Measuring efficiency, and increasing it with AI
The quest for efficiency has driven innovation since the beginning of time. People and companies shell out millions to save time, energy, or mental stress, whether it’s complexity-cutting payroll software or engaging a service provider to keep your systems secure.
The thing is, it’s hard to quantify exactly what efficiency those choices create. How can you measure the efficiency gains from a new technology or process?
In some instances, the difference is enormous and obvious—the industrial revolution certainly made the world more efficient, even if it hasn’t been quantified—but as we stand on the brink of a second revolution, driven by technology and artificial intelligence, the nuances become a little harder to pin down.
So how do you measure something as intangible as efficiency?
The unmeasurable measurement
One answer is “biocost,” a combined measurement of four key factors of efficiency:
The last three are otherwise categorized as physical, mental, and emotional effort.
Together, these factors represent the cost of work. By lowering just one or all four, your employees and business will get more done with less effort, freeing resources and opening a path for innovation and improvement.
Shrinking your biocost footprint
Biocost can be lowered in a number of ways, most typically by exchanging money for a service. Taking the bus 10 miles, for example, will yield a lower biocost than walking all that way. Biocost can also be limited through cooperation and collaboration—when two or more people work together, either on separate tasks or the same task, to achieve an end goal, they can lower any of the four factors.
But that collaboration still has to be efficient. For example, imagine a client asks a salesperson a question she doesn’t know the answer to. She tells the customer she’ll ask a support rep and come back with an answer. Then begins the process of figuring out which expert to ask, emailing that person, calling them, leaving a message, waiting for them to get back to you with the answer, and following up. This drains time and energy, causes a mental burden for your employees, and, ultimately, could lose you a sale.
So how do you lower the biocost in this particular situation? One way would be to have that knowledge openly and freely available to your salesperson, through an always-accessible resource or AI.
The sales rep could simply ask the AI, which would sort through the appropriate contacts and direct the question to the best expert on that matter. Once the answer was retrieved, the AI would then store that information for the next person who asked it. The collaborative process is much faster, and involves much less time and mental work on the part of the salesperson.
However, it’s still difficult to measure the biocost saved using this process. When you’re testing different workflows or new technologies, you want to make sure your experiment is actually improving efficiency, not just moving things around. Well, we found a way.
Benchmarking biocost with academia
In an effort to minimize biocost, SHI has been working with leading business schools to come up with a standardized way to accurately measure biocost in the workplace. Through a series of studies and a process created by MBA candidates, SHI is assisting in the creation of an algorithm that determines the biocost of a particular activity. This way, we can see how technologies—specifically AI—can reduce the time, energy, attention, and stress required for a task, demonstrating the new efficiency in hard numbers.
Just as in the example above, we’re hoping to implement an AI assistant into certain workplace scenarios, typically those that involve hard-to-scale or expert-specific knowledge. By measuring the biocost before and after implementation, we’ll be able to show the tangible effect that an AI assistant may have in the workplace.
If you’re interested in pursuing or testing such an AI and lowering your own workplace biocost, contact SHI for more information.