Menu
​How partners can build strong ROI business cases for IoT projects

​How partners can build strong ROI business cases for IoT projects

Despite end-user enthusiasm, a confused channel remains challenged by market immaturity.

Interconnected, intertwined and interlinked - the Internet of Things to edging towards mainstream adoption, creating opportunity and obstruction in equal measure.

Apparently, the opportunities are endless. Apparently, end-user enthusiasm is through the roof. And apparently, partners are primed and ready to profit.

But a quick channel reality check paints a problematic picture.

Projects are failing to get off the ground for a myriad of reasons - CIOs and line of business leaders are quarrelling, returns on investment are seldom seen and confusion between vendors, channel partners and end-users continues to run amok.

The end result is a channel desperate for clarification.

But while a true definition continues to evade, partners are now beginning to grasp the concept, the opportunities and crucially, the challenges, of making IoT a viable business strategy.

Regionally, 25.5 per cent of businesses have launched specific solutions, with 62 per cent of companies reporting IoT as strategic to the organisation.

With Australia and New Zealand included, IDC research shows that a strong partner network is critical to effectively rolling out IoT projects, alongside the ability to offer a holistic IoT solution and having a planned IoT roadmap.

In outlining the top three criteria for businesses when selecting vendors across the region - and subsequently channel partners - the next challenge centres around navigating such as increasingly complex industry.

An industry that plays host to an expanding constellation of devices, that in turn creates confusion for all areas of the IT supply chain.

“The Internet of Things (IoT) needs a standard, everyone agrees on that,” Ovum research analyst, Michael Azoff, acknowledged.

“But the reality is that there are simply too many players vying for their standard to dominate, and the result is the highly fragmented market we currently face.”

Despite this handicap, Azoff said the case for IoT projects is often good - many organisations plunging in are saving millions of dollars, or creating new opportunities and revenue streams.

“To avoid building systems that do not deliver returns due to the immaturity of the market, the business case return on investment (ROI) has to be strong at the conception,” Azoff explained.

“The reason for embarking on an IoT investment has to stand on its merits, use a suitable standard from the leading contenders, and address key questions, including whether it will solve an existing challenge, improve how you do business, or generate new income streams.”

If so, Azoff said the risk of building a legacy system is mitigated because the outlay will be reimbursed by the solution.

“If the world goes on to adopt a different standard from the one you adopted, it will matter less because your solution has recouped the original investment,” he added.

Do not wait for the IoT market to mature

For Azoff, the IoT market fragmentation will cause many potential users of the technology to wait for further clarity and a winner to emerge.

“However, the many IoT alliances and their competing standards currently show no signs of reducing in number,” he cautioned.

Major technology companies, such as Cisco, IBM, Intel, PTC, and Samsung, are members of multiple alliances, including the Alliance for the Internet of Things Innovation (AIOTI), Allseen Alliance, Industrial Internet Consortium, Internet of Things Consortium, and others.

But Azoff believes that waiting for such clarity to emerge will forego the advantages of entering the market today, while the wait could take a decade or more.

“Ovum’s advice is therefore to build a business case based on the current technology status, pick a standard that has good industry support so you are not locked into a single vendor, and ensure the numbers add up within a reasonable period,” Azoff added.

“The ROI should justify making the IOT investment today.”

IoT and cloud-native technologies are a perfect match

Currently, Azoff said the cost of building IoT infrastructure has never been cheaper, with sensor and microprocessing component costs at their lowest, while the computing requirements to run the system can exploit new-generation cloud-native technologies.

For example, many IoT use cases involve responses to events, and event-driven compute cloud services are now available, such as AWS Lambda and IBM OpenWhisk, which offer low-cost computer processing without the need to spin up servers.

“The infrastructure is completely automated and hidden, hence its alternate name of server-less computing,” Azoff added.

“Modern application architectures such as microservices are a perfect match for event-driven IOT use cases.”

AI opportunity

Azoff said IoT can also generate big data, and machine learning-based analytics is ideal for mining the data and has been a proven use case in practice for some years.

However, the rise of intelligent programming with deep learning opens up further opportunities for automated intelligence.

“Remote systems can be better managed and controlled with intelligent systems that provide greater opportunity for IoT projects,” he added.

As explained by Azoff, deep learning proved itself in 2016 when Google Deep Mind’s AlphaGo beat world Go champion Lee Sedol in four games to one.

“This AI technology trains itself to learn new skills,” he added. “The combination of big data generated by IoT and advanced AI promises to transform whole industries.

“For example, cameras on automobiles can update global 3D maps in real time, with AI used to ensure quality control, and decide which images collated from multiple vehicles should enter the master map.”

Follow Us

Join the ARN newsletter!

Error: Please check your email address.

Tags IDCovumInternet of Things

iasset.com is a channel management ecosystem that automates all major aspects of the entire sales, marketing and service process, including data tracking, integrated learning, knowledge management and product lifecycle management.

Show Comments