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Excel Dashboard for Analysis and Prediction

Date post: 05-Dec-2014
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Being on the same page and you understand how we intend to understand all the drivers of supermarket A's demand using competitors pattern of growth in demand per district and for lifestyle and special products, increase in delivery rate and pattern of supermarket A's customer growth or evolution of its turnover
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Jul-13 TOTAL DEMAND LIFESTYLE DEMAND SPECIAL DEMAND TURNOVER SUPERMARKET A 30.1 7.5 127.8 5.0 SUPERMARKET-C 69.7 27.3 86.6 5.0 Jul-13 TOTAL DEMAND LIFESTYLE DEMAND SPECIAL DEMAND TURNOVER SUPERMARKET A 30.1 7.5 127.8 5.0 SUPERMARKET- B 10.1 -17.2 42.6 5.0 In the above table the change in demand and turn over can be found out for July 2013. But tables below show the change in Dec 2013 Dec-13 SUPERMARKET A 18.1 3.9 107.3 11.6 SUPERMARKET- C 43.6 52.2 41.2 11.6 Dec-13 SUPERMARKET A 18.1 3.9 107.3 11.6 SUPERMARKET- B -0.5 27.2 -19.6 11.6
Transcript
Page 1: Excel Dashboard for Analysis and Prediction

Jul-13   TOTAL DEMAND LIFESTYLE DEMAND SPECIAL DEMAND TURNOVER

SUPERMARKET A   30.1 7.5 127.8 5.0

SUPERMARKET-C   69.7 27.3 86.6 5.0

Jul-13   TOTAL DEMAND LIFESTYLE DEMAND SPECIAL DEMAND TURNOVER

SUPERMARKET A   30.1 7.5 127.8 5.0

SUPERMARKET-B   10.1 -17.2 42.6 5.0

In the above table the change in demand and turn over can be found out for July 2013. But tables below show the change in Dec 2013

Dec-13          

SUPERMARKET A   18.1 3.9 107.3 11.6

SUPERMARKET-C   43.6 52.2 41.2 11.6

Dec-13          

SUPERMARKET A   18.1 3.9 107.3 11.6

SUPERMARKET-B   -0.5 27.2 -19.6 11.6

Page 2: Excel Dashboard for Analysis and Prediction

The change in provinces and districts are unique from overall change in supermarkets. Table below shows the change is negative and positive in different input.

