Is IoT stuck in the swamp ?

(about the struggle to focus on Total Cost of Ownership (TCO) in IoT)

It feels like in the second half of 2023, everyone in the IoT industry is longing for the start of a new year. IoT budgets are being frozen or cut, and even the LinkedIn bloggers who enjoy entertaining discussions about which IoT technology delivers the best 0.1% battery performance have gone silent.

AI is the new kid on the block. The IoT honeymoon is over. It is time to deliver.? But what exactly is IoT supposed to deliver that M2M hasn't delivered for the last 20 years??

The essence of what lies behind the hype, behind the promised revolution, is the promise of cheap data from low-cost sensors with the ability to transform business process efficiency.

Two flavours of IoT

This post takes the perspective that the LPWAN bubble is the only IoT technology that has the potential to drastically reduce the cost of data, and spark a revolution in process innovation vs a normal evolution of M2M.

This 2nd IoT bubble is occupied by cloud service providers/telecom operators and focused on connected factories/machines.?

Both worlds have very few touch points, use different languages and face different challenges.?

Focus on Total Cost of Ownership (TCO)

IoT has not yet delivered on the promise of cheap data. More than 75% of IoT projects fail to scale.? So let's look at the success of IoT projects from a different angle:?the CAPEX cost of IoT devices is 20% of the total TCO of data, the remaining 80% is about process cost of getting and keeping these IoT Devices in place.?

Sure, battery life plays a role in how many times devices need to be replaced in their lifetime, but within a 10-year lifetime of a sensor, let's assume that battery replacement will be part of the maintenance cycle.? Let's park the discussion about the ultimate battery performance parameter.

This shift in focus on the 80% process costs exposes the real challenge of IoT projects: getting "Device Operations" right is a key discipline to develop for scalable IoT Projects.? ?Some of the causes for inflated process costs are:

• Planning: manually sourcing the metadata at the planning stage vs tapping into existing systems (ERP, EAM,...)
• Order/Device Data Handling: manually handling IoT device data related to (1) order quantities and delivery locations, (2) security keys transfer, (3) pre-registration in IoT platform leads to significant direct and indirect (errors) project overhead.
• Installation and Onboarding: lack of E2E project transparency makes project controlling and dispatching an art form. Project completion rates, service partner performance KPI's and overall SLA parameters are at best an educated guess.
• Error Correction: When managing complex IoT projects across multiple chains of command, error correction becomes difficult as there are no 'eyes on the ground' during installation. Manual enrolment processes are prone to error.? Project documentation is required to avoid operational chaos.
• Maintenance: IoT devices often fail to meet their datasheet specifications and require mid-life replacement.? Lack of documentation and ad hoc processes often lead to operational chaos both in the field and on the IoT platform hosting ghost devices.

It is no surprise that Metering Projects top of the IoT Use Case charts as they are implemented on top of a existing process landscape (in utilities) of rolling out and replacing meters.

The IoT Enthusiast?

Making Enterprise IoT work means getting teams from Engineering, Operations and IT to work together towards a common 'cost of data'/TCO goal.? It is often a transformational challenge that requires breaking with traditional methods and system limitations and working across the existing silo's in organisations.

In most organisations, IoT initiatives start with an IoT enthusiast, an engineer with a strong belief in the power of IoT, its technology and its ability to measure and control.????

At the C-level, Cloud service providers and telecom operators have saturated executives with IoT-stories of factory automation and AI-business transformation.? What they are really selling is connectivity and cloud services.? Enterprises are rightly very wary of succumbing to this temptation.

IoT enthusiasts that are lucky enough to get facetime with the C-Level about an IoT Project idea, are faced with a completely different perception of the topic and risk being classified as side project, rather than part of a transformation strategy that digitises processes and tools.? They are first in line to be on the receiving side of budget cuts once the quarterly targets are not looking as promising as they should be.

Status of the IoT Industry

Cloud service providers are struggling: Microsoft fired its entire IoT team, Ericsson sold its IoT division, Google closed its IoT unit,....

The LPWAN ecosystem is bracing itself. Platform vendors are cutting costs to reach profitability, consolidation is on the horizon.?

Customers are bracing themselves for an economic downturn.? Employees, burned out from team meeting marathons, barely have the capacity to manage today's problems, without the luxury of taking a strategic view of what future challenges lie ahead.

Deviceflo

Deviceflo has been trying to swim in this swamp for the last 3 years, preaching a TCO approach to IoT projects.? With Deviceflo's tools and process orchestration, the TCO of IoT data can be reduced by 25-50%, giving the CIO a tool to embrace the world of IoT and have a discussion with the COO about IoT driven process optimisation.??

The reality after 3 years is that the daily struggle of the IoT enthusiast is too great, and in the absence of strategic support from C-level, the solutions that are implemented satisfy the immediate need to create a data stream, with no plan for organising maintenance processes that can meet SLA requirements and be outsourced to service partners.??

This is frustrating, but unfortunately the reality of the IoT market.