort. They

have 60+ divisions with approximately 50,000 customer sites. Each site is classified as either a

"street" account (e.g. mom-and-pop restaurant) or a "national" account (e.g. hospitals).

Typically, commissioned salespeople called Territory Managers (or TM's) handle the street

accounts, and salaried salespeople called National Account Managers (or NAM's) handle the

national accounts. Salespeople periodically visit their accounts in person.

However, based in part on geography, some national accounts are handled by TM's. Key West,

Florida, is a prototypical example – Key West's cluster of accounts is remote relative to the

client's other accounts, and contains both street accounts and a few national accounts. Rather

than dispatch a NAM's all the way to Key West to visit national accounts, the client has

assigned all the street and most national accounts there to TM's, so fewer salesperson are

inconvenienced by the journey to the remote location.

The client recognizes however that commission driven TM's are more expensive, harder to

manage and harder to staff than salaried NAM's, so the out team is investigating the

potential savings associated with moving some of the national accounts that are currently

managed by TM's over to NAM's. Our team wants to make an intelligent recommendation that

leaves situations like Key West as they are. Initially, the client wants GeoAnalytics to help

quantify the percent of national accounts currently managed by TM's that should remain the

responsibility of TM's rather than being shifted to NAM's.

The client has requested the following initial deliverables:

1) A percentage of national accounts to be excluded from the shift to NAM's;

2) A map of the excluded accounts;

3) An explanation of the approach to establishing the exclusions.

It's acceptable to limit the initial analysis to 5 or 6 divisions to speed up processing time if

  1. needed.

When discussing analytical approaches with the client, a few assumptions/comments emerged:

1) Visiting 3-4 accounts in a day is reasonable and productive.

2) No less than 20% of the accounts should be left with TM's.

3) All accounts are, technically speaking, national accounts, but some are being served by street representatives.
4) We don't know where salespeople begin their days – some start from home, but we

don't know their home addresses, and should not try to factor this in, as a

reconfigured set of accounts may simply force rehiring of salespeople.

5) Of the sites with National Team presence, some of these are National Chains

(segment = "NCH"), which should be excluded (or, rather, treated as sites without

regular National Team coverage) when running the analysis.

6) There are potential obstacles associated with transferring customer sites owned by

different divisions.

The associated file contains the locations of the client's own customers, and which division,

team and salesperson covers them.

Data definitions for the file's fields are as follows:

ID – a unique number for each row of data.

Division – refers to the geographic division of the company that manages each customer site.

Customer Number – refers to each unique customer site.

Segment – a grouping of individual accounts into categories such as IND for industry or EDU

for education.

Business Type – this speaks to whether the business is, in theory, national or local. Everything

with an "NM" in here is theoretically national business; everything with an "LMC or "LMNC" is

theoretically local business. Note: this doesn't mean that these accounts are actually served by

national vs. local sales reps.

Covered By – designates which type of rep actually covers the account ("National Team" vs.

"Street Team", and a few "Unclear" that are still worth mapping if they are NM accounts).

Salesperson ID – a unique code for each salesperson in the beverage distribution company.

Latitude – the Y coordinate for the customer location visited by the sales representative (in an

EPSG:4326 spatial reference system) as derived from the teams Geocoder.

Longitude – the X coordinate for the customer location visited by the sales representative (in

an EPSG:4326 spatial reference system) as derived from the teams Geocoder

Location type – designates the accuracy of the location (based on a geocoding process).