I thought to share with you a tangible view on how IoT is transforming all industries as opposed to discussing yet again the familiar IoT use case:
( a list for those interested, just in case )
- Manufacturing optimization
- Warranty compliance
- New services (predictive maintenance)
- Sales enablement
- Product development
- Service optimization
My claim is that: no industry will escape IoT transformation. Companies that deploy IoT today have a chance to save their business and grow while the others will be squeezed out. To make the case, I will use the example of the laundromat, a simple yet essential service.
At the center of the laundromat is the coin operated washing machine. You are probably thinking, what does this have to do with IoT? Well, think IoT connected washing machine and the light bulb will come to life. Before you consider the laundromat to be too small or irrelevant business checkout WASH which operates 65 000 machines.
What happens when the laundromat uses smart and connected washing machines?
1-Excellent consumer service.
Nothing is more annoying than arriving at the laundromat to see that all the machines are already in use or having to wait for the dryer to finish and not knowing how long. An IoT laundromat knows at all times the status of all machines. Offering a mobile application to reserve a machine or see available ones is trivial. Think notifications of free machines and “your laundry will be ready in 15 min” premium service.
2-Better utilization of assets.
An IoT laundromat knows at all times the status of all machines. This means the operations team have a precise picture on utilization of the machines, water, electricity and foot traffic in the laundromat. A quarter stuck in the payment box will no longer put the washing machine out of service till someone makes the rounds. Better still, machine down time is eliminated due to predictive maintenance.
3-New revenue streams from data.
Consider the data collected from the machines and the value they bring to multiple players. Which type and how much detergent is being used per load, peak activity, load type, and machine settings. Other companies would pay to access such statistics per city and per neighborhood. Think different cultures and the associated habits.
4-Reduced environmental impact (just to be a bit green).
Pricing can be varied based on peak electric load to encourage people to do their laundry when the electric grid demand is lower. There is no reason to why the spot pricing for electricity should not trickle down to the consumer.
5-Excellent customer relationship and Improved product manufacturing/design.
Assuming that the manufacturer owns the data on the performance of the washing machine then this gives them direct visibility of how the customer is using the product. This is not a common thing in the industry due to the many layers in the supply chain between the designer/manufacturer and the customer. A business operating without direct customer relationship is missing essential information for the success of future products. For example, new product development becomes a less risky affair if the business knew first hand how customers are using the existing products and services.
All the above just from a laundromat service! Imagine now the possibilities and the transformation of all industries. Imagine the impact for those that delay adoption of IoT.
IoT enables new and deeper relationships with customers.
IoT delivers insight to why the customer selected the product and the sort of service they expect around it. Most of all, IoT shows how the product is being used.
Resistance is futile.
A key hi-tech figure recently said in his keynote: Adapt, “eat or be eaten”
For those still in doubt:
Working closely with manufacturers, WASH uses machine data to anticipate maintenance before downtime occurs. Working with payment processors, WASH Laundry provides launderers with an array of payment, coupon, and loyalty programs. And the possibilities aren’t restricted to improving operations. Working with apartment-building owners, WASH uses data from its large device network to model and test managerial intuition about questions such as whether it is cost-effective to switch from cash to payment cards before committing to widespread changes. What’s more, alternative pricing options become possible with device data: Colleges are working with WASH to adjust pricing at peak periods to spread demand, reduce congestion, and improve student experience. source: (item 1 below)