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The Best Of
3 Worlds!

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A Marketer's Life

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Our Mission

Architect a Customer Value Management Solution that delivers

Measurable Business Impact

through Actionable Analytics

 

 

 

 

 

 

 

 

 

 

 

 

Every individual has different needs…

 

 

Power of ‘i

 

 

There’s something for everyone!

 

 

 

 

 

 

 

 

 

 

 

Solutions

Pivot
• Comprehensive reporting dashboard, over 1200+ reports
• Standardized Business Monitor
• Descriptive Models
• Flexible periodicity
• Sharp Insights & Business Intelligence

« Click here to go back to the framework

Prevision
• Platform agnostic prediction models
• Actionable scorecards
• Structured Knowledge transfer process
• Machine Learning

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Pixel
• Segment Builder – Behavioural & Geographical
• Robust 'Next Best Action' (NBA) Framework
• User friendly campaign creator
• Campaign recommendations by Domain experts
• Compatible with leading campaign engines

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Pinnacle
• Easy integration with source systems, BI & Analytics
• Supports static & contextual campaigns
• Effective campaign measurement
• Commercial model linked to upsides

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Case Studies

 

Our experience and depth of knowledge – having worked with some of the world’s leading organisations allow us to not only suggest solutions for some of the toughest situations but also to pre-empt some of them. We present to you some of the case studies / use cases that might be useful to you.

High Value Displacement

Problem Statement: Revenue growth not in line with subscriber growth.

Pivot Output

  • Revenue grows slower than subscriber growth – Indicates ARPU drop. Existing base or Activations?
  • ‘Waterfall analysis’ Activations stable at 6% of base; Activation ARPU = Base ARPU. Existing base reason for ARPU drop. Diplacement or Churn?
  • ‘Revenue Tree’ shows a Displacement to Replacement ratio at 6:1; Displacement a concern – loss at ~15% of base Revenue. Which segment?
  • ‘Revenue displacement monitor’ shows HV highest contribution at 55%. Which leg?
  • ‘Leg wise displacement contribution’ reveals IDD as maximum contributor. Other significant variables?
  • Tenure, Usage days, Pack Penetration common variables across displacers. Descriptive analytics rendered opaque.

 

Prevision Output

  • 6 displacement Models for each usage leg: Local On Net; Local Off Net; Total Local; SMS; ISD & Data
  • Model identifies subscribers for displacement on usage types 15 days in advance for next 30 Days for each of the usage legs
  • Model further prioritized leg with highest propensity to Displace to aid ‘Next best Action’

 

Pi Recommendations

  • Pro-active approach using ‘Predictive modeling’: Segmented propositions on Leg for Next best action
  • Reactive approach: ‘Leg-wise inactivity floor triggers’ – Second level offers for subscribers post displacement

 

Results

  • Contacting 10% of modelled base reached 51% of displacers
  • 20% displacement savings
  • Revenue defended: ~1.76% of Base Revenue

Close
Revenue growth not in line with subscriber growth. See how Pi solved this problem for a leading mobile operator.

High Value Displacement

Problem Statement: Revenue growth not in line with subscriber growth.

 

Pivot Output

  • Revenue grows slower than subscriber growth – Indicates ARPU drop. Existing base or Activations?
  • ‘Waterfall analysis’ Activations stable at 6% of base; Activation ARPU = Base ARPU. Existing base reason for ARPU drop. Diplacement or Churn?
  • ‘Revenue Tree’ shows a Displacement to Replacement ratio at 6:1; Displacement a concern – loss at ~15% of base Revenue. Which segment?
  • ‘Revenue displacement monitor’ shows HV highest contribution at 55%. Which leg?
  • ‘Leg wise displacement contribution’ reveals IDD as maximum contributor. Other significant variables?
  • Tenure, Usage days, Pack Penetration common variables across displacers. Descriptive analytics rendered opaque.

