How Cisco drives its industrial IoT business forward

Industrial IoT development is complicated and not growing as fast as analysts predicted. Cisco is seeing some success, though, thanks to its IoT ecosystem of customers, partners and expert innovators.

How Cisco drives its industrial IoT business forward
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Industrial Internet of Things (IoT) does not have the explosive growth of the consumer internet. It’s a nitty-gritty, complicated, and sometimes downright boring business. It is too complex and diverse for explosive growth like the narrowly defined, one-size-fits-all iPhone. That said, the promise of rich returns on investment from new business models that are possible with IoT is very compelling.

The only way to cut through the venture-driven IoT hype cycle is with conversations with builders and implementers at companies investing in IoT, such as Cisco’s co-innovation center chief, Maciej Kranz.

Kranz summed up his working in Cisco’s IoT business by saying:

“It has not been an easy journey, to be honest. When we started a dozen years ago, I thought that we would be much further along than this.”

maciej kranz headshot Cisco

Maciej Kranz

His comment speaks to why large companies like Cisco, with patience, a long-term vision and capital, will be the primary actors in creating a very large IoT market as large as analysts predict — but with a longer time horizon. Kranz explained why:

“We have to understand these vertical markets. How we integrate with legacy systems, the workflows, who are the key players — we will never have intimate relationships with facilities managers or people who run factories. It is not just a partnership play; we have to set the preference with the end customer.”

Customers seek new IoT-enabled business models

The IoT market is at a new starting point. IoT implementations have focused on improving existing processes to increase efficiencies. In Kranz’s view, after many incremental gains, the IoT industry is starting on new IoT-enabled business models with new revenues and profits, like mass customization and personalization and service-oriented business models.

Mass customization combines the flexibility and personalization of custom-made products with the low unit costs associated with mass production. Service-oriented business models are the extension of concepts such as pay per use. Pay per use is not much different than Amazon Web Services (AWS). Instead of owning servers, customers subscribe to use cloud computing infrastructure — except it applies to physical products. For example, a construction company might subscribe for the capacity to drill a certain number of feet each month rather than buying the drilling rig from the manufacturer.

5 elements of a successful industrial IoT project

Kranz spoke about Cisco’s evolving IoT strategy to accelerate industrial IoT development from proof of concept through production implementation, which they learned during engagements with customers such as Harley-Davidson. He has identified these five elements that lead to a successful first industrial IoT project.

  1. Start customers on the journey: Successful IoT projects start with a cross-functional team from IT, operations technology, security, production, logistics and finance. Process efficiencies from the combination of operational and business data come from connecting things and starting the data flowing. Cisco works with customers and partners to make early projects successful because results convince the naysayers to back more ambitious projects.
  2. Find the right partners: Partners from the horizontal stack are a given, but partners for vertical integration are essential. Most of these projects, except smart cities, are brownfield deployments with legacy infrastructure requiring integration. Cisco is not an industry domain expert. Success depends on working with the partners to integrate the legacy systems they built or migrating to new ones.
  3. Executive sponsorship: Change has antibodies that resist it. A chief operating officer, chief experience officer, or divisional CEO must sponsor the project to ensure success.
  4. Patience: The first projects are small without much revenue. You have to bank on the long term that the journey leads to more comprehensive implementation and eventually you will make a lot of money in the process. It is a very different approach than a traditional IT organization. It is much more complex with longer-term time horizons. You also have to play matchmaker, not only from a technology perspective, but bringing teams together who have not worked together before.
  5. Avoid science projects: A science project is an R&D project without the support of the line of business. For example, Cisco worked with an advanced architecture team for two years only to find that business had not bought into the project.

Cisco’s ecosystem of partners and expert innovators

Cisco’s approach as a trusted supplier of networking equipment is pragmatic. The company must partner for the domain-specific expertise to directly serve several customers in the diverse industries that are investing in IoT to build solutions. The company relies on Kranz’s IoT co-innovation centers and IoT partners to identify and develop new IoT solutions that may scale.

