In their book ‘Prediction Machines’, Ajay Agrawal, Joshua Gans, and Abi Goldfarb, demonstrate how Artificial Intelligence (AI) will affect economies and economics as we move through the next several years and decades.
They present three key statements at the beginning of the book:
- Cheap changes everything
- Cheap means everywhere
- Cheap creates Value
The reason for this blog is that I believe we can apply these statements to the efficiencies that we are all trying to achieve within our organizations.
Let’s unpack what the authors are saying from a macro point of view. If something is cheap, we will probably buy or consume more of it. Tenderloin steak, potato chips, healthcare services, automobiles, etc. and the list goes on and on. If we see value in a goods and services at a certain price point, then using more of it is an economic pattern we have all observed.
The same is true for the processes you and I use at the companies we work for. If something has great value and allows us to deliver more to our management teams, suppliers, staff, and marketing groups, we most likely will adapt to that process because of the value it gives us. That value is time savings and cost reduction! We are all consumers no matter what perspective we take.
So where am I going with this…….
Manufacturing Web Services
In my business, Manufacturing Web Services at DSI, we recognized that this macro force is alive and well within our own business model. Our customers wanted the ability to roll out web services at a faster and faster pace. The cost of implementing these services aside, the time to do data capture web sites for each business challenge was scaling to a cost prohibitive endeavor. Each business problem introduced the repetitive cycle of design, sign-off, database creation, approval, implementation, testing, install, training, etc. The list goes on and on for each new website and web service introduced.
'No Code' Systems
The need for a ‘no code’ system that allow plant personnel to quickly roll out forms to capture manufacturing information was not only required, but necessary as production techniques move toward Web 3.0 and Industry 4.0. Not too long ago, if a manufacturing facility wanted to introduce a new electronic process into manufacturing, it took months to do with many parties involved.
We don’t have six months anymore to roll something out. The time to start collecting the data our factories produce was yesterday. We need to be able to roll these processes out to operators and employees and the tools should be intuitive and immediate. Training was either done initially or the system requires very minimal training because the software mediated system is so adaptive.
Tools for Industry 4.0
The system design still takes place, but it takes place within a ‘container’ that allows for the ‘vertical’ delivery of a process to help us with our business problem and it has placed all the ‘horizontal’ components such as database, security, access permissions, configuration into a tool that plant operations personnel can use (configure).
Software engineers and designers developed these tools in order to allow plant personnel to ‘configure’ their business process solutions for electronic data capture. The time from initial design all the way through the roll out of the process has been greatly reduced (cheaper).
Efficiencies need to accelerate. A tool that can be used everywhere and not just in one area of the plant is key (cheaper). We should all demand tools that allow a broader group of personnel to participate and contribute to making the places we work better and more efficient.
It allows your company to survive and compete.
Let’s recap as to how we started this……
- Cheap changes everything - Absolutely! The cost of rolling out new business processes has become deflationary and we can do more with the same budgets…..
- Cheap means everywhere - Without a doubt! One tool allows us to be everywhere within a plant and reach economies of scale…..
- Cheap creates Value - You bet! Reducing the time to roll out data capture services in order to make our plants and factories more efficient. We need this data to either ‘analyze’ the past or ‘predict’ the future.
After all, to write this blog, I didn’t stand out on the corner and buy kerosene from Standard Oil (think expensive - time, money, and delivery, not to mention inconvenience) to light a lamp so that I could see my computer screen, I flicked a switch and the ‘cheap’ electricity allowed me to pen this blog on a beautiful Sunday morning.
Remember, start small and finish big! Always keep moving forward….