Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Predictive Analytics Q&A with Tom Davenport
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Culture/Leadership > Predictive Analytics Q&A with Tom Davenport
AnalyticsBusiness IntelligenceCulture/Leadership

Predictive Analytics Q&A with Tom Davenport

Brett Stupakevich
Brett Stupakevich
0 Min Read
SHARE

Tom Davenport Predictive Analytics1 photo (predictive analytics)Tom Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College, the co-founder and research director of the International Institute for Analytics, and a Senior Advisor to Deloitte Analytics. He has published widely on the topics of analytics in business, process management, information and knowledge management, and enterprise systems. His most recent book is Analytics at Work: Smarter Decisions, Better Results, with Jeanne Harris and Bob Morison. He wrote or edited twelve other books, and has written over 100 articles for such publications as Harvard Business Review, Sloan Management Review, the Financial Times, and many other publications.

Q – What will facilitate the greater adoption of analytics?  Improving analysis skills, easier to use analytics tools, awareness of the value of analytics, availability of data?

A – All of the above, I think. Right now the two fastest-moving drivers are the greater availability of data and the “marketing” of analytics by researchers and writers like me, and vendors alike. And I expect that both of these drivers, and the other two as well, have a long way to run.

Q – “Gut feelings” are still widely trusted in organizations everywhere. How do you marry “gut feelings” with “analytics-driven” decision making?

A – The two modes of deciding are not quite as alien from each other as many people think. First, even the most scientifically and quantitatively-focused analyst knows that an intuition about what’s going on in your data—we call it a hypothesis—can be a very helpful guide to understanding and modeling it. Of course it’s important to still test your hypothesis to see if it’s valid. And intuitive decision makers who have a lot of experience are actually letting their brains analyze a lot of data. If you don’t have much experience in a particular decision domain, you should treat your gut as the last resort.

Q – It’s believed by some that predictive analytics is only available to the largest, most sophisticated organizations. Do you believe that’s true and if so what will make it more accessible to a wider range of organizations?

A – No, I think that predictive and prescriptive analytics (the latter refers to optimization and randomized testing) can be done by any organization. Almost every company has some data that can be analyzed. The software is getting cheaper all the time, and there are even open-source options that are free. So the only real limiting factor is awareness of what’s possible and the skill to pull it off. Even that is more accessible through on- and off-shore outsourcing.

Q – How can organizations improve decisions? Will the move toward self-service, more collaborative and social tendencies of today’s analytics teams and technologies improve the decision-making process? 

A – This is the key question and what analytics are intended to do. They are one tool for that purpose. But there are a lot more. Another, as you suggest, is getting more input and participation in decision processes through the use of technology—social media, prediction markets, and so forth. Another is to take the learning from recent advances in behavioral economics and neuroscience, and embed them in our decision processes. In effect, we have both the need and the opportunity to reengineer our decisions. I’m not sure we have the will yet, however.

Q – What are your predictions for the future of business decision making?  What do you predict will happen to the industry in the next five-10 years?

That’s an interesting way of putting the question. I don’t think it’s really an “industry” yet. There are a few assorted toolkits. I think in the future we will try to connect the tools much more closely to the decision being made. We’ll have thousands of “analytical apps” to choose from, and each one will guide a decision maker through the process of making an effective quantitative decision. There won’t be the need to know what all the tools can do or where all the data is; all you’ll have to know is what decision you need to make, and the rest will be structured for you. Maybe we’ll even have software that keeps track of all the decisions an organization needs to make, who makes them, and what process they used to make them. This would be possible today, but again, I’m not sure that most executives are ready for that level of accountability. But the organizations that adopt such tools will simply make better decisions than those that don’t.

 

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive
image fx (71)
The Power of AI for Personalization in Email
Artificial Intelligence Exclusive Marketing
image fx (67)
Improving LinkedIn Ad Strategies with Data Analytics
Analytics Big Data Exclusive Software
big data and remote work
Data Helps Speech-Language Pathologists Deliver Better Results
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

How to Become a Data Analyst

4 Min Read
business development data
Big DataBusiness Intelligence

The Real Role of Big Data In Business Development

5 Min Read
data analytics in healthcare
Analytics

EKU Notes Data Analytics Is Crucial For Health Awareness For Businesses

9 Min Read

When improbable events are expected

5 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
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?