 

Prevision Output

  • 6 displacement Models for each usage leg: Local On Net; Local Off Net; Total Local; SMS; ISD & Data
  • Model identifies subscribers for displacement on usage types 15 days in advance for next 30 Days for each of the usage legs
  • Model further prioritized leg with highest propensity to Displace to aid ‘Next best Action’

 

Pi Recommendations

  • Pro-active approach using ‘Predictive modeling’: Segmented propositions on Leg for Next best action
  • Reactive approach: ‘Leg-wise inactivity floor triggers’ – Second level offers for subscribers post displacement

 

Results

  • Contacting 10% of modelled base reached 51% of displacers
  • 20% displacement savings
  • Revenue defended: ~1.76% of Base Revenue

Close

Market Opportunity Framework

Business Intent: Reduce Gap with Leader

Pivot Output

Industry overview: High market potential with industry SIM penetration at ~70%

  • ‘Region-wise Base Sniper’ identifies:
    • Base gap with leader at 27% and is a distant #2
    • Gross share lower than Base share
    • Market leader continues to have 23% higher Gross share
    • Telco has only a 9 ppt differential on quality
    • New operator aggressive Gross game – Pushing to #2 in 3 High ARPU regions
    • Need to understand Base & Gross share together?
  • ‘Market Opportunity Grid’ identifies 7 regions for Gross adds Acceleration. Current utilization pattern?
  • ‘Utilization pattern analyzer’ excludes 2 regions with more than 80% utilization. Behaviour of existing subscribers in 5 regions?
  • ‘Internal Sniper Analysis’ shows a need for different interventions in different regions

 

Pi Recommendations

Move away from “Straight Jacket” to “Geo-based initiatives”.

  • Geo based Acquisition offers: Location based tariffs in 45% of cell sites across 5 identified regions
  • Targeted MNP offers using with differential tariffs and commissions based on ‘Customer Potential Value Index’ & ‘MNP Opportunity Grid’

 

Results

  • 10% increase in Gross share/month
  • Gap with leader reduced by 1% in a Qtr
  • Incremental Revenue at 3.4% of Telco Base revenue

 

Close
The business intent of this issue was to reduce the gap with leader. Click here to know more.

Market Opportunity Framework

Business Intent: Reduce Gap with Leader

Pivot Output

Industry overview: High market potential with industry SIM penetration at ~70%

  • ‘Region-wise Base Sniper’ identifies:
    • Base gap with leader at 27% and is a distant #2
    • Gross share lower than Base share
    • Market leader continues to have 23% higher Gross share
    • Telco has only a 9 ppt differential on quality
    • New operator aggressive Gross game – Pushing to #2 in 3 High ARPU regions
    • Need to understand Base & Gross share together?
  • ‘Market Opportunity Grid’ identifies 7 regions for Gross adds Acceleration. Current utilization pattern?
  • ‘Utilization pattern analyzer’ excludes 2 regions with more than 80% utilization. Behaviour of existing subscribers in 5 regions?
  • ‘Internal Sniper Analysis’ shows a need for different interventions in different regions

 

Pi Recommendations

Move away from “Straight Jacket” to “Geo-based initiatives”.

  • Geo based Acquisition offers: Location based tariffs in 45% of cell sites across 5 identified regions
  • Targeted MNP offers using with differential tariffs and commissions based on ‘Customer Potential Value Index’ & ‘MNP Opportunity Grid’

 

Results

  • 10% increase in Gross share/month
  • Gap with leader reduced by 1% in a Qtr
  • Incremental Revenue at 3.4% of Telco Base revenue

 

Close

High Value Acquisition Churn

Business Intent: Incremental revenue from existing gross adds

Pivot Output

  • ‘Inflow & Outflow Analysis’ shows overall base drops. Existing base or Activations?
  • Net IZU (IZU – ZU Winback) constant at ~11%; Drop in activations putting pressure on base growth. Revenue impact?
  • Revenue drops by 12% higher than subs drop. Existing base or Activations?
  • ‘Revenue Tree’ shows that revenue contribution of new activations to total revenue drops continuously. Drop primarily due to widening gap between revenue gain from Activations and revenue drop from existing base. MARPU or Quality?
  • ‘Waterfall analysis’ shows MARPU drops by 2%; T2M and T3M Quality on a declining trend – Retention from new activations a concern. Segment share of activations?

 

arpugraph

  • ‘Activation Revenue dependency’ shows 10% of subscribers account for 40% of Revenue – High skew from HV subscribers. Retention by segment?
  • HVA and UHVA churn at ~26%; HVA churn accounts for ~7% of total Acquisition churn and 55% of Acquisition Revenue loss – HV Acquisition churn a concern. Other significant variables?
  • Tenure, Usage days, Pack Penetration common variables across high value activations. Descriptive analytics rendered opaque.

