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Better Decisions === Faster Stats
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    Tagged: job management, management, offshoring, tutorial, vendor selection

    AohriAohri

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  • 10/22/09--12:14: Big Talking
  • Here is a link to my video capture of classroom presentation I did for some students today- ( note plays on Windows Media Player only and uses streaming thanks to the University of Tennessee’s high tech initiatives )

    The slides are given in the form of SlideShare presentations and also here-

    http://docs.google.com/present/view?id=dcvss358_955fsvm8mfr&autoStart=true&loop=true

    and

    http://docs.google.com/present/view?id=dcvss358_961djjqdtdd&autoStart=true&loop=true

    The topics are

    1) Creating an R Package easily ( till first 30 minutes)

    and

    2) Offshoring 101 (last 25 minutes)

    Title: R and Offshorring
    Speaker: Ajay Ohri
    Desription: Oct 22, 2009
    URL: http://vcweb.bus.utk.edu/20091022-124732-cap530/

    ps- I am sorry for the accented language and hope audio is audible.


    Tagged: offshoring, R

    AohriAohri

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  • 11/25/09--21:56: Born in the USA?
  • Here is some econometric search-ing I did

    Using Google Public Data-and Wolfram Alpha and The Bureau of Labour Statistics

    United States

    United States – Monthly Data
    Data Series Back
    Data
    May
    2009
    June
    2009
    July
    2009
    Aug
    2009
    Sept
    2009
    Oct
    2009
    Unemployment Rate (1)
    Jump to page with historical data
    9.4 9.5 9.4 9.7 9.8 10.2
    Change in Payroll Employment (2)
    Jump to page with historical data
    -303 -463 -304 -154 (P) -219 (P) -190
    Average Hourly Earnings (3)
    Jump to page with historical data
    18.53 18.54 18.59 18.66 (P) 18.67 (P) 18.72
    Consumer Price Index (4)
    Jump to page with historical data
    0.1 0.7 0.0 0.4 0.2 0.3
    Producer Price Index (5)
    Jump to page with historical data
    0.2 1.7 (P) -1.0 (P) 1.7 (P) -0.6 (P) 0.3
    U.S. Import Price Index (6)
    Jump to page with historical data
    1.7 2.7 (R) -0.6 (R) 1.5 (R) 0.2 (R) 0.7
    Footnotes
    (1) In percent, seasonally adjusted. Annual averages are available for Not Seasonally Adjusted data.
    (2) Number of jobs, in thousands, seasonally adjusted.
    (3) For production and nonsupervisory workers on private nonfarm payrolls, seasonally adjusted.
    (4) All items, U.S. city average, all urban consumers, 1982-84=100, 1-month percent change, seasonally adjusted.
    (5) Finished goods, 1982=100, 1-month percent change, seasonally adjusted.
    (6) All imports, 1-month percent change, not seasonally adjusted.
    (R) Revised
    (P) Preliminary
    United States – Quarterly Data
    Data Series Back
    Data
    3rd Qtr
    2008
    4th Qtr
    2008
    1st Qtr
    2009
    2nd Qtr
    2009
    3rd Qtr
    2009
    Employment Cost Index (1)
    Jump to page with historical data
    0.6 0.6 0.3 0.4 0.4
    Productivity (2)
    Jump to page with historical data
    -0.1 0.8 0.3 6.9 9.5
    Footnotes
    (1) Compensation, all civilian workers, quarterly data, 3-month percent change, seasonally adjusted.
    (2) Output per hour, nonfarm business, quarterly data, percent change from previous quarter at annual rate, seasonally adjusted.

    And also included are the average wages for salary of teachers and average salary per hour of some offshore  prone industries

    http://www.bls.gov/oes/2008/may/oes_nat.htm#b25-0000

    http://www.bls.gov/oes/2008/may/oes_nat.htm#b11-0000

    and

    http://www.google.com/publicdata?ds=usunemployment&met=unemployment_rate&idim=state:ST370000:ST540000:ST510000&tdim=true

    WHAT THEY PAY TEACHERS (MAY 2008)

