The document discusses trends in global technology talent and costs. It notes a "Gini effect" where pay can widely vary for similar roles in emerging markets. Additionally, expectations of constant pay raises in Asia have led to a "Goldilocks syndrome." The document also examines the growth of tier 2 tech hubs in the US and potential talent impacts from the European debt crisis.

1. Understanding Cost and Talent Characteristics
From Gini Effect to Goldilocks Syndrome in global technology talent pool
Talent Practice
Data | Analytics | Technology | Network
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2. Introduction
2012 will see an increase in the global location and talent foot print of technology companies. The global
foot print of technology companies is influenced by many drivers. In a recent Zinnov survey of HR leaders,
the following reasons were identified as the primary drivers:
- Planned movement to global locations to take advantage of superior global design and development skills
- Planned movement to global locations with cost savings as the primary goal
- Global location growth due to acquisitions
- Movements associated with market expansion
The primary objective of this article is to explore the cost characteristics of the global technology talent.
Several economic factors also dominated the year 2011 including reduced consumer spending in the US,
European debt crisis, and economic policy issues in Asia. The economic factors have medium to long term
impact on the cost and availability of global talent pool. In addition to explaining cost characteristics of the
global technology talent, this article will also examine the relationship between talent pool and macro-
economic factors.
The rise of “Gini Effect” in emerging locations
In emerging countries, there is significant variation in cost for a similar talent classification at the same
location, for the same position. This wide range of pay introduces the classical economic “Gini Effect”
where in locations like India and China have a wide range of pay for a specific experience level in a given
domain. For example, the compensation for entry level IT professionals in Bangalore, India is in the range
of USD 4,760 – USD 10,200. Similar trend exists in software and hardware product development domains.
In other words, if examined using classical economic models, the Gini index will be high for various job
levels and positions in emerging countries. Zinnov recently analyzed why this variation is more
pronounced in emerging countries. The three major factors contributing to this effect are as follows:
Type of employer: In emerging countries, there is a distinct pay difference between what multi-
national companies (MNC) companies, service provider companies and the local companies pay their
respective talent
Type of education: The fresh engineering talent pool (which feeds a majority of the talent pool) can
originate from different grades of engineering institutes (commonly referred to as the Tier1, Tier2 and
Tier3 institutes)
Alternate talent pool: In addition to the core engineering curriculum, several non-engineering
graduates undergo training in the form of certifications and enter the technology talent pool
The Gini effect is not necessarily a new trend in emerging locations. And it is bound to continue as there is
the prolific expansion of institutes, the emergence of tier2 cities at these locations, and as more and more
non-engineering graduates aspire to enter into the technology industry through certifications. Such
disparities normally take years to dissipate, hence the Gini effect will stay on for the next few years.
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3. Companies need to understand this effect for the following reasons:
• This situation provides a unique opportunity to Global organizations – a realignment of the pyramid
structures with respect to the type of work executed at these locations can greatly improve the
contribution as well as impact of emerging locations in the location matrix
• Business case of executing a global portfolio may look more aggressive on paper than in reality. This
is because the benchmarks may indicate a lower average due to this disparity during planning stages
In summary, the Gini effect can be an advantage if understood thoroughly by organizations.
Figure 1: Variance in Pay
Salary Growth Rates and Goldilocks Syndrome:
In Asia Pac countries, there is on an average, about 8% to 12% increase per year in the labor cost across
various levels. Engineering labor cost in emerging locations is also the domain with the highest pay.
Zinnov’s recent analysis of labor cost across four key domains - BPO, IT, Technology and Manufacturing,
revealed some interesting insights. As a general rule, salary increases with experience across the four
domains but the rate of pay growth by experience levels is highest in technology.
 In the Technology domain in emerging locations, based on our data set, a minimum salary of
around USD 10,000 and a maximum salary of around USD 160,000 were observed.
 Other verticals proved less expensive with a minimum salary of less than USD 5,000 and a
maximum salary of USD 85,000 to USD 100,000 for the BPO, Manufacturing and IT domains.
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4. The consistent growth in salary in India and China has induced a “Goldilocks Syndrome” effect in the
labor pool. A classic situation of this effect is when the labor pool almost expects constant and upward
growth in the pay rate. This effect is very complex when analyzed from a behavior science point of view.
The expectation is set by several aspects including social, environmental and employee peer factors.
Zinnov’s analysis also shows that the top of the pyramid “management” talent pool may have limited
mobility options. This is because there are only few positions that would offer similar pay advantages at
that level.
In countries like India, the inflation rate is increasing at very high levels. In spite of such not so favorable
labor cost headwinds, the Asia Pac locations will continue their dominance in technology talent and
location footprint.
