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
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    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
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Common Misconceptions on Automating Decisions
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 > Common Misconceptions on Automating Decisions
Business IntelligenceDecision Management

Common Misconceptions on Automating Decisions

JamesTaylor
JamesTaylor
6 Min Read
SHARE

Regular readers of my blog (as well as those who hear me speak and our Decision Management clients) know that I talk alot about automating decisions. Really, a lot. The evidence that taking control of decisions, specifically operational decisions, and developing Decision Management Systems to automate and manage those decisions drives improved organizational effectiveness is extremely compelling.

Regular readers of my blog (as well as those who hear me speak and our Decision Management clients) know that I talk alot about automating decisions. Really, a lot. The evidence that taking control of decisions, specifically operational decisions, and developing Decision Management Systems to automate and manage those decisions drives improved organizational effectiveness is extremely compelling. The stories in my book, the stories I discuss in my presentations, and the stories you hear from vendors in this space are of increased agility, decreased costs, increased profit and decreased fraud. Decision Management and Decision Management Systems work.

HALDespite these proof points I still get some push back. For too long the association many business people have is that something automated will be inflexible, costly, hard to adopt and one-size-doesn’t-really-fit-anyone. They worry that completely automating decisions will require compromises in accuracy and devalues their staff. They associate automated decision with some kind of big black box that issues decisions that must be obeyed – something like Hal from 2001 but with less humanity. Which brings us to the misconceptions

  1. Decision Management Systems are just like other systems
    Decision Management Systems are not systems of record and are not responsible for the workflow, the process, of your business. They just make decisions. This alone would make them different from the systems that store and manage the data that your business relies on but they are also built differently:
    • They are agile, built using a business rules foundation to make sure that they way they work is transparent and can easily be changed when necessary, often by non-technical people on the business side of the house who understand when such changes are required.
    • They are analytic, using analytics not as a way to report progress or analyze results but as a driver of accurate, precisely targeted behavior.
    • They are adaptive, learning from what works and supporting their users as they experiment and learn themselves.
  2. Automating a decision means automating it 100% of the time
    Some Decision Management Systems do automate a decision 100% of the time, handling the decision every time it is required. This is particularly true when the channel that requires decisions is completely automated such as a web channel or a kiosk. Clearly in those circumstances only 100% automation makes sense. But in many other scenarios automating a decision means handling 80% or 90% (or even 95%) of transactions while referring the rest to a human decision maker (with some explanation of why each is being referred). This latter kind of system is much more common and has the added advantage that you can start simple, handling perhaps the easiest 50% of the transactions, and gradually adapt the system to handle a higher percentage over time. Business rules management systems enable this kind of iterative development and its very effective in Decision Management because the overall system already knows how to handle the manual decisions.
  3. Tutorial4FinalDiagramAutomating a decision means automating 100% of the decision
    Similarly some Decision Management Systems do make 100% of the decision – the process reaches the point where a decision is required, the Decision Management System makes the whole decision, and the process continues. In many other situations, though, the system makes only part of the decision. one of the reasons I really like Decision Modeling is that it allows you to take a high level decision (where automation might be impractical or heavily resisted) and break it down in its component pieces. Some of these will lend themselves to automation with business rules, others might be clearly handled using an analytic model. Others may require human judgment. With such a model in hand it is possible to determine the boundaries of your automated decision. It even allows you to define how a largely automated decision might require human judgment at times.

apple orangeI would also point out that many automated decisions are neither 100% of decisions NOR 100% of each decision. Such systems are not pure Decision Management Systems nor are they pure Decision Support Systems – they are a bit of a blend. Nevertheless they can be very effective.

More Read

Winter of 1933 and a Story About My Second Favorite Carpenter in History
Dashboards and Scorecards, similarities and differences
Decision Management and Insurance – Business Optimization and Governance
Help Desk – A User’s Guide to Analytics-based Performance Management
The Ultimate Guide to Building a Smart Office

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

sales and data analytics
How Data Analytics Improves Lead Management and Sales Results
Analytics Big Data Exclusive
ai in marketing
How AI and Smart Platforms Improve Email Marketing
Artificial Intelligence Exclusive Marketing
AI Document Verification for Legal Firms: Importance & Top Tools
AI Document Verification for Legal Firms: Importance & Top Tools
Artificial Intelligence Exclusive
AI supply chain
AI Tools Are Strengthening Global Supply Chains
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Data Mining Combined With Predictive Modeling Equal 3D Data Visualization

3 Min Read

Announcing: JuiceKit SDK Open Source

5 Min Read

Financial Services Analysis For Free

2 Min Read

Happy New Year: What’s Ahead for the Semantic Web (Part 2)

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.

AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
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?