    Education, Training, and Library Occupations top
    Wage Estimates
    Occupation Code Occupation Title (click on the occupation title to view an occupational profile) Employment (1) Median Hourly Mean Hourly Mean Annual (2) Mean RSE (3)
    25-0000 Education, Training, and Library Occupations 8,451,250 $21.26 $23.30 $48,460 0.5 %
    25-1011 Business Teachers, Postsecondary 69,690 (4) (4) $77,340 1.0 %
    25-1021 Computer Science Teachers, Postsecondary 32,520 (4) (4) $74,050 1.0 %
    25-1022 Mathematical Science Teachers, Postsecondary 45,710 (4) (4) $68,130 0.9 %
    25-1031 Architecture Teachers, Postsecondary 6,430 (4) (4) $75,450 1.9 %
    25-1032 Engineering Teachers, Postsecondary 32,070 (4) (4) $90,070 1.1 %
    25-1041 Agricultural Sciences Teachers, Postsecondary 10,000 (4) (4) $77,770 1.6 %
    25-1042 Biological Science Teachers, Postsecondary 51,930 (4) (4) $83,270 2.7 %

    WHAT THEY PAY THEMSELVES

    Management Occupations top
    Wage Estimates
    Occupation Code Occupation Title (click on the occupation title to view an occupational profile) Employment (1) Median Hourly Mean Hourly Mean Annual (2) Mean RSE (3)
    11-0000 Management Occupations 6,152,650 $42.15 $48.23 $100,310 0.2 %
    11-1011 Chief Executives 301,930 $76.23 $77.13 $160,440 0.5 %
    11-1021 General and Operations Managers 1,697,690 $44.02 $51.91 $107,970 0.2 %
    11-1031 Legislators 64,650 (4) (4) $37,980 1.1 %

    and JOBS PRONE TO SHORTAGE /OFFSHORING

    Computer and Mathematical Science Occupations top
    Wage Estimates
    Occupation Code Occupation Title (click on the occupation title to view an occupational profile) Employment (1) Median Hourly Mean Hourly Mean Annual (2) Mean RSE (3)
    15-0000 Computer and Mathematical Science Occupations 3,308,260 $34.26 $35.82 $74,500 0.3 %
    15-1011 Computer and Information Scientists, Research 26,610 $47.10 $48.51 $100,900 1.1 %
    15-1021 Computer Programmers 394,230 $33.47 $35.32 $73,470 0.6 %
    15-1031 Computer Software Engineers, Applications 494,160 $41.07 $42.26 $87,900 0.4 %
    15-1032 Computer Software Engineers, Systems Software 381,830 $44.44 $45.44 $94,520 0.5 %
    15-1041 Computer Support Specialists 545,520 $20.89 $22.29 $46,370 0.3 %
    15-1051 Computer Systems Analysts 489,890 $36.30 $37.90 $78,830 0.4 %
    15-1061 Database Administrators 115,770 $33.53 $35.05 $72,900 0.8 %
    15-1071 Network and Computer Systems Administrators 327,850 $31.88 $33.45 $69,570 0.3 %
    15-1081 Network Systems and Data Communications Analysts 230,410 $34.18 $35.50 $73,830 0.4 %
    15-1099 Computer Specialists, All Other 191,780 $36.13 $36.54 $76,000 0.5 %
    15-2011 Actuaries 18,220 $40.77 $46.14 $95,980 1.4 %
    15-2021 Mathematicians 2,770 $45.75 $45.65 $94,960 1.7 %
    15-2031 Operations Research Analysts 60,860 $33.17 $35.68 $74,220 0.8 %
    15-2041 Statisticians 20,680 $34.91 $35.96 $74,790 1.5 %
    15-2091 Mathematical Technicians 1,100 $18.46 $20.24 $42,100 2.7 %
    15-2099 Mathematical Science Occupations, All Other 6,600 $26.44 $31.55 $65,630 4.3 %

     

    UNEMPLOYED IN THE USA (above)

    BY STATE (below)

    16 million people out of work. Give or take a million.

    How can America pay 5.6 million people UNEMPLOYMENT BENEFITS

    Keep another 10 million unemployed,

    another 10 million only partially employed.

    and still claim aggregate cost savings from offshoring jobs.


    Tagged: google public data, offshoring, statistics, unemployement, united states, wolfram alpha

    AohriJump to page with historical dataJump to page with historical dataJump to page with historical dataJump to page with historical dataJump to page with historical dataJump to page with historical dataJump to page with historical dataJump to page with historical dataScreenshot-3Screenshot-4AohriJump to page with historical dataJump to page with historical dataJump to page with historical dataJump to page with historical dataJump to page with historical dataJump to page with historical dataJump to page with historical dataJump to page with historical dataScreenshot-3Screenshot-4

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    Using Yahoo Finance, I plotted the past three years stock price of Indian Offshores  (Genpact, Wns, Exl) and in comparison with Indian Software companies (Infosys, Wipro, TCS, Sify) and market index.

