THE RELEVANCE OF MATHEMATICS IN

TELECOMMUNICATION INDUSTRY

CONTENT

• INTRODUCTION

• USES OF MATHEMATICS IN COMMERCIAL SALES

– SALES FORECAST

– RESEARCH AND PERFORMANCE ANALYSIS

– DISTRIBUTION PARTNER INCENTIVE STRUTURE

– FLAGSHIP COLLECTIONS/ SALES REPORTING

• JOB ROLES THAT REQUIRES MATHEMATICS

INTRODUCTION

• Students majoring in mathematics might wonder

whether they will ever use the mathematics they

are learning, once they graduate and get a job. Is

any of the analysis, calculus, algebra, numerical

methods, math programming, etc. really going to

be of value in the real world except teaching? The

answer is yes.

What are my opportunities in labor market?

Where do I apply

various mathematics

theorems

Of what relevance are the algebras

How can I apply

Mathematical Analysis in real

life situation

Is my career path restricted to teaching as

a mathematician

Where can I fit in after graduation What are

career opportunities

AREAS APPLIED

USES OF MATHEMATICS IN COMMERCIAL SALES

Prediction of total weekly, Monthly and yearly reports from the beginning of the period, using available Parameters to calculate possible figure At the end of the period under review

Analyze sales performance, compare previous month/year performance, current month/year, find out causes spike in sales or dip and advice the business on measures to sustain performance or strategies to improve

Structure incentive payment for Distribution partners wrt territory subscriber base, target achievement and base stations in assigned territory for a mutual business benefit for the organization and distribution partners

Collection of sales proceeds from flagship shops: viz: cash, postpaid payment, POS and do proper. This is done via designing a template with excel

Example

Tailored regional offerings can be devised based on the ‘Ground Realities’

SALES FORECAST PERFORMANCE ANALYSIS

BUSINESS INTELLIGENCEFLAGSHIP COLLECTIONS/ SALES REPORTINGDISTRIBUTION PARTNER INCENTIVE STRUTURE

SALES FORECAST

• Prediction of futures sales using available parameters, viz: Network quality, sales trend, number of subscribers, visibility and recharges done in a particular territory.

SALES FORECAST FOR THE MONTH OF JUNE

DP MAY PERFORMANCE JUNE TARGET JUNE FORECAST JUNE ACTUAL

Lyttle Oak

9,200,000.00

23,031,000

15,000,000 13,635,000

Multinet Systems Nig. Ltd.

41,520,000.00

42,739,811

45,000,000

94,699,000

Glaceo Investment Ltd.

22,225,000.00

35,502,858

25,000,000 24,100,000

Multitek Data Services Ltd.

29,990,000.00

41,938,708

35,000,000

51,316,000

Tee & T Concepts Nig. Ltd.

21,320,000.00

31,591,922

25,000,000

32,990,000

Terry Okwute Nig. Ltd.

12,996,000.00

21,121,114

15,000,000 12,765,000

Deblesskins Investments Ltd.

33,135,000.00

21,121,114

35,000,000

50,685,000

Remglory Ventures Ltd.

27,435,000.00

33,436,458

30,000,000 27,160,000

Idems Ultimate Ventures

8,330,000.00

21,121,114

10,000,000

10,675,000

Initial Logistics Ltd.

2,140,000.00

22,096,889

5,000,000 12,935,000

Dadev Ventures

22,970,000.00

29,430,944

35,000,000 70,525,000

Jons Ndy Ltd.

22,130,000.00

21,121,114

25,000,000 31,355,000

Gabros Divine Technologies Ltd.

63,930,000.00

55,301,267

70,000,000

60,935,000

TOTAL 317,321,000.00 399,554,313 370,000,000 493,775,000

GRAPHICAL REPRESENTATION

Lyttle

Oak

Multinet Sy

stems N

ig. Lt

d.

Glaceo

Inve

stmen

t Ltd.

Multitek Data

Servi

ces Lt

d.

Tee &

T Concep

ts Nig.

Ltd.

Terry

Okw

ute Nig.

Ltd.

Debles

skins In

vestm

ents

Ltd.

Remglo

ry Ven

tures Lt

d.

Idems U

ltimate Ven

tures

Initial Lo

gistics

Ltd.

Dadev

Ventures

Jons Ndy L

td.

