When most people think about IoT, they think about smart cars, personal assistants, and controlling their home appliances. And yes, all of these things are a part of the IoT universe – devices talking to one another without human intervention; machines and artificial intelligence being able to learn patterns and make predictions; oceans of data being gathered, churned, and reported out based upon specific queries.
But personal use of IoT is just one aspect of this new universe. The business uses, and specifically the development of new strategies and models, promise to transform how companies make decisions and conduct business. And companies that want to remain competitive in this new marketplace of IoT, machine learning and AI, will embrace all that this new technology offers.
Businesses provide products or services to their clients/ customers. And they can be B2B or B2C, depending on what they produce and who needs it. They can also have a client base that is confined to a single country or is spread throughout the globe.
Being competitive means that, whether a company offers products or services, it embraces the latest technological advances in order to produce high quality, produce it faster, and meet the demands of its customer base.
Enter IoT, Machine Learning and AI
All of these technologies rely on this: a system of connected devices, objects, mechanical and digital machines, and people with the skills to develop programs and algorithms that can transfer information through a network, so that all of the devices, objects and machines can perform tasks without human intervention. In the end, objects perform and critical data is churned and reported out to be studied and interpreted by humans.
And here is how all of this impacts business models and strategies.
Businesses That Offer Products
Physical products have to be made; they have to be stored as inventory; they have to be shipped. In this whole process, there are multiple functions that must occur. And new technology will allow such a business to accomplish the following in manufacturing and logistics.
- Track incoming raw materials
- Add ‘smart’ technology to the manufacturing process, so that machines are programmed to complete tasks that formerly were completed manually by people
- Add ‘smart’ technology to the products themselves. Sensors and chips can inform the manufacturer if and when issues with the product arise, what those issues are, and allow for those issues to be resolved remotely.
- Track inventory as it is pulled for shipment and automatically order more raw materials as needed to replace a depleting inventory
- Track transport of each product through its route to its destination/ arrival, even internationally.
And speaking of international commerce, there is the issue of multi-language communication with foreign customers. Translation services to date provide both machine and human translation, and it is important for companies to find the best translation site for their needs. But machines continue to learn, and the day may come when that function is fully in the hands of machines and AI.
Beyond this, however, there is the data that can be gathered regarding consumer behavior and demand for new and/ or enhanced products – data that will drive future decisions about what to produce to meet new and evolving demands, thus staying ahead in a competitive marketplace.
Businesses That Offer Services
A Case Study in Banking
Consider, for a minute, all of the functions that banks perform. Software programs and machines now perform most of those functions, so that human error is virtually eliminated. Consumers can now access their accounts online and perform virtually any function – check balances, transfer funds, pay bills, etc.
And thanks to machine learning and AI, banks have been able to gather data, aggregate it, and gain insight into the services that consumers want. Based on that, they are now offering such services as summaries of expenditures by category, debt to income ratios, and even recommendations for savings and debt management.
Beyond that, the data that banks now collect is churned, so that patterns of consumer spending and debt are churned and can provide predictive analysis regarding products and services that banks should begin to offer. One example is in the area of consumer loans. Data aggregation will provide recommendations about the types of loan products consumers will find most attractive, and even at what times of the year certain loan products will be more in demand. This information will drive business strategies.
Data science brings an entirely new level of understanding to businesses that provide services – financial enterprises, insurance, health care, travel, and more. And when businesses adjust their strategies to synchronize with what data tells them, they will serve customers better and keep their market share.
It’s a new world. Years ago, the Internet ushered in the information age. We could use it to search for what we wanted to know. Then, it gave us the ability to talk with other Internet users. Ultimately, it has become an ocean of information and data and a place to communicate, purchase goods and services, and make use of amazing technologies (e.g., AR/VR) to get experiences our grandparents never would have dreamed of.
And now we have the next major disruption – IoT, machine learning, and artificial intelligence. On a personal level, we can now make use of IoT to enjoy and control parts of our lives. At the same time, businesses are using this new technology to track our behaviors, to discover what we want and need, and to see to it that the products and services we do want are available. While we may have some worries about ‘Big Brother’ watching us, we nevertheless welcome the fact that companies are developing strategies to accommodate our wishes.
At a relatively young age, Donald Fomby has already amassed impressive experience as a freelance writer. Donald studied Computer Science at Texas A&M and is a loyal Aggies football fan to this day.