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Practical IIoT

Practical IIoT


Taken from FMP Celtic Manor Event, October 11th 2018

Practical IIoT: Gaining Tangible ROI from the Industrial IoT

Adrian Turner - Director, IoT Innovation - Verisae, an Accruent company
What is the IIoT?

  • Interchangeably called the ‘Industrial Internet’, ‘M2M’, and ‘Industry 4.0’ amongst other terms.
  • Belief that machines are faster and more reliable at communicating their status and health than humans.
  • Applications are mission critical, rather than a user convenience.
  • Connected data is transmitted with high volume at high velocity.

‘As of today it is estimated that over 70% of industry leaders will have implemented an IoT solution.’

Gartner IoT Report (2017)

Today industry leaders already see the value in adding IoT to their tech stacks. It is important in taking these huge amounts of data and making them actionable.

Industry leaders are just now stumbling onto beginning blocks of IoT. They are connected some facilities and assets but the majority of our 10,000 customers are not currently utilizing a system. Many of them are just like you in this room today. They are either considering it or they are in early planning stages. They don’t know where to start and they do not know where to invest. I have seem customers in healthcare, manufacturing, retail, and education- most of these customers are just getting started.


‘The likelihood of achieving ROI on IoT projects drops as timelines extend beyond 12 months.’
Gartner, Avoid the ‘Danger Zone’ to Achieve IoT Project Payback, March 2018


IoT is a relatively new trend in this context. Some people are still experimenting with implementing them into their organization’s model. This means there will be some implementations easier than others.

I would argue though that any implementation project that has gone over 12 months was due to some basic project management missteps such as changing goals, partnership mismanagement, or scope creep. Often with our clients that first get started wanting to implement IoT – they go in with an idea and they end up changing their goals part way through due to new information discovered through implementation such as adding categories, wanting to add in new streams of data, etc.

This is the problem when you have a relatively new technology and there aren’t best practices and a well proven methodology of implementing it across the board. That is what makes it very different from installing something well known like space planning or a CMMS.

Common Pitfalls of IIoT projects

Four Signs of a Doomed IIoT Project

  • Scope Creep: The Art of the Possible makes it tempting to make continual adjustments to your plan. 43% of all projects are challenged due to scope creep (late, over budget and/or with fewer than the required features and functions. And scope creep can cost up to four times as much as initial development costs.
  • Insufficient Stakeholder Engagement: A successful project cannot be delivered in isolation.
  • Lack of Leadership: Everyone wants to own the cool IoT project, especially IT but you need to be strong.
  • Aggressive Scheduling: An IIoT has many interrelated dependencies so take a cautious view.

When you are first implementing you need to have a laser focus in order to achieve ROI. Select those few categories that make sense for your business and go for it. Expand later, don’t try to tackle everything in the first roll out. Some of our most successful clients have done 1-4 phase rollouts and expansions. Any IoT provider that is good at what they do will consult you in the process of year over year improvement and refinement.

Hallmarks of Success

  • Capture Quick Wins: Avoid the temptation for everything to be complete or perfect.
  • Challenge Assumptions: Test the business case at asset category. Enforce budgetary discipline.
  • Sweat the Detail: Success lies in the unglamorous. AI/ML, Predictive Maintenance & Reporting are the fruits, not the seeds, of your project.
  • Vendor Independence: Too many clouds makes a fog.

Behind the Scenes: Hardware Agnostic Predictive Analytics

The challenge is how do we break down smart machine data silos at enterprise scale? Some do with nice open protocols, some with legacy, proprietary protocols, but when you are faced with a diverse range of applications and business units, how can we bring that together into a common platform?


Modern estates are complex. Each one tells a story, but it’s a partial story and each contributes a chapter of the whole. Face with the challenge of this, what can we do to normalise that and bring them together? We started by bringing it all together in a logical way and then normalising the data.


Try not to fall for the temptation of the simple option of a full hardware replacement. The investments you paid on your devices can still pay dividends further down the line.


You then need to start making sense of the data through:

  • Advanced Alarm Triage
  • High Volume, High Velocity Telemetry

Then we have to bring it all back together into a suitable FM model which is dependant on many things.

Device Attributes

  • Hardware interdependence
  • Health & Status
  • Connectivity
  • Equipment Schedules
  • Digital Twins

Site Attributes

  • Geography
  • Area
  • Volume
  • Type
  • Energy Types
  • Operational Hours

This solved the problem of ‘how do we extract the most meaningful data from our existing equipment base?’ It also allows us to target investment and achieve some of the more ambitious ROIs. The process helps drive the investment case and insight and you can then start doing some interesting analysis off the back of it with real context.

How does this drive ROI?

  • Capture and monitor estate wide health in a single point-of-view
  • Drive down maintenance cost: The data works together to validate potential failures and reduce false positives.
  • Improve Contractor Efficiency: Contractors have all information at their fingertips, in real time.
  • Platform for Growth: Additional devices can be incorporated into the platform on a rolling basis.
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