The co-innovation centers bring together customers with independent innovators that have the domain-specific expertise to solve white space IoT problems. Cisco located it's 10, soon to be 12, co-innovations centers in Toronto, Rio De Janeiro, London, Paris, Berlin, Barcelona, Tokyo, Korea and Australia. The centers are incubators to accelerate the cycle of proof of concepts, prototypes, pilots and scalable solutions. This R&D is important because there are few horizontal industrial IoT applications. IoT becomes verticalized very quickly, made granular by industry, and role — retail, logistics, production, etc.

The co-innovation centers engage with customer line of business and operations teams in specific industries concentrated in geographic regions that are concerned with business outcomes instead of technology. For example, the Berlin co-innovation center works with car manufacturers in Germany and continental Europe. In Australia, one is in Perth near the mining industry and one is in Sydney near the agriculture industry.

Cisco’s Industrial IoT partners have domain-specific expertise such as production, logistics, intelligent buildings, etc. Here is where IoT diverges from the internet. The partners established businesses long ago and are much older than the familiar internet and deeply entrenched. For example, the $200 billion manufacturing automation business sells proprietary and semi-proprietary technologies that lock customers into future purchases as their projects expand.

It takes the power of the end customer, or an industry-specific consortium of end customers, to change this dynamic. Kranz cited the consumer-packaged goods industries as an example of an end customer effecting change in the vendor ecosystems. A couple of years ago, consumer packaging goods leaders got together to drive a new packaging standard through all these strange ecosystems. Kranz punctuated this point, perhaps as a corollary to his five IoT success elements, saying:

“When a bunch of large customers gets together, they can drive these kinds of changes.”

Another example of the complexity of building industrial IoT businesses cited is intelligent buildings, which Kranz sees going through a big transformation in the next 24 months. He explained:

“We have to have a value proposition for the real estate developer: lower cost of operations, higher rents, better occupancy. Architects must specify our products. We must integrate, test and validate with the partner ecosystem so that you can go to the general contractor and tell him, ‘Here is our integrated value proposition. We have already done all this work for you, so your risk of project delay is low.’ We have to have a value proposition for everyone in the value chain.”

4 promising developments in IoT

Kranz considers these four things to be the most promising IoT developments of the past year:

  1. IoT security is finally being taken seriously. The industry is coming together as it did with Wi-Fi 15 years ago. CSOs are being pulled into the operational environments, implementing things such as segmentation and access controls in OT environments.
  2. Machine learning in IoT is gaining a foothold in areas such as preventative maintenance. IoT is an enabler. By connecting things, you get the data for machine learning. It is a natural extension to IoT.
  3. Cloud 2.0 has emerged, distributing the cloud. Distributing the cloud functions as close to the source as possible so that the huge amounts of data is captured in real time or near real time will enable many new control and automation applications.
  4. Most of the Fortune 1000 have adopted some measure of IoT.

Standards would accelerate IoT

When asked to identify one obstacle that if removed would accelerate IoT adoption, Kranz said:

“The lack of standards is wasting much time and resource. There are about 400 IoT companies with the value proposition of connecting proprietary end devices and abstracting them to applications. We need to have a consistent set of standards for a data frame. For instance, if we have temperature or vibrations measurement from different sensors, they should be consistent across all the sensors. Standards for how you transfer the data. Standards for getting the state of the devices. It is slowing us down and increase the cost of deployment by 3 or 4X.

“It is hard because there are a couple of hundred of standards bodies in IoT. The internet was lucky to have just a couple of standards bodies. If in the next 24 months we established a couple of standards around security and data structures, the IoT market would take off.”

The industrial IoT is not the consumer internet. Projects specific to one mega-factory can take years to progress from development to implementation. It is developing in industries where very large companies are willing to invest in R&D to prototype, but the results have to improve the efficiencies of operations to improve P&Ls and balance sheets rounded to the nearest million dollars, predicitive of a large opportunity, but with a longer timeframe than forecasted.

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