Labor Cost Growth Rate (CAGR %)
Labor Cost per FTE (USD)
Figure 2: Labor Cost Growth Rates
The primary reasons for this expected trend includes:
- The median cost of technology talent pool is still the lowest in the Asia Pac region, making these
locations very attractive especially for large technology teams.
- Innovation, a key metric indicating the maturity of talent pool is one the rise in Asia. Several examples
and case studies are emerging from India and China in the field of technological innovation.
- Since 2005, Asian countries have seen maximum growth rate in talent pool number; India and China
leading the pack.
- Favorable government policies especially in China have accelerated growth of the technology talent
pool.
- The customer base for technology companies in the Asia Pac region is expanding constantly
resulting in “close to customer” talent requirements
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5. Second Talent Wave: The emergence of Tier2 locations in the United States
In 2011, Zinnov launched an extensive analysis of tier2 locations in the United States with an objective of
evaluating the technology talent pool. Over 50 tier2 locations were analyzed. The results of our evaluation
indicated that some of the locations including Ann Arbor, Boise, Raleigh, Boulder and Fairfax are viable
technology locations within the US. Several factors were considered in this evaluation including talent
base, university ecosystem, competitive landscape, labor policy and other such critical factors. Our
research and surveys indicated that on an average there is a 30% cost difference in the cost for
technology talent between tier1 cities and tier2 cities. (Please note that our tier definitions were based on
talent taxonomy. Locations such as Bay Area, Boston are clustered as tier1 cities in this analysis while
other cities such as Ann Arbor, Boise are clustered as tier2).
Based on our analysis, we project that the current economic trends in the US will help these tier2 locations
to continue to gain momentum from this “Second Talent Wave”. These conditions include a moderate
recovery in the US, slightly better economic conditions compared to 2008, controlled inflation and a slightly
improving economic outlook. Zinnov calls this wave as a second talent wave because the first talent wave
was associated with the movement of talent from the Bay Area to locations like Austin in 2005 to 2006.
The first wave brought some initial benefits to Austin, but as the economy collapsed, the global movement
took place at a far aggressive pace.
Zinnov believes that in 2012, more technology companies will take advantage of tier2 locations in the US
especially for small to medium sized operations.
Figure 3: US Tier2 Location Suitability
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6. The Impact of European Debt Crisis
The last few years witnessed growth in several Central and Eastern European locations with respect to the
technology talent pool. The situation is not very encouraging when it comes to western European
locations. The debt crisis and prolonged unemployment in western European nations is expected to drive
out talent to outside locations. Continued economic distress is driving skilled professionals from Europe,
and many are moving to former European colonies in Latin America and Africa (Ref: Wall Street Journal).
This labor movement will be closely watched in 2012. Several European nations are losing S&P credit
rating - this will further accelerate this movement. Such accelerated movements may further prolong the
crisis from a macro economic standpoint.
Figure 4: Talent Pool Growth in Eastern and Central European Locations
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7. Conclusion
Prior to 2000, majority of the technology companies were concentrated in one part of the globe, i.e., the
US and Western Europe. In the period post 2000, there was the emergence of new global hotspots and a
shift of operations to Asia Pac and Eastern and Central European regions.
The technology talent pool in the Asia Pac locations continue to offer several advantages with respect to
cost and scale. With those advantages, there are some challenges associated with cost escalation and
talent expectation management. A phenomenon called “Fat Tailed Effect” can be observed with respect
to technology talent in Asia Pac locations. A fat tailed effect simply states that “averages” will not
necessarily indicate the correct market conditions. In such cases, benchmarks around the mean
(benchmarks driven by assuming normal distribution of salaries, talent acquisition time, retention period,
talent mobility etc.) may not reflect the ground reality accurately.
While Eastern European technology locations are expected to grow, the world is watching the
developments in Western Europe. It will be interesting to see the impact of the crisis on technology talent
pool movements in 2012.
Additional Information
Zinnov has conducted multiple surveys on global talent, cost and peer group analysis. Please send your requests to
info@zinnov.com to schedule a free 1 hour workshop on Deputed Workforce.
About Zinnov
Founded in 2002, Zinnov – meaning Zeal in Innovation – provides solutions and advisory services in the area of
Talent, Global Sourcing and Emerging Markets Expansion to Fortune 1000 and reputed SMB companies.
Zinnov’s Talent Neuron product is a web based tool that provides talent, cost, peer group benchmarking and location
data. The insights, analytics and data driven intelligence empowers HR, Engineering, IT, Shared Services and
Corporate Executives in developing/executing strategic, operational and transformation initiatives.
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