AI-driven Needs Analysis
AI-driven Needs Analysis
Why Businesses Cannot Act Ethically or Protect the Climate
Humanity has entered the AI Age without knowing how best to leverage AI for success. Businesses are struggling to apply AI without changing their traditional practices or improving the data they use for decision-making, and their results are less than satisfactory.
Decisions, whether made manually or automatically, require predictability and objectivity. High predictability requires a repeatable process and sufficient amounts of valid, unbiased, reliable ratio data and objectivity that is free of bias, greed, and self-interest. Because AI can analyze more data faster and more accurately than humans, it can consistently follow a process without error and has no preference as to decisions. Therefore, AI is far better suited for making better business decisions than humans.
Why Businesses Cannot Act Ethically or Protect the Climate
Human bias, greed, and self-interest are endemic business problems that are revealed in businesses that choose to unfairly skew wages toward higher-level workers, not protect the environment, not hire workers of certain races, ages, or gender differences, etc. Ironically, the root causes of most business problems are human bias, greed, and self-interest; however, no needs analysis model currently checks for these three significant factors.
Performance Ratio Data is the "Holy Grail"
Only performance ratio data captured automatically without human involvement is valid, unbiased, and reliable enough to be predictive. That data is the “holy grail” of every business worldwide because it references the most precise performance level possible, which is the time it takes each worker to perform every step of every SOP they execute. Time and money are ratio data because they can be used in mathematical calculations, translated to money, and broadly compared across workers, SOPs, equipment, and any other important performance variables.
Knowing the time it takes to perform every step of every SOP also informs businesses of the cost it takes to perform each step, the time and cost to perform each SOP, and ultimately the time and cost of all business activities.
For AI to equally benefit economies, businesses, and workers, companies need to a) stop relying on old ways of doing things, b) create a common language with clear goals that everyone in the company understands, c) gather and share accurate and unbiased performance data across all areas of the business, d) develop or purchase an advanced intelligence augmentation (AIA) system to collect the data needed for AI, and e) create or buy and implement a workflow for AI-driven needs analysis that the AI can follow.
Once everyone in a business is philosophically, strategically, and tactically congruent, then the business can write or optimize the algorithms and flowcharts their AI will follow. After an AI-driven needs analysis process is implemented, it can be expected to look at performance data all day, every day, without the bias, greed, or high costs that come from having humans do the analysis.
This book suggests an AI-driven needs analysis system as the solution. When provided valid, reliable performance ratio data, VURPRD, the system, can perform business-wide needs analysis 24/7/365, without the time, cost, bias, greed, or self-interest incurred by human decision-makers. The system creates and keeps an up-to-date list of actions the AI suggests, shown as a project plan template that includes details like goals, measurements, deadlines, budget, potential problems, communication strategy, and recommended team roles.
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