 

Prevision Output

  • To statistically predict acquisitions which would become high value(HVA) /Ultra high value(UHVA) in the next 3 months based on first 3, 7 or 15 days of their behaviour
  • Amongst the 3, 7 and 15 days – 15 day High value Model delivers best results

 

Results

  • 15 day High value lift – Top 10 percentile indentified 54% of High Value
  • High value T3M Activation churn reduces by 5 ppt to 21%
  • Revenue defended: ~1.5% of Base Revenue

Close
Incremental revenue from existing gross adds was the intent behind this case study.

High Value Acquisition Churn

Business Intent: Incremental revenue from existing gross adds

Pivot Output

  • ‘Inflow & Outflow Analysis’ shows overall base drops. Existing base or Activations?
  • Net IZU (IZU – ZU Winback) constant at ~11%; Drop in activations putting pressure on base growth. Revenue impact?
  • Revenue drops by 12% higher than subs drop. Existing base or Activations?
  • ‘Revenue Tree’ shows that revenue contribution of new activations to total revenue drops continuously. Drop primarily due to widening gap between revenue gain from Activations and revenue drop from existing base. MARPU or Quality?
  • ‘Waterfall analysis’ shows MARPU drops by 2%; T2M and T3M Quality on a declining trend – Retention from new activations a concern. Segment share of activations?

 

arpugraph

  • ‘Activation Revenue dependency’ shows 10% of subscribers account for 40% of Revenue – High skew from HV subscribers. Retention by segment?
  • HVA and UHVA churn at ~26%; HVA churn accounts for ~7% of total Acquisition churn and 55% of Acquisition Revenue loss – HV Acquisition churn a concern. Other significant variables?
  • Tenure, Usage days, Pack Penetration common variables across high value activations. Descriptive analytics rendered opaque.

 

Prevision Output

  • To statistically predict acquisitions which would become high value(HVA) /Ultra high value(UHVA) in the next 3 months based on first 3, 7 or 15 days of their behaviour
  • Amongst the 3, 7 and 15 days – 15 day High value Model delivers best results

 

Results

  • 15 day High value lift – Top 10 percentile indentified 54% of High Value
  • High value T3M Activation churn reduces by 5 ppt to 21%
  • Revenue defended: ~1.5% of Base Revenue

 

Close

Balance Build-up

Problem Statement: Increase share of wallet through balance build up.

Pivot Output

  • ‘Daily Balance Analysis’ shows Daily balance low (10% of ARPU) and dropping. ARPU/Usage day dropping or Days of Stock balance declining?
  • ‘Balance to consumption analysis’ shows B/C ratio stable at 80% and ARPU/usage day flat. Stock balance declining trends low and declining(<2 days).Balance behavior by slabs?
  • ‘Daily Balance slab contribution’ shows high skew in the ‘Very Low balance slabs’ with 66% of subs having <1.5 USD balance. Other KPI trends?
  • ‘Daily Balance slab deep dive’ reveals low balance concern across HV subs, High tenure & high usage days subs. Impact of Recharge Portfolio?
  • Recharge KPIs indicates high recharge turns and very low value of recharge. Indicating no incentive to upgrade value of recharge. Denomination wise trends?
  • ‘Recharge denomination deep dive’ indicates 80% recharges & 55% recharge value come from the lowest recharge denomination. Pattern in HV segments?
  • ‘Revenue segment wise recharge analysis’ further shows that HV subs exhibit patterns in line with base – Very high turns & Low recharge value – each transaction a for churn. Need to revisit recharge portfolio.

 

Pi Recommendations

Moving from a linear to a ‘MM4M’ recharge portfolio.

  • Restructure existing market portfolio
  • Incentivize HV recharges
  • Segmented Talk time offers using “Full talk time Model’

 

Results

  • Using Full talk time Model, each subscriber was give 2 segmented recharge offers:
  • With Validity
  • Without Validity
  • 11% incremental adoptions – results in increased balance build up
  • 0.33 Mn USD incremental revenue

Close
Pi strategised for a market leader to increase share of wallet through the balance build-up route.

Balance Build-up

Problem Statement: Increase share of wallet through balance build up.