Jul-13   TOTAL DEMAND LIFESTYLE DEMAND SPECIAL DEMAND TURNOVER

SUPERMARKET A   30.1 7.5 127.8 5.0

SUPERMARKET-B   10.1 -17.2 42.6 5.0

SUPERMARKET-A_ BORNO -43.3 0.9 -100.0 -99.9

SUPERMARKET-B_ CROSS RIVER -12.5 -29.1 55.0 -3.7

SUPERMARKET-C_ Far East 0.5 54.0 0.0 -1.1

Dec-13          

SUPERMARKET A   18.1 3.9 107.3 11.6

SUPERMARKET-B   -0.5 27.2 -19.6 11.6

SUPERMARKET-A_ BAUCHI 1.4 -10.0 189.9 22.5

SUPERMARKET-B_ BAYELSA -22.3 -34.9 13.0 8.8

SUPERMARKET-C_ BORNO 0.4 39.9 0.0 -99.9

-100.0

0.0

100.0

200.0

300.0

400.0

TOTAL DEMAND LIFESTYLE DEMAND SPECIAL DEMAND TURNOVER -100.0

0.0

100.0

200.0

300.0

400.0

500.0

Total Demand Life Style DemandSpecial Demand Turnover

Page 3: Excel Dashboard for Analysis and Prediction

-100.0

0.0

100.0

200.0

300.0

400.0

500.0

Total Demand Life Style DemandSpecial Demand Turnover

-100.0

0.0

100.0

200.0

300.0

400.0

TOTAL DEMAND LIFESTYLE DEMAND SPECIAL DEMAND TURNOVER

So patterns are unique for different provinces , districts and time

Jul 2013 Dec 2013

Page 4: Excel Dashboard for Analysis and Prediction

Delivery  Rate   10.61525558

SUPERMARKET A SUPERMARKET B SUPERMARKET C

SPECIAL DEMAND 37.66 -19.57 41.24

Far East

Delivary Rate 9.60    

Delivary Rate Index -0.98    

LIFESTYLE DEMAND 18640.86 71.61 34.63

SPECIAL DEMAND 61.77 -100.00 3479.23

TOTAL DEMAND 25.81 -83.93 34.63

TURNOVER 9.60 9.60 9.60

FINANCIAL TURNOVER -12.89 582.05 -18.59

SUPERMARKET A SUPERMARKET B SUPERMARKET C-200.00

800.00

1800.00

2800.00

3800.00

4800.00

LIFESTYLE DEMAND LIFESTYLE DEMAND SPECIAL DEMAND TOTAL DEMAND TURNOVER FINANCIAL TURNOVER

Page 5: Excel Dashboard for Analysis and Prediction

Delivery  Rate   10.61525558

SUPERMARKET A SUPERMARKET B SUPERMARKET C

TOTAL DEMAND 18.10 -0.47 43.58

Far North

Delivary Rate 11.16    

Delivary Rate Index 3.10    

LIFESTYLE DEMAND 42224.73 69.19 81.83

SPECIAL DEMAND -7.58 37.62 7314.30

TOTAL DEMAND 1.37 53.76 66.94

TURNOVER 11.16 11.16 11.16

FINANCIAL TURNOVER 9.66 -27.71 -33.41

SUPERMARKET A SUPERMARKET B SUPERMARKET C-200.00

800.00

1800.00

2800.00

3800.00

4800.00

LIFESTYLE DEMAND LIFESTYLE DEMAND SPECIAL DEMAND TOTAL DEMAND TURNOVER FINANCIAL TURNOVER

Page 6: Excel Dashboard for Analysis and Prediction

Slide 4 and 5 show that 10% change in delivery rate from mid year July 2013 has affected demand for different categories. This change has also affected both B and C , shown below

SUPERMARKET A SUPERMARKET B SUPERMARKET C

SPECIAL DEMAND 37.66 -19.57 41.24

SUPERMARKET A SUPERMARKET B SUPERMARKET C

LIFESTYLE DEMAND 3.87 27.15 52.20

Page 7: Excel Dashboard for Analysis and Prediction

Far East

Delivary Rate 9.60    

Delivary Rate Index -0.98    

LIFESTYLE DEMAND 18640.86 71.61 34.63

SPECIAL DEMAND 61.77 -100.00 3479.23

TOTAL DEMAND 25.81 -83.93 34.63

TURNOVER 9.60 9.60 9.60

FINANCIAL TURNOVER -12.89 582.05 -18.59

Far North

Delivary Rate 11.16    

Delivary Rate Index 3.10    

LIFESTYLE DEMAND 42224.73 69.19 81.83

SPECIAL DEMAND -7.58 37.62 7314.30

TOTAL DEMAND 1.37 53.76 66.94

TURNOVER 11.16 11.16 11.16

FINANCIAL TURNOVER 9.66 -27.71 -33.41

For few provinces/ districts change is unique due to negative rather than positive impact or vice versa.

Page 8: Excel Dashboard for Analysis and Prediction

CROSS RIVER Delivery Rate Customer Base

Jul-13 -6.30 0.42

Dec-13 4.51 -1.95

Supermarket A

Jul-13 -9.59 15.37

Dec-13 10.75 2.21

KWARA Delivery Rate Customer Base

Jul-13 -16.61 9.13

Dec-13 15.97 4.20

Supermarket A

Jul-13 -9.59 15.37

Dec-13 10.75 2.21

KWARA

Jul-13

Dec-13

Supermarket A

Jul-13

Dec-13

-10

-5

0

5

10

15

20

There is significant change and above tables show that the delivery rare and customer base has in probably inverse relationship for Supermarket and different province/ districts.

Page 9: Excel Dashboard for Analysis and Prediction

Delivery rate can predict the future demand roughly the accuracy may be questionable as other significant factors are in action.

Rate Demand

45 14447.205

Rate Demand

40 13961.96

Rate Demand

30 12991.47

Lifestyle demand has higher growth rate than special demand. These are also different amount three supermarkets. Supermarket A and C has similarity in change ( like increase or decrease but not in amplitude of change). Supermarket is different as it shows negative change in demand from mid year to end.

KWARA, Riverine, ZAMFARA, Core West, KOGI, GOMBE, CROSS RIVER, NASARAWA, ONDO, BORNO, Districts, Core East, Far East, EKITI, ADAMAWA,OSUN, AKWA IBOM, DELTA, ABIA, IMO, KEBBI, YOBE and BENUE provinces or districts have lower or negative growth for Supermarket A. These areas have lower comparative growth than average rate in lifestyle demand. Lifestyle demand has higher rate than special demand so this was considered in comparison. Few areas have similarity for their very high growth like NIGER, SOKOTO, ANAMBRA, TARABA, FCT, KADUNA and ENUGU in lifestyle segment.

Page 10: Excel Dashboard for Analysis and Prediction

Brief of the dashboard

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Brief of the dashboard

Page 12: Excel Dashboard for Analysis and Prediction

Brief of the dashboard

Page 13: Excel Dashboard for Analysis and Prediction

Brief of the dashboard

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Brief of the dashboard

Page 15: Excel Dashboard for Analysis and Prediction

Brief of the dashboard


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