    The following insights emerge-

    1) Indian Software companies have constantly created wealth.

    2) Indian Offshoring companies have constantly lost market value – perhaps because they were able to dump IPO prices at much higher prices by creating hype.

    3) You are much better off investing in Indian stock market or a blue chip Indian software company than take part in an Indian offshorers IPO.

    4) SIFY lost most value and its founder CEO is now in jail for fraud. The fraud was he added phantom employees, and phantom revenue to boost balance sheet. Auditors from PwC (were jailed) included a board member of Indian Chartered Accountants and Satyam (SIFY) had won awards for corporate governance. It makes sense to do rigorous cash flow due diligence this side of the pond.

    5) I won no stock in any of this companies  (not surprisingly) but do have a portfolio of mutual funds (index).

    So the next time you are promised the moon by an Indian IPO- KPO, remember to do the math ;)


    Tagged: BPO, ceo, Companies, founder, indian bpos, indian kpos ipo, indian offshoring ipos, kpo, Math, offshoring, software, Stock market, Time, yahoo

    AohriSlide1AohriSlide1

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    The Hall of Prayer for Good Harvest, Temple of...

    Image via Wikipedia

    An interview with a noted Indian Software CEO, mentions China the possible biggest threat in next 5 years at  http://www.thehindubusinessline.com/2010/10/13/stories/2010101353180700.htm

     

    China could be the biggest threat to India in next five years, positioning itself as the lowest-cost manpower supplier in the IT sector by 2015, according to Mr Vineet Nayar, CEO, HCL Technologies.

    “I believe it (China) is the biggest threat in the next five years that we are going to face…So India will have to up its game,” he told reporters on sidelines of ‘Directions’, the company’s annual town hall.

    Terming China, as both “threat and opportunity”, Mr Nayar said that India will have to find alternate “differentiators” than the ones it currently has. Despite issues of language and the purported inability to scale-up, China has sharpened its technological and innovation edge, he added.

    “Look at the technology companies from China…how does that fit in with the assumption that they (China) do not understand English or technology. They are producing cutting edge technology at a price which is lower than everyone else,” he said.

    Manpower

    By 2015, Mr Nayar said, China will be the lowest cost manpower supplier in IT sector to the world

    ——————————————————————————————–

    I wonder how he did his forecast. Did he do a time series analysis using a software, did he peer into his crystal ball, or did he spend a lot of time brainstorming with his strategic macro economic team on Chinese threat.

    China has various advantages over India (and in fact the US)-

    1) Big pool of reliable scientific manpower

    2) State funded education in higher studies and STEM

    3) Increasing exposure with the West-English speaking is no longer an issue. Almost 50 % of Grad Students in the US in STEM and certain sectors are Chinese and they not only retain fraternal ties with the motherland- they often remain un-assimilated with American Culture mainstream. or they have a separate interaction with fellow American Chinese and seperate with American Americans.

    Chinese suffer from some disadvantages in software-

    1) Communism Perception- Just because the Govt is communist and likes to confront US once a year (and India twice a month)- is no excuse for the hapless Chinese startup guy to lose out on software outsourcing contracts. unfortunately there have been reported cases where sneak codes have been inserted in code deliverables for American partners, just like American companies are forced to work with DoD (especially in software, embedded chips and telecom)

    If you have 10000 lines of code delivered by your Chinese partner, how sure are you of going through each line of code for each sub routine or call procedure.

    2) English- Chinese accent is like Chinese cooking. Unique- many Chinese are unable to master the different style of English even after years (derived from Latin and Indo European class of languages)

    Sales jobs tend to go to American trained Chinese or to Westerners.

    In Indian software companies, accent is a lesser problem.

    ———————————————————————————-

    The biggest threat to Indian software in 5 years is actually Indian software itself- Can it evolve and mature to a product based model from a service only model.

    Can Indian software partner with Chinese companies and maybe teach the Indian government why friendship is more profitable than envy and suspicion. If the US and China can trade enormously despite annual tensions, why cant Indian services do the same- if they lose this opportunity, US companies will likely bypass them and create the same GE/McKinsey style backoffices that started the Indian offshoring phenomenon.

    3) Lastly- what did the poor American grad student do to deserve that even if devotes years to study STEM (and being called a Geek and Nerd) his job will get outsourced to India or China (if not now- in his 30s or worse in his 40s). Talk to any middle aged IT chap in the US who is middle class- and India and China would figure in why he still worries about his overpriced mortgage.