Pivot Output

  • ‘Daily Balance Analysis’ shows Daily balance low (10% of ARPU) and dropping. ARPU/Usage day dropping or Days of Stock balance declining?
  • ‘Balance to consumption analysis’ shows B/C ratio stable at 80% and ARPU/usage day flat. Stock balance declining trends low and declining(<2 days).Balance behavior by slabs?
  • ‘Daily Balance slab contribution’ shows high skew in the ‘Very Low balance slabs’ with 66% of subs having <1.5 USD balance. Other KPI trends?
  • ‘Daily Balance slab deep dive’ reveals low balance concern across HV subs, High tenure & high usage days subs. Impact of Recharge Portfolio?
  • Recharge KPIs indicates high recharge turns and very low value of recharge. Indicating no incentive to upgrade value of recharge. Denomination wise trends?
  • ‘Recharge denomination deep dive’ indicates 80% recharges & 55% recharge value come from the lowest recharge denomination. Pattern in HV segments?
  • ‘Revenue segment wise recharge analysis’ further shows that HV subs exhibit patterns in line with base – Very high turns & Low recharge value – each transaction a for churn. Need to revisit recharge portfolio.

 

Pi Recommendations

Moving from a linear to a ‘MM4M’ recharge portfolio.

  • Restructure existing market portfolio
  • Incentivize HV recharges
  • Segmented Talk time offers using “Full talk time Model’

 

Results

    • Using Full talk time Model, each subscriber was give 2 segmented recharge offers:
    • With Validity
    • Without Validity
    • 11% incremental adoptions – results in increased balance build up 0.33 Mn USD incremental revenue

 

Close

IDD Opportunity

Problem Statement: Identify potential latent IDD needs to maximize revenue, in an IDD intensive market.

Pivot Output

  • IDD Y-o-Y performance show usage grow by 57%& revenue by 13%.Country wise Usage/Revenue distribution?
  • ‘Top 5 Countries contribution analysis’ reveals India & Nepal as the largest contributors. Further drill down shows that Nepal accounts for majority of revenue drop. Other KPIs?
  • ‘Nepal KPI trends’ shows dropping usage and Usage days. While penetration has dropped absolute users has remaining stagnant over a year. Validate displacement/Replacement using Revenue tree.
  • ‘Revenue Tree’ shows a Displacement to Replacement ratio at 2.6:1; 80% of Displacement loss coming from High value segments. HV Displacement the biggest concern. Pack or Not in pack?
  • Usage KPIs decline for Nepal users in both packs & non packs. Displacement from pack subs accounts for majority of displacement. Pack Inflow/ Outflow?
  • Pack inflow/outflow analysis’ reveals lapsing from IDD pack higher than average lapser – 19% vs. 11%. Forfeiture validated?
  • ‘Forfeiture Distribution & Health monitor’ shows latent need for higher version of pack indicated by Negative forfeiture. Any other behaviour patterns?
  • ‘Multi country calling profiling’ reveals Nepal users have significant calling to India & Arab countries. Need for a Multi country pack for Nepal users.

 

Pi Recommendations

Moving away from Mass production to Mass Customization for target segments.

  • HV Nepal displacers offered ‘Segmented Combo pack’. Combo pack covered Nepal, India and Arab countries.

 

Results

  • 20%displacement retained & 3% reduction in lapsing
  • Revenue defended: ~ 1.76% of Base Revenue

Close
Pi helped a market leader identify the IDD opportunity in an IDD intensive market.

IDD Opportunity

Problem Statement: Identify potential latent IDD needs to maximize revenue, in an IDD intensive market.

Pivot Output

  • IDD Y-o-Y performance show usage grow by 57%& revenue by 13%.Country wise Usage/Revenue distribution?
  • ‘Top 5 Countries contribution analysis’ reveals India & Nepal as the largest contributors. Further drill down shows that Nepal accounts for majority of revenue drop. Other KPIs?
  • ‘Nepal KPI trends’ shows dropping usage and Usage days. While penetration has dropped absolute users has remaining stagnant over a year. Validate displacement/Replacement using Revenue tree.
  • ‘Revenue Tree’ shows a Displacement to Replacement ratio at 2.6:1; 80% of Displacement loss coming from High value segments. HV Displacement the biggest concern. Pack or Not in pack?
  • Usage KPIs decline for Nepal users in both packs & non packs. Displacement from pack subs accounts for majority of displacement. Pack Inflow/ Outflow?
  • Pack inflow/outflow analysis’ reveals lapsing from IDD pack higher than average lapser – 19% vs. 11%. Forfeiture validated?
  • ‘Forfeiture Distribution & Health monitor’ shows latent need for higher version of pack indicated by Negative forfeiture. Any other behaviour patterns?
  • ‘Multi country calling profiling’ reveals Nepal users have significant calling to India & Arab countries. Need for a Multi country pack for Nepal users.

