Smart Operations Management Vision

Many staff and management people in industrial and commercial organizations spend most of their time doing “intelligent grunt work” tasks which include:

Attending time-wasting planning and coordination meetings
Reading reports about what went wrong yesterday
Entering duplicate data in multiple systems
"Walking the floor" or staring at endless screens to find the status of customer orders
Or trying to spot what is going wrong right now and needs their immediate attention
Creating and analyzing endless numbers of Excel or other spreadsheets.

All of this is so that these people can do one of two things:

Make decisions
Provide other people with critical information

Much of this intelligent grunt work, along with gathering and analyzing the data upon which information and decision are based, can be performed much more efficiently, and at a lower cost, by a cloud of intelligent agents, running on networks of computers, rather than by people.

In automating these tasks, we need to recognize that there is specific knowledge where decisions can be made automatically based on rules and mathematical algorithms.

But, often much more frequently, there is also general knowledge, where the breadth of knowledge of people, as well as their intuition, has to used to make decisions about what data means and to whom to forward the resultant information.

As a result, intelligent agents are, for the most part, best used for automatically gathering and analyzing data, from a variety of sources, alerting people when they need to take action, presenting the resultant information in a meaningful form, and then automatically relaying the decisions made by people to other people or systems that need the resultant information.

Sometimes, decisions can be fully automated but usually intelligent agents function best in a decision support advisory role.

In most industrial and commercial operations, multiple events, which could impact decision making, occur at random times, in parallel, at many different locations. As such, it is important that these decision support functions take place in parallel in near real-time.

Hence the need for multiple intelligent-agents all running in parallel, exchanging information with each other, rather than using one large regenerative AI program which can take a long time to run on a large expensive super-computer.

Today, the cost and power of computing has improved to the point where many intelligent-agents can be run in parallel on a single ruggedized industrial Internet of Things (IOT) computer costing under $1,000.

This enables intelligent agent software such as the Real-Time Agent Platform (RTAP^™) software from the SmartOps^™ to be deployed at affordable cost for even small and mid-sized organizations, with many such computers deployed to different geographic locations or even deployed on mobile platforms, such as vehicles.

Today intelligent agent-based decision support systems are being used to augment existing ERP (Enterprise Resource Planning) systems.

But it is believed that these intelligent agent systems will come to replace ERP systems, except possibly in traditional ERP roles such as accounting.

The goal of SmartOps is not just to provide affordable Smart Operations Management systems to improve the efficiency of operations in industrial and commercial organizations but more importantly to encourage their increased use in applications which can benefit humanity, such as protecting our food and pharmaceutical supply chains against contamination, counterfeiting, and bioterrorism.

Also, as we are experiencing a rapid decline in populations world-wide, especially amongst urbanized developed nations, we will need to employ intelligent agent systems in a wide variety of roles, if we are to maintain our standard of living as well as to take care of our rapidly increasing number of elderly people.