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Organizations don't have a great track record for successful internet of things projects, according to Cisco. A study conducted by the company last year found that only 26% of companies have had an IoT initiative they considered a complete success, while a third of all completed projects failed. Perhaps even more discouraging, the study showed that 60% of IoT initiatives stalled at the proof-of-concept stage.
In this expert tip, Jon Stanford, principal for industrial security and IoT solutions at Cisco Customer Experience, discussed the status of IoT adoption as well as the challenges and opportunities that organizations are experiencing.
Editor's note: The following has been edited for clarity and brevity.
IoT definition and metrics still muddled
What's your assessment of IoT adoption among U.S.-based organizations?
Jon Stanford: If I had to put a grade on it, we're at C+. That's due to a couple of reasons. One, IoT really has a hundred different definitions, so businesses struggle with what IoT is and more specifically what it means to them.
And another challenge is how we're going through iterations of IoT. Businesses are trying to take the promise of IoT and all the technologies associated with it and marry it to their digital transformation efforts. But that will take on different flavors depending on the vertical. If you think about a manufacturer they're going to look at IoT differently than a bank would, because IoT would enable different kinds of outcomes in those cases. But I expect over the next few years we'll get into the next phase, and what we'll have is a uniform definition of what it means in different industries and we'll be able to have more measurable outcomes.
How, then, do you define IoT?
Stanford: Another label for IoT is smart data. But smart data takes on different definitions. For a bank, the definition might [mean asking:] How can we better engage with customers? For a manufacturer, it might [mean asking:] How do we get visibility into assets that don't communicate outside their local functional operations, and how do we use that data to be more competitive?
What is holding up broader IoT adoption among organizations?
Stanford: The desire and the demand for IoT and access to data and what companies would do with the data is pretty clear to organizations, but I don't think the challenges are as well understood. I don't think many organizations understand what it would take to enable a smart data world and to get access to this data. They don't understand the level of connectivity required, or the best way to do that, and the way to do that in the most optimized and most cost-effective way. That's where I think some of the lack of fulfillment has occurred.
Business outcomes not well-defined
What's the most common challenge organizations face in adopting IoT?
Stanford: Most organizations struggle at a business level with what outcomes they want to achieve. They might recognize that IoT brings increased connectivity [to numerous endpoints], and they might be aspirational around data and analytics, but the more fundamental question is what outcomes do they want to achieve.
Many organizations haven't thought that out so well. They start thinking about the technology and implementation. So, before they start expending resources, they need to think about the fundamental drivers and outcomes for them as an organization.
You've talked about the dark data problem in IoT initiatives. What is that?
Stanford: Assets generate valuable data, but this data is not connected to the outside world, and it is not connected to the business side. So, you can't mine this data. The dark data problem is essentially a connectivity problem. For example, manufacturers build a production plant that's optimized to produce widgets. The business side says that's all well and good, but we need visibility into [the data produced by] those assets. In the smart data world, we need that data [from the production line asset] to extend beyond the production context, because there's intelligence to be gleaned from that data. IoT is about connecting to that data and making use of that data.
IoT adoption takes effort, causes disruption
Any other common challenges you'd highlight?
Stanford: Assuming that they have identified the right outcomes, [many organizations] fail to recognize the level of effort that might be required around adopting an IoT initiative. It can be very eye-opening. If the company wants to be more competitive in the market using IoT, they might be surprised by the level of disruption that [an IoT initiative] might cause within their organizations. It might require them to change core business processes or stand up functions that don't exist today.
How should organizations address these challenges?
Stanford: We engage with customers to develop a journey map that ensures that from start to finish the customer fully understands what they want to achieve in terms of a transformation. So, they might talk about the technology, but behind that are business drivers. It's a mistake for organizations to assume it's a technical problem -- and, therefore, being a technical problem they need to [find] technical solutions … to achieve an outcome. They have to look at it as a business process problem and identify outcomes and ask whether they're achievable. Part of that might mean technology adoption as well as fundamentally changing business processes.
Current IT infrastructure, skill sets, fall short
But IoT clearly has technology implications. What are the biggest impacts on organizations there?
Stanford: One would be the impact [IoT initiatives can have on] their current technologies portfolio. Companies have made investments over time in IT, and adoption of a major IoT initiative may require significant changes to the company's internal IT infrastructure. That can be a huge challenge, shifting from here to there. And in a worst case scenario, that might mean they're not going to get a full return out of the investments they've already made in their current IT infrastructure.
For example, if a healthcare organization had previously implemented a digital records system, their new IoT use case might require the same records being made available to a workforce that is now mobile. If the current system isn't designed to support mobility, they might need to integrate the system with brand-new technologies to securely deliver the content when and where it's now needed. A device manufacturer might adopt an IoT data initiative to lower their operating costs via predictive maintenance, which requires rearchitecting existing network routing and switching infrastructure and implementing additional security protections to gain access to the right data.
So, the net new investments may also be very shocking for some organizations.
If I were to throw in a third challenge, I'd say skill set. IoT for organizations, especially for those who adopt IoT initiatives that are very forward-leaning, requires a very knowledgeable, very capable workforce that's up to date on all the latest technologies and development methods, and have skills around software-enabled processes. Those resources are very scarce and everyone is in competition for the next generation of technologists.
What are the biggest security issues around IoT?
Stanford: IoT adoption means increasing connectivity to endpoints and devices that aren't connected today, so there's a potential increase in the threat topography, there are more potential entry points into the network for bad actors and there are more things to secure. This increased connectivity issue is a fundamental part of the security concern, and it could be a significant barrier for some organizations.
What's the future for IoT?
Stanford: We're moving to a data analytics-driven world, so a lot of fundamental things in IT are transforming. The world of the future is a world of hyperconnected; things will increase their connections to other things over time. Look at refrigerators, for example: They're smart and they connect to the internet. The smart data world of IoT provides tons of opportunities, and I think industries across the board are just now looking at intelligent data and asking what can they do with this and what new business models will it open up and what does it mean for the future. We're going to see it fundamentally transform a number of industries.