To gather insights on the evolution of IoT at this point in 2017, we spoke to 19 executives who are familiar with the current state of the Internet of Things.
Having a Strategy
Several keys to success were recommended for an effective and successful IoT strategy. The most frequently mentioned tips were focused on having a strategy and use case in mind before starting a project. Understand what you want to accomplish, what problem you are trying to solve, and what customer needs you are going to fulfill to make their lives simpler and easier. Drive business value by articulating the business challenge you are trying to solve – regardless of the vertical in which you are working.
Architecture and data were the second most frequently mentioned keys to a successful IoT strategy. You must think about the architecture for a Big Data system to be able to collect and ingest data in real-time. Consider the complexity of the IoT ecosystem, which includes back-ends, devices, and mobile apps for your configuration and hardware design. Start with pre-built, pre-defined services and grow your IoT business to a point where you can confidently identify whether building an internal infrastructure is a better long-term investment.
Companies can leverage IoT by focusing on the problem they are trying to solve, including how to improve the customer experience. Answer the question, “What will IoT help us do differently to generate action, revenue, and profitability?” Successful IoT companies are solving real business problems, getting better results, and finding more problems to solve with IoT.
Companies should also start small and scale over time as they find success. One successful project begets another. Put together a journey map and incrementally apply IoT technologies and processes. Remember that the ability to scale wins.
Data collection is important, but you need to know what you’re going to do with the data. A lot of people collect data and never get back to it, so it becomes expensive to store and goes to waste. You must apply machine learning and analytics to massage and manipulate the data in order to make better-informed business decisions more quickly. Sensors will collect more data, and more sophisticated software will perform better data analysis to understand trends, anomalies, and benchmarks, generate a variety of alerts, and identify previously unnoticed patterns.
A Core Component
IoT has made significant advancements in the adoption curve over the past year. Companies are realizing the value IoT data brings for them, and their end-user customers, to solve real business problems. IoT has moved from being a separate initiative to an integral part of business decision-making to improve efficiency and yield.
There’s also more data, more sources of data, more applications, and more connected devices. This generates more opportunities for businesses to make and save money, as well as provide an improved customer experience. The smart home is evolving into a consolidated service, as opposed to a collection of siloed connected devices with separate controls and apps.
There is not a single set of technical solutions being used to execute an IoT strategy since IoT is being used in a variety of vertical markets with different problems to solve. Each of these verticals and solutions are using different architectures, platforms, and languages based on their needs. However, everyone is in the cloud, be it public or private, and needs a data storage solution.
All the Verticals
The real-world problems being solved with IoT are expanding exponentially into multiple verticals. The most frequently shared by respondents include: transportation and logistics, self-driving cars, and energy and utilities. Following are three examples:
A shipping company is getting visibility into delays in shipping, customs, unloading, and delivery by leveraging open source technologies for smarter contacts (sensors) on both the ship and the 3,500 containers on the ship.
Renault self-driving cars are sending all data back to a corporate scalable data repository so Renault can see everything the car did in every situation to build a smarter and safer driverless car that will result in greater adoption and acceptance.
A semiconductor chip manufacturer is using yield analytics to identify quality issues and root causes of failure, adding tens of millions of dollars to their bottom line every month.
The most common issues preventing companies from realizing the benefits of IoT are the lack of a strategy, an unwillingness to “start small,” and concerns with security.
Companies pursue IoT because it’s a novelty versus a strategic decision. Everyone should be required to answer four questions: 1) What do we need to know? 2) From whom? 3) How often? 4) Is it being pushed to me? Companies need to identify the data that’s needed to drive their business.
Expectations are not realistic and there’s a huge capital expenditure. Companies cannot buy large-scale M2M solutions off the shelf. As such, they need to break opportunities into winnable parts. Put a strategy in place. Identify a problem to solve and get started. Crawl, walk, then run.
There’s concern around security frameworks in both industrial and consumer settings. Companies need to think through security strategies and practices. Everyone needs to be concerned with security and the value of personally identifiable information (PII).
Deciding which devices or frameworks to use (Apple, Intel, Google,Samsung, etc.) is a daunting task, even for sophisticated engineers. Companies cannot be expected to figure it out. All the major players are using different communication protocols trying to do their own thing rather than collaborating to ensure an interoperable IoT infrastructure.
Edge Computing and PII
The continued evolution and growth of IoT, to 8.4 billion connected devices by the end of 2017, will be driven by edge computing, which will handle more data to provide more real-time actionable insights. Ultimately, everything will be connected as intelligent computing evolves. This is the information revolution, and it will reduce defects and improve the quality of products while improving the customer experience and learning what the customer wants so you will know what to be working on next. Smarter edge event-driven microservices will be tied to blockchain and machine learning platforms; however, blockchain cannot scale to meet the needs of IoT right now.
For IoT to achieve its projected growth, everyone in the space will need to balance security with the user experience and the sanctity of PII. By putting the end-user customer at the center of the use case, companies will have greater success and ROI with their IoT initiatives.
All but a couple of respondents mentioned security as the biggest concern regarding the state of IoT today. We need to understand the security component of IoT with more devices collecting more data. As more systems communicate with each other and expose data outside, security becomes more important. The DDoS attack against Dyn last year shows that security is an issue bigger than IoT – it encompasses all aspects of IT, including development, hardware engineering, networking, and data science.
Every level of the organization is responsible for security. There’s a due diligence responsibility on the providers. Everywhere data is exposed is the responsibility of engineers and systems integrators. Data privacy is an issue for the owner of the data. They need to use data to know what is being used and what can be deprecated. They need a complete feedback loop to make improvements.
If we don’t address the security of IoT devices, we can look for the government to come in and regulate them like they did to make cars include seatbelts and airbags.
The key skills developers need to know to be successful working on IoT projects are understanding the impact of data, how databases work, and how data applies to the real world to help solve business problems or improve the customer experience. Developers need to understand how to collect data and obtain insights from the data, and be mindful of the challenges of managing and visualizing data.
In addition, stay flexible and keep your mind open since platforms, architectures, and languages are evolving quickly. Collaborate within your organization, with resource providers, and with clients. Be a full-stack developer that knows how to connect APIs. Stay abreast of changes in the industry.
And here’s who we spoke with:
Scott Hanson, Founder and CTO, Ambiq Micro
Adam Wray, CEO, Basho
Peter Coppola, SVP, Product Marketing, Basho
Farnaz Erfan, Senior Director, Product Marketing, Birst
Shahin Pirooz, CTO, Data Endure
Anders Wallgren, CTO, Electric Cloud
Eric Free, S.V.P. Strategic Growth, Flexera
Brad Bush, Partner, Fortium Partners
Marisa Sires Wang, Vice President of Product, Gigya
Tony Paine, Kepware Platform President at PTC, Kepware
Eric Mizell, Vice President Global Engineering, Kinetica
Crystal Valentine, PhD, V.P. Technology Strategy, MapR
Jack Norris, S.V.P., Database Strategy and Applications, MapR
Pratibha Salwan, S.V.P. Digital Services Americas, NIIT Technologies
Guy Yehaiv, CEO, Profitect
Cees Links, General Manager Wireless Connectivity, Qorvo
Paul Turner, CMO, Scality
Harsh Upreti, Product Marketing Manager, API, SmartBear
- Rajeev Kozhikkuttuthodi, Vice President of Product Management, TIBCO