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
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    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
  • 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

Big Data and Business Intuition Work Together
Big Data and Business Intuition Work Together
Analytics and the myth of the aha moment
How Data Analytics Can Help You Grow Your Business
Business Intelligence: Decisions, Decisions
Starting Your Business: Data From the Ground Up
  • 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

Flat editorial illustration: The article's core relationship is workload-by-workload decision-making for cloud migration, where s
Which Workloads Should Move to the Cloud?
Cloud Computing Exclusive IT
Flat editorial illustration: The article positions data governance as a strategic board-level concern rather than a purely techni
Why Data Governance Is Becoming a Board-Level Business Priority
Big Data Exclusive Policy and Governance
Flat editorial illustration: The article argues that data annotation quality should be measured by inspectable gold sets, written
The Top Data Annotation Companies Are Separated by Proof of Quality, Not Headcount
Big Data Exclusive
Flat editorial illustration: The article's core relationship is the gap between raw bank-feed records and reliable subscription i
Subscription Trackers Have a Transaction Data Problem
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Freakonomics and Your Data
AnalyticsCloud ComputingData MiningData QualityKnowledge ManagementStatistics

Freakonomics and Your Data

6 Min Read
PMML support is growing rapidly. From down under and into the stars!
Business IntelligenceData MiningPredictive Analytics

PMML support is growing rapidly. From down under and into the stars!

5 Min Read
Planning for ROI in Text Analytics
AnalyticsData MiningStatisticsText Analytics

Planning for ROI in Text Analytics

6 Min Read
Mash Your Future with Augmented Reality
Business IntelligenceCRMData Mining

Mash Your Future with Augmented Reality

2 Min Read

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

5 Great Tips for Using Data Analytics for Website UX
5 Great Tips for Using Data Analytics for Website UX
Big Data
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

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?