Maslow’s Hierarchy of Needs in IoT
Meeting customers regularly, we always get asked
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- can you do predictive maintenance?
- Do you have “value-add” analytics (whatever value add really means)?
- Automated energy savings?
The quick answer, of course we can!
This is why we have our software engineers, electrical engineers, hardware product designers and data scientists all in one room working together towards 1 common goal.
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- API for your IoT to enable
- Equipment recognition (not facial recognition)
- Programmatic control of your facilities
However, to get there you need to start somewhere. The first step is to get your facilities connected with the right sensors, either operational or electrical, preferably both.
Once you’ve connected your premise, depending on the size, we generally “hook you up” with our certified installers within a day, our best is 150 facilities across multiple States in 5 weeks!
Now you’re connected, we always see the same pattern in our customers. I summarize this into “Maslow’s hierarchy of needs in IoT”.
Stage 1 Saving Money (or as we call it safety)
Already within the first months, we provide our customers with significant savings, reaching up to 30% month on month reduction of energy costs.
Here a typical case study of a convenience store in the retail sector.
You can contact our team for more details here
Stage 2 Minimizing downtime (quality assurance in Energybox parlance)
Now that you’ve got a grip on your costs, you’ve been collecting data and all the while we’ve been worrying about our sustainable value to you.
Looking to retain value, our data scientist, algorithms, and AI engine have been working to understand the type of equipment you have, understand your and the equipment patterns to be able to ensure quality and minimizing equipment downtime.
Visualizing key metrics in our dashboard to assist you in the management of your equipment and facilities.
Stage 3 Total Cost of Ownership
As you look to replace equipment or set up a new facility, invest in that new refrigerator, walk-in freezer, creamer or even car washing machine for your facilities, you weigh of different criteria in your decision.
We collect large quantities of data across different equipment and can identify consumption patterns which when combined with our data scientists and AI engines we also include maintenance.
Combining the operational expenses with third party data for capital expenses for these machines and then dividing these over the total service life of the equipment, we can provide you with the insights you are looking for to maximize that investment in new equipment.
Stage 4 Control
This is a longer topic which I’ll share in a separate blog, where I will talk about the different stages of how control enables and drives a path to a fully autonomous facility.
There is no way our customers are even prepared to hand over the operations of all their facilities in 1 go to be fully autonomous. We’re seeing a much more pragmatic approach where our customers are looking to an evolution towards autonomous facilities.
Read more about the stages of this evolution and where we are in the world today. Stay tuned with us!
Stefan Rust
SVP Software & Marketing