    Unless the US wants only Twitter and Facebook as dominant technologies in the 21 st century.

    Amen.

     

     

     


    Tagged: america, analysis, Asia, china, code, Companies, culture, Economic, education, English language, facebook, government, Government of India, HCL Technologies, India, interview, jobs, Language, Latin, model, offshoring, outsourcing, sector, security, software, startup, STEM, student, technology, Time, Time series, time series analysis, twitter, united states, US, Vineet Nayar, why, work

    AohriThe Hall of Prayer for Good Harvest, Temple of...AohriThe Hall of Prayer for Good Harvest, Temple of...

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    The impact of currency fluctuations on outsourcing businesses globally.

    If you have a current offshore team in a different country/currency zone then you may find that the significant cost savings from outsourcing have vanished due to currency fluctuations that occur for reasons like earthquakes, war or oil- something which is outside the core competency of your business corporation. As off shoring companies incur cost in local currencies but gain revenue in American Dollars and Euro (mostly), they pass on these fluctuating costs to their customers but rarely pass along discounts on existing contracts. Sometimes the offshoring contract actually gains from currency fluctuations.The Indian rupee has fluctuated from  43.62 Rupees per USD (04-01-2005) to 48.58 (12-31-2008) to the current value of 44.65.This makes for a volatility component of almost 10 percentage points to the revenue and profit margins of an off shoring vendor. Inflation in India has been growing at 8.5 % and the annual increase in salaries has been around 10-15 % for the past few years. Offshoring vendors have been known to cut back on quality in recruitment when costs have risen historically, and the current attrition rate in Indian ITES is almost 17%.
    This raises important questions for companies going for global bids for the offshoring contracts. Should macroeconomic indicators like currency fluctuations, wage-inflation be part of the request for proposal process (RFP). Would vendors be comfortable in disclosing the ratio of salary costs to billing revenue. Should dips in service quality be penalized by customer. Most importantly, while going in for a multi year contract, the projection of fore-casted savings may vary greatly due to extraneous factors.
    (this article was originally written for and published by http://www.indiasoftwarebrief.com/ in their daily newsletter and their socail media channel- see http://www.linkedin.com/groups/impact-currency-fluctuations-on-outsourcing-3825591.S.48411960)

     

     


    Tagged: attrition, Business, Business process outsourcing, Companies, Contract, costs, currency, Gains, India, Indian rupee, media, offshoring, outsourcing, quality, Salary, united states, war

    AohriAohri

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    Here is an interview with Pranay Agrawal, Executive Vice President- Global Client Development, Fractal Analytics – one of India’s leading analytics services providers and one of the pioneers in analytics services delivery.

    Ajay- Describe Fractal Analytics’ journey as a startup to a pioneer in the Predictive Analytics Services industry. What were some of the key turning points in the field of analytics that you have noticed during these times?

    IMG_5387

    Pranay- In 2000, Fractal Analytics started as a pure-play analytics services company in India with a focus on financial services. Five years later, we spread our operation to the United States and opened new verticals. Today, we have the widest global footprint among analytics providers and have experience handling data and deep understanding of consumer behavior in over 150 counties. We have matured from an analytics service organization to a productized analytics services firm, specializing in consumer goods, retail, financial services, insurance and technology verticals.
    We are on the fore-front of a massive inflection point with Big Data Analytics at the center. We have witnessed the transformation of analytics within our clients from a cost center to the most critical division that drives competitive advantage.  Advances are quickly converging in computer science, artificial intelligence, machine learning and game theory, changing the way how analytics is consumed by B2B and B2C companies. Companies that use analytics well are poised to excel in innovation, customer engagement and business performance.

    Ajay- What are analytical tools that you use at Fractal Analytics? Are there any trends in analytical software usage that you have observed?

    Pranay- We are tools agnostic to serve our clients using whatever platforms they need to ensure they can quickly and effectively operationalize the results we deliver.  We use R, SAS, SPSS, SpotFire, Tableau, Xcelsius, Webfocus, Microstrategy and Qlikview. We are seeing an increase in adoption of open source platform such as R, and specialize tools for dashboard like Tableau/Qlikview, plus an entire spectrum of emerging tools to process manage and extract information from Big Data that support Hadoop and NoSQL data structures

    Ajay- What are Fractal Analytics plans for Big Data Analytics?

