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
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    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
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Data versus Expertise Dilemma
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > Decision Management > Data versus Expertise Dilemma
AnalyticsBusiness IntelligenceDecision ManagementKnowledge Management

Data versus Expertise Dilemma

CMatignon
CMatignon
5 Min Read
SHARE

balanceIn the decade (or two) I have spent in Decision Management, and Artificial Intelligence at large, I have seen first-hand the war raging between knowledge engineers and data scientists.  Each defending its approach to supporting ultimately better decisions.  So what is more valuable

balanceIn the decade (or two) I have spent in Decision Management, and Artificial Intelligence at large, I have seen first-hand the war raging between knowledge engineers and data scientists.  Each defending its approach to supporting ultimately better decisions.  So what is more valuable?  Insight from data?  Or knowledge from the expert?

Mike Loukides wrote a fantastic article called “The unreasonable necessity of subject experts“ on the O’Reilly radar, that illustrates this point very well and provides a clear picture as to why and how we would want both.

Data knows stuff that experts don’t

In the world of uncertainty that surrounds us, experts can’t compete with the sophisticated algorithms we have refined over the years.  Their computational capabilities goes way above and beyond the ability of the human brain.  Algorithms can crunch data in relatively little time and uncover correlations that did not suspect.

Adding to Mike’s numerous example, the typical diaper shopping use case comes to mind.  Retail transaction analysis uncovered that buyers of diapers at night were very likely to buy beer as well.  The rationale is that husbands help the new mom with shopping, when diapers run low at the most inconvenient time of the day: inevitably at night.  The new dad wandering in the grocery store at night ends up getting “his” own supplies: beer.

Mike warns against the pitfalls of data preparation.  A hidden bias can surface in a big way in data samples, whether it over-emphasizes some trends or cleans up traces of unwanted behavior.  If your data is not clean and unbiased, value of the data insight becomes doubtful.  Skilled data scientists work hard to remove as much bias as they can from the data sample they work on, uncovering valuable correlations.

 Data knows too much?

When algorithms find expected correlations, like Mike’s example of pregnant women being interested in baby products, analytics can validate intuition and confirm fact we knew.

When algorithms find unexpected correlations, things become interesting!  With insight that is “not so obvious”, you are at an advantage to market more targeted messages.  Marketing campaigns can yield much better results than “shooting darts in the dark”.

Mike raises an important set of issues: Can we trust the correlation?  How to interpret the correlation?

Mike’s article includes many more examples.  There are tons of football statistics that we smile about during the Super Bowl.  Business Insider posted some even more incredible examples such as:

  • People who dislike licorice are more likely to understand HTML
  • People who like scooped ice cream are more likely to enjoy roller coasters than those that prefer soft serve ice cream
  • People who have never ridden a motorcycle are less likely to be multilingual
  • People who can’t type without looking at the keyboard are more likely to prefer thin-crust pizza to deep-dish

There may be some interesting tidbit of insight in there that you could leverage.  but unless you *understand* the correlation, you may be misled by your data and make some premature conclusions.

Expert shines at understanding

Mike makes a compelling argument that the role of the expert is to interpret the data insight and sort through the red herrings.

This illustrates very well what we have seen in the Decision Management industry with the increased interplay between the “factual” insight and the “logic” that leverages that insight.  Capturing expert-driven business rules is a good thing.  Extracting data insight is a good thing.  But the real value is in combining them.  I think the interplay is much more intimate than purely throwing the insight on the other side of the fence.  You need to ask the right questions as you are building your decisioning logic, and use the available data samples to infer, validate or refine your assumptions.

As Mike concludes, the value resides in the conversation that is raised by experts on top of data.  Being able to bring those to light, and enable further conversations, is how we will be able to understand and improve our systems.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

AI supply chain
AI Tools Are Strengthening Global Supply Chains
Artificial Intelligence Exclusive
data analytics and truck accident claims
How Data Analytics Reduces Truck Accidents and Speeds Up Claims
Analytics Big Data Exclusive
predictive analytics for interior designers
Interior Designers Boost Profits with Predictive Analytics
Analytics Exclusive Predictive Analytics
big data and cybercrime
Stopping Lateral Movement in a Data-Heavy, Edge-First World
Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Fake News
Artificial IntelligenceBig Data

Big Data is Leading the Fight Against Fake News

5 Min Read

German-Speaking Business Managers in Europe Need More Flexible, Self-Service BI

2 Min Read

Is Twitter Killing Blogging?

5 Min Read

Why Are Mid-Market Companies Waiting to Embrace Big Data?

7 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 chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

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?