Gabro

s Divi

ne Tech

nologies L

td. -

10,000,000.00

20,000,000.00

30,000,000.00

40,000,000.00

50,000,000.00

60,000,000.00

70,000,000.00

80,000,000.00

90,000,000.00

100,000,000.00

MAY PERFORMANCEJUNE TARGETJUNE FORECASTJUNE ACTUAL

SALES PERFORMANCE ANALYSIS

Provision of objective feedback to salesmen trying to get a positive

change in performance. Essentially it is about telling the sales/marketing

men what actually happened as opposed to what they perceived to be

happening. It also entails giving recommendations no what should be

done in future to achieve better result.

Year to Date Sales Summary

4% increase

S/N Description

Jan Feb Mar April May June July AUG SEPT Oct Nov DecYTD

Revenue Target

YTD Revenue Actual

% increase against previous month

1SIMs [QTY ‘000]

191,701

176,298

137,200

178,593

165,000

148,500

107,300

218,500 173,898

226,087

196,448

242.8

18,922.5 20,166.0

24

2Data SIM(QTY) 0 1,200 0 1,400 100 0 360 50 100 0 0 0 0

3Blank SIM(QTY) 2,250 3,200 1,950 2,200 3,950 350 4,300 4,500 4,100 3,350 1,200 28,800 2300

4Modem (QTY) 332 0 1,759 455 657 390 495 255 780 510 330 120 -64

5Phones [QTY’000] 1,119 176 0 0 130 0 830 74 1,548 1,485 442 1,137 157

6SIMs Revenue [Nm]

18.3 16.8 13.3 17.8 16.4 14.8 14.8 21.8 17.4 22.6 19.6 24.3 24

7

Airtime Sales Revenue [Nm]

1,483.8 1,361.3 1,592.6

1,795.8

1,661.4

1,608.3

1,534.0 1,730.6

1,740.2 1,637.4

1,709.30 2,016.4 18

8

Devices Sales Revenue [Nm]

5.1 0.6 6.1 1.6 2.7 1.36 4.6 1.0 4.7 6.3 1.3 1.9 46

9 E-top up 15.6 15.5 20.0 23.9 17.4 21.6 21.8 7.8 18.0 13.5 16.2 21.9 35

Total Sales Revenue [Nm]

1,506.2

1,379.3

1,617.0

1,814.9

1,680.0

1,626.7

1,555.7

1,761.8 1,789.4

1,663.3

1,728.9

2,044.3

18

SALES Dashboard

there was a 18% increase in revenue in Dec over Nov ‘13

South South Performance trend

Jan

Feb

MarApr

ilMay

June

Ju

ly

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0.00

500.00

1,000.00

1,500.00

2,000.00

2,500.00

TargetActual

BUSINESS INTELLIGENT

• Working in the Business Intelligence team is a premier opportunity to develop a career in business and big data analytics

• Business Intelligence Analysts are strong in quantitative analysis, enjoy coding but also want to balance that with their interest in business. They think critically to tackle complex challenges

Relevance of Mathematics in BI

• Consulting with internal customers (e.g., Marketing, Logistics, Customer Service) to develop analyses that lead to actionable insights that accelerate profitable growth

• Wrangling data from multiple sources including sales, inventory, product, and customer databases to create integrated views that can be used to drive decision making

• Working with several large and complex SQL databases• Designing and building reports and analyses in Excel

DISTRIBUTION PARTNER INCENTIVE DISTRIBUTION PARTNER INCENTIVE This is what motivates/encourages distribution partners to go extra mile in the business

its mathematically structured so as to reward each DPs according to their performance, putting into consideration their territory coverage, network quality, subscriber base, sales volume and target achievement.

Example of Incentive structure

Total Territory Recharge

200,000,000

Objectives Target Achievement

Unit score Weights Score

Activation in territory 92% 4 35 140

Recharges in Territory 74% 2 35 70

E-Top up contr. To Airtime Sales

88% 3 15 45

Total Sales 101% 5 15 75

Final Score in (%) 330

Territory Recharge Share (0.75%) 1,500,000

Territory recharge Incentive for DP 990,000

% Target achieved Unit Score

<60% 0

60% - <70% 1

70% - <80% 2

80% - <90% 3

90% - <100% 4

≥100% 5

66.0% Final score divided by 500 multiplied by 100%

JOB ROLES THAT REQUIRES MATHEMATICS

• Sales Analysis• Business Intelligent Unit• Incentive And Performance Management• Finance• Commercial Planning Unit• RF And Optimization Engineering• FLAGSHIP COLLECTION/RECONCILIATION

QUESTIONS