How Can Companies Get More From IoT?
Identify a specific business problem to solve. Make people's lives simpler and easier. Those are the keys to successful IoT initiatives.
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To gather insights on the current and future state of IoT, we talked to 23 executives involved with IoT. We asked them, "How can companies get more out of IoT?"
- Solve problems simply and easily.
- Think about the business case you are trying to solve. Focus on one to four aspects of the IoT business chain: 1) how to monetize; 2) monetizing what matters; 3) starting small – one or two lines of business and then scaling by replicating; and, 4) there are many players offering many vertical-specific solutions – look for opportunities to partner to provide the best solution for the business problem.
- Have the right ideas/devices to serve a real customer need. Problems are typically scalability and how to create a device. Devices differ from software and require different skillsets like putting embedded devices together. There is a lack of good engineers. Create tooling to make it easier to connect devices. Connected devices are complex and present a new set of challenges like security, connectivity, over-the-air updates necessary to keep the device current. IoT devices are not a one-time sale, they need security and upgradability. How are you going to monetize the device – subscription model or one-time charge up front? If you push the hardware price down, then your R&D costs go up to get the functionality and upgrades that are desired. Change thinking on the business side from short-term to long-term. For example, automobile entertainment systems just think about what the consumer wants now. Tesla delivers the value of software upgrades long-term. Short-term thinking is still a struggle.
- IoT is not a software-only deployment. Sensors must be built and deployed in the field. Takes time to build and rollout. Legacy systems require modernization.
- Companies can get more out of IoT by determining how to quickly and efficiently manage, analyze and also create meaningful insights from the data they’re collecting. Key is these companies need to maintain high accuracy and speed of the analysis. Another factor for getting is balancing centralization and localization of intelligence to help determine how smart or dumb you want the sensors and devices to be, and balancing personalization with the need to maintain the privacy and confidentiality of data.
- Challenges/barriers is connecting with legacy infrastructure. Organizations are slow to upgrade to next-generation technology. Connectivity can be a problem for remote locations. Vendors are so focused on platforms rather than the fact that customers do not have the people capable of performing the analysis, AI/ML skills to take advantage of the data to solve problems. There’s a significant skills deficient. Employees don’t understand use cases to drive business results.
- The realization that the plumbing of putting all of the plants, machines, devices, and data together isn’t easy.
- Stop thinking IoT is easy. There is a lot of complexity to make IoT a reality and most companies do not have the telecom or IT skillsets. While it’s easy to connect to the cloud, there’s a lot of complexity to scale and build an IoT business. Collecting data where the asset is challenging. Protocols, specifications, wireless technology, security are all hard to cope with. There’s a gap between the proof of concept and a device that can scale. Organizations give up on their IoT initiatives because of a lack of skills and the costs associated with bringing an IoT project to fruition. Need to solve the complexity and create a stack that enables the customer to manage IoT devices themselves. This includes devices that run software at the edge, the telecom piece with SIM cards and connectivity, the cloud piece of managing devices and updating them, and then moving data between the edge and the cloud. All of these elements need to be combined in a single package that’s easy for the customer to use.
- Most companies currently have multiple platforms for different sensors. Our plan is to aggregate data from multiple sensors on to one unified platform. This way of consuming data allows for much more powerful analytics because we can identify correlations between different sensors. For example, correlation between sensors can help with loss prevention in retail. Take for instance “sweethearting” – when an employee gives products away for free to “sweethearts”. One way to do this is to pretend to move the product over the scanner, but in a way that it doesn’t, in fact, get scanned. Similar to how a security guard might review the tapes and notice that an employee swiped 13 items, but the cash register only rang up 10 items, a unified IoT platform could detect this discrepancy without human intervention.
- Stop drowning in IoT data lakes. Don’t just think of collecting data, know how you’re going to use it in the workflow of the enterprise.
- Be willing to adopt new things and be open to the insights data can provide.
Here’s who we spoke to:
- Adam Fingerman, CXO and Co-founder, and Troy Petersen, Marketing Director, ArcTouch
- Andreas Pettersson, CTO and CPO, Arcules
- Sean Grundy, CEO and Founder, Bevi
- Jeff Bonnell, V.P. of Industry Solutions, Coresystems
- Eli Feldman, CTO, Advanced Technology, EPAM
- Brent Pietrzak, V.P. Producer Solutions and Strategy, Flexera
- Scott Allen, CMO, FreeWave
- Mark Herring, CMO, Tim Hall, V.P. of Products, Brian Mullen, V.P. of Business Development, InfluxData
- Dipti Borkar, V.P. of Product Marketing, Kinetica
- Crystal Valentine, V.P. of Technology Strategy, MapR
- Jesse Robbins, CEO, Orion Labs
- Lars Knoll, CTO, Qt
- Olivier Pauzet, V.P. and General Manager IoT Solutions, Sierra Wireless
- Jens-Ole Graulund, CTO, Spiio
- Monte Zweben, CEO, Splice Machine
- Shawn Reynolds, CMO, Telit
- Yu Xu, CEO, TigerGraph
- Ray Wu, Founder and CEO, Wynd
- Alex Kubicek, CEO, Understory
- Jeff Finn, CEO, zvelo
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