Infosys Knowledge Services enables our clients to deliver on complex processes and monetize their data assets. Knowledge Services like Research, Analytics, Reporting and Legal Services can create multiplier impact to both the BPO and IT businesses. It is the third wave of outsourcing expected to grow to USD 17 billion. Infosys Knowledge Services blog is a platform to exchange thoughts, ideas and opinions with Infosys experts on Knowledge Services.

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April 4, 2010

Customer Segmentation - get started with what you have, than eternally wait for a perfect solution!

Had an aha experience recently during an exchange with a very senior leader of a consumer electronics manufacturer. It was an interim review meeting scheduled to go over the Customer Value Segmentation methodology one of the Analytics Managers in my team & the project team under her had developed for use by the client business - for differentiated customer service & precision targeting their campaigns

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Ignore this power shift - at your own risk!

It is always a very refreshing experience for practitioners (technology & service providers) to interact with industry analysts, for it offers an opportunity to validate what we think will work / will not work "out there" in the market, through the eyes of a neutral observer.

I was in one such discussion recently with Lora Cecere (www.supplychainshaman.com), widely followed by the industry (esp. consumer goods manufacturers) for her thoughts on Supply Chain Management.

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January 22, 2010

Right-mixing Science and Art for better Decision Making

Decision making today is more oriented towards data, metrics, predictability models and controls. Risk department forecasts their numbers using heavy duty econometric models. Many of these models are based on absolute precision. Recall the phrase ‘show me the data’ before making any argument. The point is organizations are heavily depending on science today to run the business. We are not challenging science here; it is the way it is being used to make decisions. Why are we consistently getting our numbers wrong? Now there is news about China’s real estate bubble and rise in US foreclosures. Why we make wrong decisions based on certain system and do not learn from them? Why we go back to the same system after failing? Using sophisticated financial models, CEO’s make next quarter guidance only to get them wrong again and later get criticized for not delivering on their promise. 

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January 13, 2010

Employee Attrition Management - missing the forest for the trees

With the slight improvement in the economy and the business pipeline looking up the menace of attrition has again raised its head. Attrition rates are again back to the pre slowdown time when companies in the new economy had very high attrition rates. Specifically IT/ITES companies are seeing attrition at the mid 30 to 40% level.

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December 29, 2009

Model Performance Metrics Calibration

A financial risk model by definition is required to measure and manage risk as per its defined objectives. Due to churn in business and employees taking more roles and responsibilities, sometimes the poorly documented model create problems for its new owner. The problem gets magnified during its validation as mandated by the system.

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November 13, 2009

Loss Reserving Approaches

In recent times, global financial markets are shaken by a credit crisis originating from U.S. mortgages. Some of the big banks including those with diversified portfolios with good track records have shown signs of eroding profits and credit crunch. This has brought the focus back on to the risk process adopted during last decade when the charge-offs were historically lower. As the audit process for loss forecasting are becoming more rigorous, bankers are finding their existing loss forecast process being either over simplistic or too complex to understand and validate. Hence a better method is needed which can incorporate historical information, economic trends and multi-model support without making it challenging to implement and maintain.

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November 12, 2009

Winning in the turns with "Analytics on Demand”

As the world comes out of the worst financial crisis ever, the world has seen two big turns in the space of the last 12 months alone. Lehman fall led to panic leading to the first big turn and the anniversary of the big fall was greeted by record stock market highs, possibly leading us to the next big turn. Organizational nimbleness has never been tested like this before, and, worst still, the global volatility, given the free web and higher degree of interdependence between multiple economies and events, does not show signs of ever reducing.

Understanding ever-growing reams of data with agility– both organizational as well as macro-economic, has assumed significant importance given the environment. While detailed and on time insights into the data around customers, vendors, productivity, profitability etc. enable the organizations to raise their ability to extract the best productivity from the resources deployed, these insights also provide them early signals on the business performance and bolster their capability to react quickly to the volatile business environment.

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November 11, 2009

Employee Engagement or Employee satisfaction ?

It is a typical chicken and egg question - employee satisfaction or employee engagement - what comes first? Where should the orgonization focus more? 

There are almost equal no of HR experts on both the sides and they have all the logic to support their individual and collective belief.

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November 3, 2009

Analytics Magazine!

Didn't know there is a dedicated magzine out there for Analytics

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November 1, 2009

KNIME! This is cool

One look at KNIME(!? - then read on), and it's stunning

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October 28, 2009

Getting the analytics rocket to lift-off!

For analytics to really kick-in for any organization, managers need to be able to strategize based on the data analysis done. More often than not, the means to the end is defeated as managers are swamped doing data analysis leaving little or no time for the strategizing part.

The analysis for why this problem originated has been done too! Organizations typically have a pyramid structure for their resources…broad base of junior employees, small middle management and still smaller senior management. In any Knowledge Services division in the US, due to paucity of requisite skill set, junior and middle management get promoted faster leading to a huge rocket booster strap in the middle. The problem is this booster strap weighs the division down as the roles change but the job profile remains the same… analyzing data.

The KPO analytics outsourcing wave has been built on the premise that by adding skill set relevant resources largely at junior levels to do the data analysis piece, the rocket can be stabilized and lift off can be achieved.  

 

Use HR analytics to positively impact your ops profit

Historically, the HR world has been relying on a lot of qualitative data for taking many decisions which have an effect on the organization at multiple levels. The sparse usage of quantitative data could have many reasons of which non-availability of data, lack of one-view of the employee (data), non-availability of an integrated data system to enable various data types to talk to each other or simply the inability or unwillingness of the HR professional to use hard data to take decisions related to human beings are some of the oft repeated reasons.

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October 27, 2009

Evolution of Job

Thousands of years back man went to work every day to fetch food for the family by hunting in the jungles. Much later man went on to do farming to produce enough food for the family. From Hunting to Farming it probably took thousands of years. There was no concept of efficiency or productivity. Also there was no wage for that matter. One hunted in the jungles, if lucky got some food for the day. if not then tried another day. Similarly,  the farmer labored in the field throughout the year to produce the food he wanted. There was no connection between the produce and the time and effort put into the process. No one ever asked a farmer how much time it took to produce a bag of wheat.

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October 24, 2009

Democratizing Analytics - Is it possible?

A lot has been said & written about sustainable competitive advantage that could be gained by organizations by leveraging analytics. While large organizations might have the wherewithal to put in place a robust data & analytic infrastructure, attract talent to leverage their data & analytic stack, most small & medium enterprises would be lucky to have just clean data.

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What is Analytics?

Analytics, though a (relatively) recently coined term, is said & understood to mean so many different things.

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