 

Pi Recommendations

Moving away from Mass production to Mass Customization for target segments.

  • HV Nepal displacers offered ‘Segmented Combo pack’. Combo pack covered Nepal, India and Arab countries.

 

Results

  • 20%displacement retained & 3% reduction in lapsing
  • Revenue defended: ~1.76%of Base Revenue

Close

MNP Opportunity

 mnp01
  • Declining Base share, Gross share with Gross share(17%) < Base share(22%)
  • Widening gross share gap with leader
  • Acquisition – key to bridge gap with leader
arrdWhat is the acquisition mix
 mnp02
  • Dropping activations
  • MNP contribution to activations at 3%
arrdMNP Acquisitions or Non MNP Acquisitions?
 mnp03
  • ARPU & Quality of MNP acquisitions significantly higher
  • Revenue from 1 MNP sub = ~3 Non MNP sub
arrdPort in subs by revenue segment?
 mnp04
  • ~5% of MNP activations are HV subs bringing in 40% of revenueNeed to target HV port ins
arrdCurrent MNP market status to target HV MNP acquisitions?
 mnp5
  • Telco at a distant #2, new player gains at the cost of Leader
  • Need to secularize port ins
arrdRegion-wise port-ins?
 mnp06
  • CSI indicates 5 regions have large MNP contributions (63% of industry MNP)
arrdQuantify MNP opportunity in these regions?
 mnp07
  • 13% ( ~345k subs) have high IC call from competition (Off-net calling slabs analysis)
arrdConvert to revenue potential using a scientific method?
 mnp08
  • Customer Potential value Index used to identify & target HV MNP subs across regions/operators

 

Recommendations:

CPV index to identify HV MNP Port in target

mnp09

HV port ins from 5 selected regions for acquisition

 

Results:

  • 3% of High value subs MNP adoption over a quarter
  • 5% Reduction in share gap with Leader in a quarter

Close
Pi leveraged the MNP Opportunity to bridge the gap with the leader. Read more.

MNP Opportunity

 mnp01
  • Declining Base share, Gross share with Gross share(17%) < Base share(22%)
  • Widening gross share gap with leader
  • Acquisition – key to bridge gap with leader
arrdWhat is the acquisition mix
 mnp02
  • Dropping activations
  • MNP contribution to activations at 3%
arrdMNP Acquisitions or Non MNP Acquisitions?
 mnp03
  • ARPU & Quality of MNP acquisitions significantly higher
  • Revenue from 1 MNP sub = ~3 Non MNP sub
arrdPort in subs by revenue segment?
 mnp04
  • ~5% of MNP activations are HV subs bringing in 40% of revenueNeed to target HV port ins
arrdCurrent MNP market status to target HV MNP acquisitions?
 mnp5
  • Telco at a distant #2, new player gains at the cost of Leader
  • Need to secularize port ins
arrdRegion-wise port-ins?
 mnp06
  • CSI indicates 5 regions have large MNP contributions (63% of industry MNP)
arrdQuantify MNP opportunity in these regions?
 mnp07
  • 13% ( ~345k subs) have high IC call from competition (Off-net calling slabs analysis)
arrdConvert to revenue potential using a scientific method?
 mnp08
  • Customer Potential value Index used to identify & target HV MNP subs across regions/operators

 

Recommendations:

CPV index to identify HV MNP Port in target

mnp09

HV port ins from 5 selected regions for acquisition

 

Results:

  • 3% of High value subs MNP adoption over a quarter
  • 5% Reduction in share gap with Leader in a quarter

Close

Data Opportunity

Problem Statement: Identifying opportunities in a high data growth market.