    Pranay- We see our clients being overwhelmed by the increasing complexity of the data. While they are all excited by the possibilities of Big Data, on-the-ground struggle continues to realize its full potential. The analytics paradigm is changing in the context of Big Data. Our solutions focus on how to make it super-simple for our clients combined with analytics sophistication possible with Big Data.
    Let’s take our Customer Genomics solution for retailers as an example. Retailers are collecting information about Shopper behaviors through every transaction. Retailers want to transform their business to make it more customer-centric but do not know how to go about it. Our Customer Genomics solution uses advanced machine learning algorithm to label every shopper across more than 80 different dimensions. Retailers use these to identify which products it should deep-discount depending on what price-sensitive shoppers buy. They are transforming the way they plan their assortment, planogram and targeted promotions armed with this intelligence.

    We are also building harmonization engines using Concordia to enable real-time update of Customer Genomics based on every direct, social, or shopping transaction. This will further bridge the gap between marketing actions and consumer behavior to drive loyalty, market share and profitability.

    Ajay- What are some of the key things that differentiate Fractal Analytics from the rest of the industry? How are you different?

    Pranay- We are one of the pioneer pure-play analytics firm with over a decade of experience consulting with Fortune 500 companies. What clients most appreciate about working with us includes:

    • Experience managing structured and unstructured Big Data (volume, variety) with a deep understanding of consumer behavior in more than 150 counties
    • Advanced analytics leveraging supervised machine-learning platforms
    • Proprietary products for example: Concordia for data harmonization, Customer Genomics for consumer insights and personalized marketing, Pincer for pricing optimization, Eavesdrop for social media listening,  Medley for assortment optimization in retail industry and Known Value Item for retail stores
    • Deep industry expertise enables us to leverage cross-industry knowledge to solve a wide range of marketing problems
    • Lowest attrition rates in the industry and very selective hiring process makes us a great place to work

    Ajay- What are some of the initiatives that you have taken to ensure employee satisfaction and happiness?

    Pranay- We believe happy employees create happy customers. We are building a great place to work by taking a personal interest in grooming people. Our people are highly engaged as evidenced by 33% new hire referrals and the highest Glassdoor ratings in our industry.
    We recognize the accomplishments and contributions made through many programs such as:

    1. FractElite – where peers nominate and defend the best of us
    2. Recognition board – where anyone can write a visible thank you
    3. Value cards – where anyone can acknowledge great role model behavior in one or more values
    4. Townhall – a quarterly all hands where we announce anniversaries and FractElite awards, with an open forum to ask questions
    5. Employee engagement surveys – to measure and report out on satisfaction programs
    6. Open access to managers and leadership team – to ensure we understand and appreciate each person’s unique goals and ambitions, coach for high performance, and laud their success

    Ajay- How happy are Fractal Analytics customers quantitatively?  What is your retention rate- and what plans do you have for 2013?

    Pranay- As consultants, delivering value with great service is critical to our growth, which has nearly doubled in the last year. Most of our clients have been with us for over five years and we are typically considered a strategic partner.
    We conduct client satisfaction surveys during and after each project to measure our performance and identify opportunities to serve our clients better. In 2013, we will continue partnering with our clients to define additional process improvements from applying best practice in engagement management to building more advanced analytics and automated services to put high-impact decisions into our clients’ hands faster.

    About-

    Pranay Agrawal -Pranay co-founded Fractal Analytics in 2000 and heads client engagement worldwide. He has a MBA from India Institute of Management (IIM) Ahmedabad, Bachelors in Accounting from Bangalore University, and Certified Financial Risk Manager from GARP. He is is also available online on http://www.linkedin.com/in/pranayfractal

    Fractal Analytics is a provider of predictive analytics and decision sciences to financial services, insurance, consumer goods, retail, technology, pharma and telecommunication industries. Fractal Analytics helps companies compete on analytics and in understanding, predicting and influencing consumer behavior. Over 20 fortune 500 financial services, consumer packaged goods, retail and insurance companies partner with Fractal to make better data driven decisions and institutionalize analytics inside their organizations.

    Fractal sets up analytical centers of excellence for its clients to tackle tough big data challenges, improve decision management, help understand, predict & influence consumer behavior, increase marketing effectiveness, reduce risk and optimize business results.

     


    Tagged: Analytics, Big Data, data analysis, fractal analytics, India, Machine learning, NoSQL, offshoring, pranay agrawal, spotfire, united states

    AohriIMG_5387AohriIMG_5387


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