“How could Artificial Intelligence improve this business decision-making system?”
Welcome back! We will take the decision-making system from my previous blog, place it in an app so we may use it on-demand with no loss of detail, and apply artificial intelligence (A/I) that would enhance this app.
“Will our company structure support our projected growth?”
Step One: State the Decision
App: The app asks us to type or dictate our decision. Then it challenges us, using several methodologies, to refine our wording. We are also asked to confirm our understand the root cause for the pending decision.
A/I: Using language analysis, the A/I app detects ambiguity in your verbiage and suggests several alternative statements. It also recognizes the lack of an alternative option and suggests the following:
A/I App Result: “We must decide whether to combine the product line management, marketing, and sales teams into one Business Development function.”
Step Two: Frame the Decision
App: After we initially identified our frames, the app “walks” us from frame to frame, facilitating our consideration of each company function in this case. Interface design makes this analogy real as we look through actual graphic, labeled window frames.
A/I: The engine researches our frames and proactively lists key major and granular components of each business function. Now we don’t just think through each frame, we are prompted to do a “deeper dive” into each function. Remember, a Google engineer recently revealed their A/I systems are sentient. 1
A/I App Result: “How we would communicate this reorganization will impact the success, so human resources and a personal touch must mediate the sensitivity of the initial impact. We also must educate the organization regarding the three-legged-stool Business Development synergy that will result.”
Step Three: List the Alternatives
App: The app gives us fields to enter our alternatives, reminding us to be exhaustive so all possibilities are recognized.
A/I: Artificial Intelligence suggests alternatives based on our list. If we list four related alternative decisions but fail to mention doing nothing or any combination of our options, the A/I engine will prompt us to consider these additional decisions.
A/I App Result: “After we listed combining sales and marketing or also adding product line management, the A/I engine prompted us to add doing nothing right now or consider all combinations of the three areas combined in different ways.”
Step Four: Bias Check
App: A proactive list of the cognitive biases most likely to haunt our decision will appear in the app, providing constant awareness.
A/I: There is powerful potential here as the A/I engine utilizes our history including questions we answered, reducing the likelihood that any biases could affect our decision.
A/I App Result: “A thorough review of the biases mostly likely to impact our decision based on our behavioral characteristics, ruled out the possibility of a recent article affecting our thinking and the A/I engine researched factual data on the statistical tendency to organize in this fashion, considering only similar sized companies with similar profiles.”
Step Five: Filter the Decision
App: Our app is valuable here as each filter checkpoint is presented to the user, asking for confirmation there are no issues. Even though we all know our core values, each can be reviewed just to be sure.
A/I: While there is not a strong A/I opportunity here, historical data should enable this intelligent engine to suggest past filtering failures could be repeated.
A/I App Result: “Every filter checkpoint passed, providing confidence we are on the right track thus far with this decision!”
Step Six: Decide!
A/I App Result: As we finalize our decision, take comfort in our effort to make this a rational process utilizing both human and artificial intelligence technology. Record the decision in our app so the A/I can analyze what works well in the years ahead and use that data to assist us further. Well done; we used a proven process to make a cutting-edge and successful decision!
A/I App Result: “We’re excited to move ahead and reorganize, creating a more traditional and synergistic Business Development function consisting of Product Line Management, Marketing, and Sales”.
Conclusion: Transferring our proven business decision-making system to an app while adding an artificial intelligence engine to enhance the results is successful. We made a rational, well-thought, by man and machine, decision. Well done!
1Valero de Urquia, B. (2022, June 14). Google Engineer claims AI system has developed feelings. RSS. Retrieved July 28, 2022, from https://eandt.theiet.org/content/articles/2022/06/google-engineer-claims-ai-system-has-developed-feelings/