Pivot Output

  • Data sees highest absolute Y-o-Y growth at 23% contributing to 34% of total incremental revenues.. Need to usage trends?
  • Data revenue growth not in line with usage growth. (23% vs 147%) Need to understand Revenue equation?
  • ‘Data Revenue Influencer analysis’ reveals usage/usage day/user & yield as the largest influencers to data revenue. Is it from Activations or Existing base?
  • ‘Activations Vs Existing base Analysis’ shows
    • Usage/user significantly higher in Activations
    • Revenue/user similar for existing base & Activations
    • Yield 33% higher for Existing base over Activations
    • Activations data penetration 18% higher amongst Activations
    • Validates that influencers (Usage/usage day & Yield) are impacted by gap in Activations & Exising base
    • Existing base is a concern. Need to check Existing base by revenue segment?
  • ‘Data revenue tree’ deep dive on existing base indicates,
    • Data Revenue growth funded by Activations.
    • High displacement seen in existing base (Displacement:Replacement ratio: 2:1)
    • Deepdive show HV segments net negative on revenue – elasticity from subscribers not making up for displacement. Need to check HV revenue contribution?
  • ‘Data revenue bell curve’ indicates very high revenue skew – 51% revenue from 11% of the subs. Need for proactive displacement reduction from HV existing subscribers.

 

Pi Recommendations

  • Reactive approach: Floor value triggers to reduce displacement
  • Proactive approach: Data displacement model to identify potential displacers.

Results

  • 20% of High value subs displacement saved
  • Revenue defended: 0.18 Mn
Close
Pi identified an emerging opportunity in Data through a smart analysis of usage trends. Read more.

MNP Opportunity

Problem Statement: Identifying opportunities in a high data growth market.

Pivot Output

  • Data sees highest absolute Y-o-Y growth at 23% contributing to 34% of total incremental revenues.. Need to usage trends?
  • Data revenue growth not in line with usage growth. (23% vs 147%) Need to understand Revenue equation?
  • ‘Data Revenue Influencer analysis’ reveals usage/usage day/user & yield as the largest influencers to data revenue. Is it from Activations or Existing base?
  • ‘Activations Vs Existing base Analysis’ shows
    • Usage/user significantly higher in Activations
    • Revenue/user similar for existing base & Activations
    • Yield 33% higher for Existing base over Activations
    • Activations data penetration 18% higher amongst Activations
    • Validates that influencers (Usage/usage day & Yield) are impacted by gap in Activations & Exising base
    • Existing base is a concern. Need to check Existing base by revenue segment?
  • ‘Data revenue tree’ deep dive on existing base indicates,
    • Data Revenue growth funded by Activations.
    • High displacement seen in existing base (Displacement:Replacement ratio: 2:1)
    • Deepdive show HV segments net negative on revenue – elasticity from subscribers not making up for displacement. Need to check HV revenue contribution?
  • ‘Data revenue bell curve’ indicates very high revenue skew – 51% revenue from 11% of the subs. Need for proactive displacement reduction from HV existing subscribers.

 

Pi Recommendations

  • Reactive approach: Floor value triggers to reduce displacement
  • Proactive approach: Data displacement model to identify potential displacers.

Results

  • 20% of High value subs displacement saved

Close

Our Clients

Management Team

Kumar
‘The Thinker’

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Kumar

Comes with 25+ years experience in corporate, working with leadership positions that include an exciting three years as the CMO of Vodafone India apart from Pepsi, Brittania and Tetrapak.

Known for his lateral thinking abilities and seeing emerging patterns to script great visions, he architected the One to One Marketing agenda for Vodafone – a key differentiator and a global best practice. Also has worked with Vodafone Opcos across the world in implementing Customer Value Management framework.

A strong believer that the “Confluence of power of ‘i’ and the consumer’s power to know will unlock value of enterprise data!”

Highly networked and always high on energy!

A paradoxical sweet tooth and fitness freak!

Has a double masters from Delhi School of Economics and IIM(A).

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Sundar
‘The Simplifier’

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Sundar

Comes with a 20+ years of a rich corporate career studded with names like Google, Vodafone, Asian Paints.

An articulate leader with immense clarity of thought!

Known for his uncanny aptitude to break down complex problems into simple, logical & down to earth solutions.

An avid Technology geek & a fab badminton player who has no qualms about all the right stripes – IIT (Madras) and IIM (Lucknow) alumnus.

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Vijay
‘The Doer’

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Vijay

Comes with a 13+ years of experience in Telecom sales and marketing.

A high-flier in his corporate life, had successfully implemented the Nano-marketing framework during his career at Vodafone and had shown extraordinary results through implementing a robust customer value management framework.

Dynamic & affable, with a unique ability to look at complex data, connect the dots & arrive at sharp actionable insights.

