There is a great deal of hype regarding AI, some is justified and some not so much. Pundits, including this one talk about the value an organization will get and, in some cases, immediately. But what is the actual measurable value a firm can realistically expect?
I recently used a free AI Value Calculator, asking how an oil refinery could become more effective and safer. The following response was received:
“**Value Proposition:** At [Your Company Name], we understand that oil companies face increasing pressure to enhance safety and efficiency within refinery operations. Our innovative solutions are designed specifically to address the unique challenges of the refining industry. By integrating advanced technology and safety protocols, we empower your team to operate more effectively while minimizing risks. With our expertise, you can expect: – **Increased Operational Efficiency:** Streamline processes with cutting-edge tools that boost productivity and reduce downtime. – **Enhanced Safety Measures:** Implement systems that prioritize employee safety and ensure compliance with industry regulations. – **Real-Time Monitoring:** Gain insights through data analytics that allow for proactive decision-making and immediate response to potential hazards. Choose [Your Company Name] as your partner in revolutionizing refinery operations, ensuring you meet both efficiency goals and safety standards. Together, we can create not just a safer workplace, but also a more effective refinery that drives success in today’s competitive landscape. For more information or to schedule a consultation, please contact us at [phone number] or visit our website at [website URL]. Let’s work together to pave the way for a more secure and productive refining environment.”
The Problem with Value
There are several problems with this response, and I (the user) am part of that problem.
- My prompts were minimal and not specific
- The response was pablum, as it did not tell me anything I did not already know.
- What do phrases like, “Implement systems that prioritize employee safety and ensure compliance with industry regulations,” actually mean and how do I accomplish that?
- What do I tell the “C” level executive that she can expect to see on our bottom line as a result of this expenditure and what is the risk profile?
Determining the economic value proposition for any capital investment project has always been a challenge and is difficult to accomplish, especially when the list of intangibles is long. The recent issues surrounding Cracker Barrel rebranding is a case in point.
The process of assessing possible value and the associated risk of attaining said value from investments is not trivial. It takes a lot of thinking and iterative re-thinking from a knowledgeable and qualified team, as well as input from others. And in my opinion, there has to be a dollar value that can be documented and defended–meaning, it is a solid assessment and not wishful thinking.
The Journey to Measurable Value
“If you don’t know where you are going, you’ll end up someplace else.”― Yogi Berra
We been conducting economic and financial assessments of capital projects for over two decades. Our Economic Value Proposition Matrix (EVPM) has been developed and curated with organizations in the Critical Infrastructure Sector. It meets and exceeds the tough requirements of some of the most prestegious global firm and has demonstrated its ability to provide decision makers with an economic and financial “What If” and “Iterative” model of proposed spend before a dime is committed to the project. We love tough questions and have learned most that are used. Moreover, it Risk Assessment section if one of the most robust available.
It is being used for AI Spend assessments and a case study will be available in our forthcoming book, from CRC Press, The Transformation of Our Spreadsheet Society: Moving Towards a Nonlinear, Big Data Enabled AI Environment, to be released by early 2026.
Is AI Different Than Other Capital Expenditures (CAPEX)?
The traditional response from IT providers is, It Depends! In some ways this is a correct statement. However, industry/individual organizations have been through existential difficulties before and frequently.
Most IT CAPEX is either Science/Engineering or transactional, i.e., ERP. However, much of AI centers on behavior and therefore, involve an addition dimension–latent variables. We have been interested in latent variables since the early 1990s and first published our approach towards learning about their impact on behavioral systems in my 1996 doctoral dissertation, Cross-cultural negotiations between Japanese and American businessmen: A systems analysis (exploratory study).
In our forthcoming book by CRC Press, The Transformation of Our Spreadsheet Society: Moving Towards a Nonlinear, Big Data Enabled AI Environment, we develop a detail approach and representative AI model about the value that can be identified and measured using latent variable.
So, what is a latent variable? Largely unknown, these variables are essential in the complex data analysis and modeling needed in statistics, machine learning, and other scientific assessments.
Very important–They cannot be measured directly but can be inferred from other measurable variables.
This is a major and usually unrecognized problem when attempting to place an economic value on a project yet to start, i.e., the planning and funding stage.
Our upgraded EVPM model takes latent variables into consideration giving management greater insight into the costs, return and ultimate value of AI investments. We believe that unless this dimension is properly assessed, calculated values are WRONG and will not result in the value proponent’s advance.
Look for further details regarding our economic value of AI model and feel free to contact us if you have specific needs or questions.
