Network Reinvention

Question 1

What factors have generated retail turbulence and market opportunity?

Answer 1

Diversification - e.g. supermarket banks
Consumer power
Deregulation
Competition
Globalisation
Disintermediation
New entrants - start-ups competing head to head with established players
New delivery channels/tech.

Question 2

What are the 3 main limitations to SIMs?

Answer 2

1. Consumption factors
2. Provision factors
3. Technology factors

Question 3

What consumption factors do SIMs ignore?

Answer 3

Demographic segmentation
Work-based trips
Leisure trips
Low value and convenience purchases
Elastic demand

Question 4

What provision factors fo SIMs ignore?

Answer 4

Product quality
Price
Brands
Customer loyalty
Scale economies
Footfall and micro-location

Question 5

What technology factors do SIMs ignore?

Answer 5

Internet competition e.g. Blockbuster vs. Netflix
Distribution channels e.g. e-commerce
Home delivery

Question 6

What are the alternatives to SIMs?

Answer 6

1. Analogue models
2. Regression models - in retail R2 can’t be
3. Network segmentation
4. Site rating models

Question 7

What is network segmentation?

Answer 7

Grouping of stores based on similar characteristics - inspired by geodemographics

Question 8

What characteristics can stores be grouped by in network segmentation?

Answer 8

Location
Competition
Demographic factors
Site factors

Question 9

What was Birkin et al.’s (2002) scorecard rating system?

Answer 9

Chose variables based on network segmentation analysis:
Urbanisation
Attractiveness
Retail centre quality
Demand

If a store achieved a score > average segment score then OVERACHIEVING
If a store achieved a score below average segment score then UNDERACHIEVING

Question 10

What is the equation for the predicted scorecard result?

Answer 10

Segment average volume x (Branch rating/Average segment rating)

Question 11

What are Site Rating Models?

Answer 11

Similar to network segmentation, but used in things other than food retail e.g. petrol stations

Scorecard model based on range of factors - location and facility components

e.g. ‘ATM Ratings model’ used: demographics, retail and business activity, workplace data etc. to derive a score for ATM locations - best score = best location

Question 12

What are Analogue models?

Answer 12

Attempts to forecast potential sales by drawing comparisons with other stores that are similar in physical, locational and trade-area circumstances

I.e. draws ‘analogies’ between an existing and the proposed store

Question 13

What is Regression modelling in retail analysis?

Answer 13

Defines a dependent variable e.g. store turnover, and attempts to correlate this with a set of explanatory variables e.g. store size

Question 14

What are the limitations of regression models in retail?

Answer 14

1. Evaluates stores in isolation - doesn’t consider impacts of competition or store’s existing network
2. Problem of ‘heterogeneity of sample stores’ - how easy is it to find stores sharing similar characteristics?
3. Assumes X variables are independent and uncorrelated - in reality floorspace and parking are likely to be correlated
4. Fails to handle spatial interactions - doesn’t model the process that generates flows of revenue between demand zones and stores

Question 15

When are Site Rating Models preferred to SIMs?

Answer 15

Non-food retail
E.g. petrol stations, ATMs, post offices etc. because they don’t work on the same principles of distance and attractiveness
Used in highly complex markets where SIMs are likely to break down

Question 16

What are the advantages to Site Rating Models over SIMs?

Answer 16

Simpler, more robust and cheaper
BUT
Less accurate and less transparent

Question 17

When are Analogue models used?

Answer 17

Most common - used in store location and store formatting

Store formatting: deciding which type of store is most suitable based on levels of competition, size of market etc. e.g. Tesco Express vs. Tesco Extra

Question 18

What are the limitations to Analogue models?

Answer 18

1. Success is very dependent on the analysts’ ability to choose a store that is similar enough to draw analogies
2. Performance of store from which analogies are being drawn may be inaccurate e.g. what if it is over or under-performing?
3. Difficult to evaluate greenfield sites using this method as catchment may be distorted by local transport networks and hard to import revenue predictions from other towns and cities

Question 19

When are Regression models used?

Answer 19

Single store analysis and to assess entire store networks

Question 20

What are the strengths of Regression models?

Answer 20

Simple
Robust
More sophisticated than basic analogue models

Question 21

Why is planning the location of ATMs difficult? Because of this, what is the best location method to use?

Answer 21

Complicated because they are frequently visited but irregularly used by a variety of customers at a variety of locations

Site Ratings Model