By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData Collective
  • Analytics
    AnalyticsShow More
    predictive analytics in dropshipping
    Predictive Analytics Helps New Dropshipping Businesses Thrive
    12 Min Read
    data-driven approach in healthcare
    The Importance of Data-Driven Approaches to Improving Healthcare in Rural Areas
    6 Min Read
    analytics for tax compliance
    Analytics Changes the Calculus of Business Tax Compliance
    8 Min Read
    big data analytics in gaming
    The Role of Big Data Analytics in Gaming
    10 Min Read
    analyst,women,looking,at,kpi,data,on,computer,screen
    Promising Benefits of Predictive Analytics in Asset Management
    11 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: #8: Here’s a thought…
Share
Notification Show More
Latest News
ai software development
Key Strategies to Develop AI Software Cost-Effectively
Artificial Intelligence
ai in omnichannel marketing
AI is Driving Huge Changes in Omnichannel Marketing
Artificial Intelligence
ai for small business tax planning
Maximize Tax Deductions as a Business Owner with AI
Artificial Intelligence
ai in marketing with 3D rendering
Marketers Use AI to Take Advantage of 3D Rendering
Artificial Intelligence
How Big Data Is Transforming the Maritime Industry
How Big Data Is Transforming the Maritime Industry
Big Data
Aa
SmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > #8: Here’s a thought…
Uncategorized

#8: Here’s a thought…

brianfarnan1
Last updated: 2009/05/04 at 4:09 AM
brianfarnan1
8 Min Read
SHARE

An occasional series in which a review of recent posts on SmartData Collective reveals the following nuggets:

There’s more to analytics than…
Although understanding data and developing statistical models is certainly an important component of an analytic project, this is just one aspect of analytics. This aspect includes cleaning data, enriching data, exploring data, developing features, building models, validating models, and iterating the process. From a broad perspective, this is a process in which the input is data and the output is a statistical model. When most people think of modeling, this is what they think of. For many analytic projects, this is just a small part of what is required for a successful engagement.

—Robert Grossman: “In Analytics, It’s the Actions that Matter”

A missing link
Most organizations today do not track who is critical, who will likely leave, or why they will leave, so there’s no opportunity to develop effective strategies to retain critical employees. Workforce analytics is the missing link in today’s business strategy. It is imperative for organizations to know how to attract, grow and retain these employees, as well as sustain the already seasoned pro…


An occasional series in which a review of recent posts on SmartData Collective reveals the following nuggets:

More Read

HR Processes

Understanding The Role of Big Data in HR Processes and Payroll

5 Ways to Improve Organizational Learning with Big Data Analytics
Analytics: Not About Saving Time
The First Step in Moving from Metrics to Workforce Analytics
Where to Begin with Workforce Analytics: The Key Three

There’s more to analytics than…
Although understanding data and developing statistical models is certainly an important component of an analytic project, this is just one aspect of analytics. This aspect includes cleaning data, enriching data, exploring data, developing features, building models, validating models, and iterating the process. From a broad perspective, this is a process in which the input is data and the output is a statistical model. When most people think of modeling, this is what they think of. For many analytic projects, this is just a small part of what is required for a successful engagement.

—Robert Grossman: “In Analytics, It’s the Actions that Matter”

A missing link
Most organizations today do not track who is critical, who will likely leave, or why they will leave, so there’s no opportunity to develop effective strategies to retain critical employees. Workforce analytics is the missing link in today’s business strategy. It is imperative for organizations to know how to attract, grow and retain these employees, as well as sustain the already seasoned professionals that bring depth and value to the organization..

— Romankanta Irungbam: “Workforce Analytics”

An organization within an organization
My concerns about IT’s role relate to the situation that I see in some companies where IT is a department set apart, rather than being a central part of the overall business. In this type of circumstance (which is perhaps more common than anyone would like to think), the success of the IT and the non-IT parts of the business are decoupled. Under these arrangements, it would be feasible for IT to be successful and the business to suffer major losses, or for the business to post record profits while IT fails to deliver projects. Of course, such decoupling can happen in other areas; for example Product A could have a stellar year, while Product B fails miserably – the same could happen with countries or regions. However, there is something else here, a sense that IT can sometimes be an organization within an organization, in a way that other service departments generally are not.

—Peter Thomas: “The scope of IT’s responsibility when businesses go back”

Offshoring: time to reconsider
At the least, the past five years of offshoring have proven that the logic of the business case depends as much on what one leaves out as on the numbers assigned. The process of globalization will continue to amaze, frustrate, and surprise, despite the best predictions of smart people. Unexpected consequences, for both good and ill, will continue to challenge firms — and individuals — on all sides of the equation.

—John Jordan: “Early Indications April 2009: Re-examining Offshoring”

Finding out why they’re really unhappy
Search Engines are fundamentally top-down in that you know what you are looking for when launching a query. However, Text Analytics is bottom-up, uncovering hidden patterns, relationships and trends locked in unstructured data – including call center notes, open-ended survey responses, blogs and social networks. Now businesses have a way of pulling key concepts and extracting customer sentiments, such as emotional responses, preferences and opinions, and grouping them into categories. For instance, a call center manager will have a hard time extracting why customers are unhappy and churn by using a search engine for millions of call center notes. What would be the query? But, by using Text Analytics, that same call center agent will discover the main reasons why customers are unhappy, and be able to predict if they are going to churn.

—Ajay Ohri: “Interview: SPSS’s Olivier Jouve”

Creating an entrepreneurial environment
While Fortune 500 companies are attempting to integrate the practice of corporate entrepreneurship, I believe it limits the art/science of discovery. I believe that corporations must truly start to allow the entrepreneurial mindset to take shape and flourish. The corporate culture must adopt an environment that allows its people (regardless of rank / title) to propel innovation and initiative. Everyone has something to offer, if giving the opportunity.

—Tom H.C. Anderson: “Glenn Llopis and Tom H. C. Anderson Discuss Earning Serendipity and Social Media Marketing”

Don’t forget manual review and correction
An obsessive-compulsive quest to find and fix every data quality problem is a laudable but ultimately unachievable pursuit (even for expert “lake cleaners”). Data quality problems can be very insidious and even the best “lake cleaning” process will still produce exceptions. Your process should be designed to identify and report exceptions when they occur. In fact, as a best practice, you should also include the ability to suspend incoming data that contain exceptions for manual review and correction.

—Jim Harris: “Hyperactive Data Quality”

TAGGED: offshoring, workforce analytics
brianfarnan1 May 4, 2009
Share this Article
Facebook Twitter Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

ai software development
Key Strategies to Develop AI Software Cost-Effectively
Artificial Intelligence
ai in omnichannel marketing
AI is Driving Huge Changes in Omnichannel Marketing
Artificial Intelligence
ai for small business tax planning
Maximize Tax Deductions as a Business Owner with AI
Artificial Intelligence
ai in marketing with 3D rendering
Marketers Use AI to Take Advantage of 3D Rendering
Artificial Intelligence

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

HR Processes
AnalyticsBig DataWorkforce Data

Understanding The Role of Big Data in HR Processes and Payroll

7 Min Read
big data analytics
AnalyticsWorkforce Analytics

5 Ways to Improve Organizational Learning with Big Data Analytics

7 Min Read

Analytics: Not About Saving Time

7 Min Read

The First Step in Moving from Metrics to Workforce Analytics

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US

© 2008-23 SmartData Collective. All Rights Reserved.

Removed from reading list

Undo
Go to mobile version
Welcome Back!

Sign in to your account

Lost your password?