We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
    cybersecurity efforts
    How Behavioral Analytics and AI Are Redefining Cybersecurity for Boca Raton Businesses
    14 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Some Thoughts on the Levels of Automation of a Decision
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 > Business Rules > Some Thoughts on the Levels of Automation of a Decision
Business RulesData MiningDecision ManagementPredictive Analytics

Some Thoughts on the Levels of Automation of a Decision

JamesTaylor
JamesTaylor
5 Min Read
Some Thoughts on the Levels of Automation of a Decision
Illustrative image generated with OpenAI gpt-image-1.
SHARE

A recent post on the IBM Good Decisions Blog – When Should You Automate a Business Decision? contains a list of ten levels of automation from a paper by Parasuraman, Sheridan and Wickens (available to IEEE members here). This set of 10 levels runs from 1 (computer offers no assistance) to 10 (computer acts autonomously).

The best thing about this list is that it makes it clear how important it is to identify the list of possible decision alternatives before deciding on the amount of automation. The number of people who get in trouble with data mining/predictive analytics and business rules because they don’t fully understand the decisions involved and the possible decision actions is high. As I describe in Chapter 5 of the new book (Decision Management Systems) you need to understand and decompose your decisions into their component parts and make sure you understand the possible actions out of each component decision during the decision discovery phase and before you start writing rules or building analytic models.

I also liked that the list shows that automation can be increased from presentation of options to narrowing of options to taking action on your behalf. Too many projects think this is a black and white choice – manual or automated? In fact the use of Decision Management Systems to narrow the available options to a reasonable or allowed set is a common use case. Particularly when combined with some intelligent presentation of information to the user (so that they can make a good selection from the remaining alternatives) these kinds of systems can be very powerful.

I do have two comments / criticisms.

More Read

Hadoop in Advertising & Media: Is Data Analytics Making Old Media New?
Why Business Needs Public Data
Open Ocean
Signals sinchronizer and its role in automated perceptural voice quality testing
Big Data in the Sports Industry
  • First there was no variation based on the role of the computer in supporting the decision-making of a human.
    The focus of the levels was on how the computer restricts the list of alternatives, how it selects from that list and how it interacts with the human around that selection. While this is a key element of a decision-making system the way in which the computer supports the human decision-maker is also important. Between level 1 (computer does nothing) and level 2 (computer offers complete set of decision alternatives) one could make a compelling case for a system that makes no attempt to make the decision but presents the information the human will need to make a decision. Given how widespread this kind of decision support system is I was struck by its absence. At other levels too it seemed to me that there was a need to differentiate between systems based on how they present information to help the human actor.
  • Second the automation and number of selections were too tied
    There is no differentiation between the behavior of the system in terms of acting automatically, asking for permission or giving an option to veto until the decision alternatives have been reduced to one. I come across many systems where the system has identified multiple alternatives, with one favorite. These systems vary from all options being presented with the systems preference identified, to those where the alternatives are presented but it is clear the system will act on its preferred unless stopped to those where the preferred option is taken but the user has the option to override it after the fact (for a while at least) by selecting an alternative from the list.

What did you think of the list? Would love to hear some other opinions.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

The New Zlibrary Official Domain Makes The Website Address Different -- AI-generated illustration
How Search Engine Indexing Lags Behind Large-Scale Website Domain Migrations
News
How Great Content Moves Through A Marketing Ecosystem -- AI-generated illustration
How Great Content Moves Through A Marketing Ecosystem
Exclusive Infographic Marketing
What Your Brand Misses That Data Reveals -- AI-generated illustration
What Your Brand Misses That Data Reveals
Big Data Exclusive Infographic
5 Common Mistakes Businesses Make During the Risk Assessment Process -- AI-generated illustration
5 Common Mistakes Businesses Make During the Risk Assessment Process
Business Intelligence Exclusive Risk Management

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Gain a 360-Degree Customer View with Data Analytics
AnalyticsCRMData Mining

Gain a 360-Degree Customer View with Data Analytics

0 Min Read

Have Marketers Taken Big Data Too Far?

4 Min Read
Workforce Analytics
Predictive Analytics

Workforce Analytics

5 Min Read

Revealing Human Nature through Social Media Measurement

3 Min Read

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

Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?