The evolution of information technology has dramatically transformed business decision-making. From the early days of electronic calculators and mainframes to today’s powerful enterprise-wide systems, technology has automated many critical business decisions and processes. Initially, data was seen as a mere byproduct of automation, but it quickly became a vital resource. Indeed, most companies today use data-driven business intelligence (BI) reporting to streamline decision-making. Moreover with the advent of robotics and artificial intelligence (AI), the business landscape is rapidly changing. This includes AI tools to enhance human decision-making to fully autonomous operations like smart robots and self-driving vehicles.

This article is an introduction to the challenges that humans and various forms of information technologies face when making business decisions. Moreover, I’ll identify for you the unique advantages each type of information technology has when it comes to organizational decision-making. Further, I’ll identify the many challenges both humans and these information technologies have in the realm of decision-making. So, let’s look at the impactful roles of process automation, data-driven decisions, and how AI is influencing business decision-making.

“Automation does not need to be our enemy. I think machines can make life easier for men, if men do not let the machines dominate them.”

John F. Kennedy

1. The Problem-Solving Process: Humans Make Mistakes And Need Tech To Make Better Business Decisions

Decision-making is as old as mankind. To understand Artificial Intelligence’s (AI) impact on decision-making, let’s first start with the basic steps of human problem solving and its challenges. Below are the four basic steps any human goes through to solve a problem.

4-Step Problem-Solving Process for Humans

• Define The Problem
• Formulate Alternative Solutions
• Evaluate and Select An Alternative
• Implement And Follow Up On The Solution.

At least for most business professionals, problem-solving is a critical skill that they practice every day. For a more detailed discussion on the basic problem solving process, click here.

Now, the fundamental problem with human decision-making is that we make mistakes. To list, key human decision-making challenges include

Human Decision-Making Challenges

The Problem-Solving Process: Humans Make Mistakes And Need Tech To Make Better Decisions

• Biases that Distort Information.
• Emotions that Lead to Faulty Decisions.
• Human Errors Make for Sub Par Decisions.
• Fatigue and Distractions Impair Decision-Making.
• Information Processing Limits Result in Cognitive Overload.

For a more detailed discussion on the human decision-making process, see my article, The Problem-Solving Process: Humans Make Mistakes and Need Tech to Make Better Decisions.

So, to varying degrees, all of us have these human weaknesses when it comes to decision-making. This is where automation and technology helps to shore up our weaknesses. Subsequently, the rest of this series will explore the opportunities and the challenges we have with using information technology in decision-making. Specifically, this includes process automation, data-driven decision-making, and lastly, AI’s impact on business decisions. See below.

2. Process Automation Technology: Its Value To Best Empower Decision Making In The Age Of AI.

Process Automation Technology: Its Value To Best Empower Decision Making In The Age Of AI.

Before AI, businesses used and continue to use traditional automation technology. Without a doubt, traditional process-based automation provides much value to business decision-making. However, it does have major limitations. See below. 

Major Limitations of Process Automation

• Constraints Of Rule-Based Systems.
• Not Adaptable to Changing Environments.
• Cannot Support Complex Decision-Making Situations.
• Not Able To Deal With Ambiguity and Uncertainty.
• Limited Capability To Collaborate With Humans.
• Not Suited For Large Data Sets.

For decades, businesses have used rules-based process automation to automate manual tasks and assist with decision-making. Now in this age of AI and data overload, our business environments are becoming increasingly complex. At the same time, AI is not the solution to every problem. Indeed, traditional process automation still has its place to support business decision-making. For a more detailed discussion on process automation use cases and its limitations, click here

3. Data-Driven Decision-Making: Its Enormous Impact And The Truth On Limitations

The explosion of big data has provided businesses with unprecedented access to vast amounts of information that they can use for decision-making purposes. Moreover, a new scientific discipline called Data Science has emerged. This discipline is singularly focused on making data useful by placing advanced analytics tools and methods in the hands of organizations. Now, we can analyze both structured and unstructured data from various sources to identify patterns and trends. Indeed, these correlations and resulting insights were in many cases previously undiscoverable. 

Further, data-driven decision-making capabilities enable businesses to respond more accurately and quickly to market changes, customer preferences, competitor activities, and other external factors. On the other hand, there are limitations with a data-driven approach. These include:

Data-Driven Decision-Making: Its Enormous Impact And The Truth On Limitations

Challenges With Data-Driven Decision-Making

• Over Reliance on Summary Data that Can Obscure Insights
• Bias Is Still Present Or Even Elevated
• Using an Application-Centric Approach that Treats Data as a By-Product

Click here to read my article where I examine the impact and limitations of data-driven decision-making. Specifically, this article will touch on data science basics, describe the data-driven decision-making process, its benefits, and its challenges for improving business decision-making in the age of AI.

4. AI Impact On Business Decisions – Know How To Best Apply To Get The Most Benefits

AI Impact On Business Decisions – Know How To Best Apply To Get The Most Benefits

Undoubtedly, AI stands out from other automation forms due to its ability to facilitate decision-making in highly complex environments. Businesses are increasingly harnessing AI for a variety of decision-making situations, reaping significant benefits in the process. Recent advancements in Large Language Models (LLM) and more generalized AI have expanded AI’s potential in augmenting business decision-making beyond traditional automation capabilities. Furthermore, AI, when combined with robotics, can operate autonomously in both decision-making and physical tasks.

So AI increasingly can replace or enhance both human and lower forms of automation to automate, augment, or support decision-making. Additionally, it can do this in use cases that are simple, complex, and even chaotic. So click here to find out how businesses can leverage AI to support organizational decision-making. And most importantly, use better decision-making to improve business execution.

5. AI Impact On Business Decisions – Know AI’s Unique Challenge To Overcome Its High Number Of Weaknesses

AI Impact On Business Decisions – Know AI’s Unique Challenge To Overcome Its High Number Of Weaknesses

However, AI still has many weaknesses when it comes to supporting business decision-making. Specifically, AI challenges include its lack of transparency, it can be biased, uses a lot of computing power, privacy concerns, and it is not morally responsible to name a few.  In spite of AI decision support being a unique challenge to overcome, it is definitely worth pursuing. At the same time it is critical that you know the weakness of AI in supporting decision-making, Click here to explore the 11 weaknesses in AI with providing automation support for business decision-making.

“The real danger is not that computers will begin to think like men, but that men will begin to think like computers.”

Sydney J. Harris

For more on our Series on AI Impact On Business Decisions, see links below:

• The Human Problem-Solving Process – Part 1
• Process Automation – Part 2
• Data-Driven Decision-Making – Part 3
• AI Impact on Business Decisions – Opportunities – Part 4
• AI Impact on Business Decisions – Limitations – Part 5

If you are in the supply chain industry and have a need to supercharge your decision-making cycles, please contact me to discuss next steps. I’m Randy McClure, and I’ve spent many years solving data analytics and decision support problems. As a supply chain tech advisor, I’ve implemented hundreds of successful projects across all transportation modes, working with the data of thousands of shippers, carriers, and 3rd party logistics (3PL) providers. I specialize in proof-of-concept and pilot projects for emerging technologies. To reach me, click here to access my contact form or you can find me on LinkedIn.

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