Sunday, December 16, 2007

Retail Analytics : Two Side Complexity

This is a continuation to my earlier post on Retail Analytics (Analytics in Retail, CPG and Distribution). I am trying to break the whole of Retail Operations to two parts and suggesting some analytics solutions.

i. Supply Chain Side:
This is the back-end operation. The typical decisions to be taken here are:
a. Location Decision : Where to locate various like the production units, warehouse, retail stores etc.
b. Production Decision : What to produce and how much to produce.
c. Inventory Decision : How much to store and in what phase, either raw or semi-finished or final product.
d. Transportation Decision : How to optimize the transportation cost while maintaining good logistics management.
e. Efficiency Optimization : This includes increasing overall efficiency of employees as well as processes involved.

Few of the Analyzes and Strategy Sciences Management works that I can remember, which will support these decisions are:
a. Network Design Methodology
b. Category Management
c. Inventory Management
d. Operations Research
e. Merchandise Performance Metrics
f. POP Indicator Analysis

I would prefer to call all these analyzes together as Supply Chain Analytics.

ii. Marketing Management Side
This is more operationally complex. To better this side understanding the customer behavior becomes critical. But this is not enough. There are various decisions to be taken as a Retail Chian store. Those decisions can be:
1. Target Customer
2. Brand Preference
3. Operational Efficiency Optimization
4. Cross-sell Focus Decisions
5. Advertisement Selection
6. Profit Maximization
7. Portfolio Maximization
Most of these topics are understandable from the terminology itself. So I don't get into much detail here.
I would rather move fast to suggest some analyzes and strategy consulting activities leveraging these decisions.
1. Brand Loyalty Metrics
2. Yield Management
3. Markdown Analysis
4. Customer Segmentation
5. Demand and Sales Forecasting
6. Competitor Analysis
7. Sensitivity Analysis (Price, Ads etc)
8. Migration Model (likelihood test to find people going to attrite or change behaviour significantly)
9 Market Basket Analysis
10. Marketing Mix Modeling
11. Advertisement and Campaign Management
12. Portfolio Maximization Analysis
13. POS Indicator Analysis

So many topics just thrown at you!!! Hope you enjoyed it. If not, let me know. I will try to address your concern in coming posts.

4 comments:

deepali said...

hi Bhupendra!! Im Deepali and right now working for an analytics company as a Business Analyst!! I found your papers vry important and i wanted to know if there is any certified course which would help me in taking forward my career in analytics.

U can contact me at this address deepali.nayak@gmail.com

CresceNet said...

Gostei muito desse post e seu blog é muito interessante, vou passar por aqui sempre =) Depois dá uma passada lá no meu site, que é sobre o CresceNet, espero que goste. O endereço dele é http://www.provedorcrescenet.com . Um abraço.

Raghav said...

Hi ,
I am Raghav , working as Data Analyst in Software firm. i want to shift from Data analyst(Mainly into ETL Loads , Reporting ) to Business Analyst. i want to c myself as Market Analyst (MR Profile). Could you please share advice me how to proceed from my current profile. As of now, i am planning to get trained in SAS tool. Will this be in the right direction for my goal.

U can contact me @ raghavendrak2@gmail.com

Gitz said...
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