Workaholic with near obsessive yet amusing attention to detail.

He truly believes “It’s all in the mind”.

A good singer & avid chess player, embodies the convergence of Music & Math!

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Investors

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Investors

As one of the leading Retained Search firms in the country, Positive Moves advises conglomerates across the globe while providing comprehensive services for Board Level, Leadership and Senior Management roles.

Vibhav Dhawan

Managing Partner at Positive Moves

A management graduate, Vibhav possesses a wealth of experience within the Executive Search Industry in Asia Pacific. He has over 15 years of experience in the leadership talent acquisition area across Asian markets having built large search practices in the Consumer, Telecom, Financial Services, Energy, Infrastructure & Engineering sectors.

Vibhav has been a Managing Partner with Positive Moves since 2005 and has been responsible for taking the Telecom, Consumer & Energy practices of Positive Moves to a leadership position in India by building management teams for a significant number of global corporations.

Praveen Malhotra

Managing Partner at Positive Moves

One of the Architects of Executive Search Business in India, Praveen played a pivotal role in the evolution of Executive Search Industry in India, when it started taking shape in early 90s, coinciding with liberalization.

Praveen is an MBA from India’s premier B-School – IIM, Ahmedabad (Affiliate of Harvard Business School). He worked with Toyota and an Indian Technology MNC, HCL group, before establishing Positive Moves in 1992.

 

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Join Us

 

Finding ourselves at the intersection of Domain, Analytics & Technology, we have an eclectic mix of people with rich experience in Telecom, FMCG & IT coexisting under the same roof. We have the following exciting positions open @ Pi. Do email us your profile to stars@positiveintegers.com, if interested.

Careers in Domain

Business Development Manager – Commercial

Job Location: Chennai   Key Responsibilities

  • Work on client specific business needs – gathering business requirements to elucidating deliverables
  • Coordination and communication with all stakeholders
  • Identify new opportunities through identifying patterns and insights from data
  • Ensure on-time and error free delivery

Qualifications / Skills Required

  • Degree/Diploma in Business Management or in any Engineering discipline
  • 5- 7 years of relevant business development experience
  • Must possess a minimum of 5 years of progressive marketing management experience
  • Market research experience

To apply please email your profile to stars@positiveintegers.com

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For exciting careers in Domain, click here.

Careers in Domain

Business Development Manager – Commercial

Job Location: Chennai   Key Responsibilities

  • Work on client specific business needs – gathering business requirements to elucidating deliverables
  • Coordination and communication with all stakeholders
  • Identify new opportunities through identifying patterns and insights from data
  • Ensure on-time and error free delivery

Qualifications / Skills Required

  • Degree/Diploma in Business Management or in any Engineering discipline
  • 5- 7 years of relevant business development experience
  • Must possess a minimum of 5 years of progressive marketing management experience
  • Market research experience

To apply please email your profile to stars@positiveintegers.com

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Careers in Technology

ETL Developer – Lead

Job Summary: As an ETL Application Developer Lead, you will provide high quality technology solutions that address business needs by developing   Key Responsibilities

  • Analyze business requirements of clients and outline the proposed IT solution
  • Provide design recommendations
  • Document detailed application specifications
  • Participate in code reviews
  • Design Informatica workflows and mappings
  • Development using Teradata utilities
  • Create and manage PL/SQL packages, triggers, and stored procedures, views, SQL transactions
  • Create and Test Control-M jobs in Non Prod

Qualifications / Skills Required

  • Bachelor’s degree in Computer Science, with minimum 10+ years of Application Development Work Experience
  • 4-7 years of professional software development experience required
  • 3+ years of professional experience as an ETL
  • Extensive experience with all Informatica Power Center transformation types and reusable components.
  • Minimum 4 year hands-on experience in Unix Shell Scripting
  • Minimum 4 year hands-on experience in PL/SQL programming
  • Experience in handling large volume of data preferred
  • Hands on experience on data mart design & development
  • Experience with job scheduling tools such as Control-M

To apply please email your profile to stars@positiveintegers.com

SAS Visual Analytics – Developer

Job Summary: We are looking for a SAS VA developer who will provide high quality technology solutions that address business needs by developing dashboards and reports.   Key Responsiblities

