Urban Case Study
Problem situation:
A MNC retail player wants to enter into India for Grocery and Apparel Retailing. They are primarily looking at cities with a population in the range of 20 to 30 lakhs.
How can MIMI help?
MIMI data reveals that there are 13 cities with a population in the range of 20 to 30 lakhs.
How can three cities be selected out of these 13 cities?
District |
Urban MPI |
Urban Population |
MPI per Million Population |
Urban Amount Deposit |
Amount Deposit per Million (Lakh) |
Urban No. HH Television Population of |
Ernakulam |
222.02 |
2232564 |
99.45 |
2940133 |
1316931.12 |
481622 |
Coimbatore |
143.69 |
2633170 |
54.57 |
2091441 |
794267.37 |
641987 |
Lucknow |
139.91 |
3037718 |
46.06 |
3813865 |
1255503.31 |
435408 |
Kancheepuram |
137.80 |
2537825 |
54.30 |
822948 |
324272.95 |
589338 |
Nashik |
122.86 |
2598167 |
47.29 |
798287 |
307250.07 |
383471 |
Barddhaman |
118.98 |
3079584 |
38.63 |
1148906 |
373071.82 |
443774 |
Thiruvallur |
118.79 |
2433018 |
48.82 |
574865 |
236276.51 |
564393 |
Indore |
115.55 |
2424312 |
47.66 |
1630883 |
672719.93 |
387486 |
Haora |
112.47 |
3064668 |
36.70 |
709842 |
231621.17 |
409888 |
Kanpur Nagar |
107.09 |
3015129 |
35.52 |
1678579 |
556718.80 |
409542 |
Rajkot |
103.59 |
2208582 |
46.90 |
1022569 |
462997.98 |
386871 |
Patna |
98.14 |
2510093 |
39.10 |
2514901 |
1001915.47 |
312297 |
Hugli |
89.14 |
2131994 |
41.81 |
637520 |
299025.23 |
351693 |
Conclusion
- It can be seen from the table that based upon MPI, the MNC can select Ernakulam, Coimbatore, Lucknow, Kancheepuram and Nashik in the first phase.
- However, considering MPI per million, Ernakulam, Coimbatore, Kancheepuram, Athiruvallue and Indore are five cities where the MNC retailer can consider entry.
- As an indicator of purchasing power, if we take Amount Deposit per Million, then Ernakulam, Lucknow, Patna, Coimbatore and Indore are five cities with the highest economic prosperity.
- Finally, based on the above conclusions, the MNC should consider entry into Ernakulam, Coimbatore and Lucknow.
Rural Case Study
Problem situation:
A leading Bank would like to expand its rural branch network in the state of Bihar . How can they prioritise five districts with the help of MIMI?
In the first stage, we can take the districts with Rural MPI more than 100. This gives us a set of 12 districts from 39 districts to further analyse.
District |
Rural MPI |
Rural Population |
Value of Crop Production |
Rural No. of Bank Offices |
Rural No. of Accounts |
Rural Amount Deposit (INR Lakh) |
Rural Shop/Offices |
Pashchim Champaran |
120.37 |
3528781 |
73666724096 |
85 |
474177 |
63421 |
16462 |
Purba Champaran |
154.43 |
4683820 |
19456818289 |
97 |
573976 |
84168 |
20449 |
Rohtas |
106.88 |
2535085 |
17626811913 |
76 |
413108 |
62923 |
14931 |
Samastipur |
131.37 |
4107725 |
14588466385 |
94 |
509577 |
99518 |
33745 |
Muzaffarpur |
147.83 |
4308714 |
14056556718 |
112 |
750045 |
113468 |
28425 |
Siwan |
108.73 |
3135865 |
10367331103 |
102 |
812096 |
138971 |
20792 |
Madhubani |
144.47 |
4311466 |
10117675311 |
94 |
454135 |
72064 |
19780 |
Darbhanga |
114.04 |
3541846 |
9659453486 |
95 |
451142 |
79795 |
20712 |
Vaishali |
105.53 |
3262715 |
9440320260 |
79 |
586874 |
89135 |
24608 |
Gaya |
117.31 |
3803888 |
9021828814 |
115 |
661383 |
105509 |
17313 |
Saran |
114.82 |
3591053 |
8471279237 |
106 |
817117 |
132785 |
25224 |
Patna |
117.69 |
3262711 |
8073637914 |
113 |
641417 |
133036 |
12727 |
Conclusion
- Out of these 13 districts, if we consider Value of Crop Production as measure of wealth of the region then Paschim Champaran, Purab Champaran and Rohtas come on top.
- In these three districts, the present number of bank offices is less than compared to other districts like Gaya and Patna and therefore, these three districts need more banking services.