  • Grow the Analytics services within the Technology team and realizing its vision to become the central nervous system of the company for data driven decision making
  • Narrow down on possible answers to the hypothesis provided / business issues articulated
  • Develop specifications for converting data files into formats suitable for analysis and perform exploratory data analysis and modeling
  • Generate output and present findings to Functional owners and SPOCs
  • Own the technical aspects of the model

Qualifications / Skills Required

  • Bachelors in Computer science or related
  • 1 years- 5 years of professional software development experience required
  • 2+ years of professional experience as an SAS Visual Analytics developer

To apply please email your profile to stars@positiveintegers.com

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Click here for the latest openings in Technology

Careers in Domain

ETL Developer – Lead

Job Summary: As an ETL Application Developer Lead, you will provide high quality technology solutions that address business needs by developing   Key Responsibilities

  • Analyze business requirements of clients and outline the proposed IT solution
  • Provide design recommendations
  • Document detailed application specifications
  • Participate in code reviews
  • Design Informatica workflows and mappings
  • Development using Teradata utilities
  • Create and manage PL/SQL packages, triggers, and stored procedures, views, SQL transactions
  • Create and Test Control-M jobs in Non Prod

Qualifications / Skills Required

  • Bachelor’s degree in Computer Science, with minimum 10+ years of Application Development Work Experience
  • 4-7 years of professional software development experience required
  • 3+ years of professional experience as an ETL
  • Extensive experience with all Informatica Power Center transformation types and reusable components.
  • Minimum 4 year hands-on experience in Unix Shell Scripting
  • Minimum 4 year hands-on experience in PL/SQL programming
  • Experience in handling large volume of data preferred
  • Hands on experience on data mart design & development
  • Experience with job scheduling tools such as Control-M

To apply please email your profile to stars@positiveintegers.com

SAS Visual Analytics – Developer

Job Summary: We are looking for a SAS VA developer who will provide high quality technology solutions that address business needs by developing dashboards and reports.   Key Responsiblities

  • Grow the Analytics services within the Technology team and realizing its vision to become the central nervous system of the company for data driven decision making
  • Narrow down on possible answers to the hypothesis provided / business issues articulated
  • Develop specifications for converting data files into formats suitable for analysis and perform exploratory data analysis and modeling
  • Generate output and present findings to Functional owners and SPOCs
  • Own the technical aspects of the model

Qualifications / Skills Required

  • Bachelors in Computer science or related
  • 1 years- 5 years of professional software development experience required
  • 2+ years of professional experience as an SAS Visual Analytics developer

To apply please email your profile to stars@positiveintegers.com

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Careers in Analytics

Sr. Business Analyst

Job Location: Chennai

Key Responsibilities

  • Work on statistical projects, gather business requirements convert them into modelling requirements
  • Ensure transparent communication with all the stakeholders
  • Work on data, carry out data preparation tasks, data quality checks and do the necessary data manipulation
  • Work on tools like SAS / R / SPSS / Kxen
  • Build statistical framework and solutions as per the client requirement
  • Identify patterns and insights from data, present it in a format understandable by the business users and make presentation of the findings

Qualifications / Skills Required

  • 3+ years of relevant analytical experience
  • Experience in the area of analytics and having done projects involving Segmentation, Decision Tree, Logistic Regression, and other such statistical models
  • Bachelors / Masters degree in Engg / Statistics / Mathematics or similar is desired
  • Strong programming skills in SAS  & SQL
  • Knowledge of R will be an added plus

To apply please email your profile to stars@positiveintegers.com

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If you are looking to give insights, click here.

Careers in Analytics

Sr. Business Analyst

Job Location: Chennai

Key Responsibilities

  • Work on statistical projects, gather business requirements convert them into modelling requirements
  • Ensure transparent communication with all the stakeholders
  • Work on data, carry out data preparation tasks, data quality checks and do the necessary data manipulation
  • Work on tools like SAS / R / SPSS / Kxen
  • Build statistical framework and solutions as per the client requirement
  • Identify patterns and insights from data, present it in a format understandable by the business users and make presentation of the findings

Qualifications / Skills Required

  • 3+ years of relevant analytical experience
  • Experience in the area of analytics and having done projects involving Segmentation, Decision Tree, Logistic Regression, and other such statistical models
  • Bachelors / Masters degree in Engg / Statistics / Mathematics or similar is desired
  • Strong programming skills in SAS  & SQL
  • Knowledge of R will be an added plus

To apply please email your profile to stars@positiveintegers.com

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