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CAFM
Internet of Things (IoT)
Software & Systems

Without data, decisions are just opinions

Open-access content Tuesday 27th April 2021
Authors
John Green
web_smart-tech-office_credit_zhu difeng_shutterstock_691348693.png

Shutterstock

As FM businesses try to avoid the race to the bottom with increasing competition and higher customer expectations, smart data-driven decisions can make the difference and deliver a significant operational advantage, explains John Green.

Since the Covid-19 pandemic began, sites have become more difficult to run due to social distancing, remote teams and potentially furloughed staff. Data is a key resource that can enable sites to keep running, and asset management systems that use smart and sustainable technology play a crucial role in day-to-day operations.

As CAFM systems evolve to keep pace with the requirements of the “new world” of work, it is becoming easier not only to capture data, but to analyse and interpret it to provide the insight you need for optimum decision making.

Traditional dashboards and KPIs can help with this; however, the content is typically lagging, meaning that they look backwards rather than forwards. Now, the industry is looking at how to use data to make automated decisions with artificial intelligence (AI). AI has sometimes been viewed cynically in the past, as the effort and investment required to deliver the desired outcomes has been unacceptably high.

AI drives efficiency and cost reduction

This dilemma can be overcome by identifying realistic outcomes, and focusing on simple achievable tasks that deliver operational cost reductions. By identifying key data and applying some basic algorithms, we can dramatically alter actions as part of our operational delivery.

When planned maintenance is established in a CAFM system, for example, it is usual to set up estimated time and planned materials against an activity such as servicing air conditioning units. As time progresses, maintenance activity will be regularly carried out on the AC unit and the mobile technician deployed to the task can accurately capture the actual time taken to do the work. 

So we may have estimated the planned work to take four hours but in reality it never takes longer than two hours. The CAFM system can then be configured to automatically update its estimated times to better reflect the actual time. This means that future planning of this type of work will be much more accurate and drive efficiency. The data is invaluable for work-winning activities, allowing cost planners to be more precise.

AI-based monitoring reduces human intervention

When AI is combined with remote monitoring, it can help organisations identify the most important alerts among hundreds generated daily from critical assets. This allows FM providers to transition from less efficient preventative maintenance towards predictive maintenance.

Some of the most common forms of remote monitoring come from the integration of SCADA and BMS systems, along with more recent developments in IoT devices. 

As remote monitoring software feeds data to the asset management software, AI can be used to recognise the right time to act. A work order can be automatically created, scheduled and dispatched to the most suitable operative or subcontractor, using automated scheduling software. Problems with assets can be resolved before they cause the equipment to break or significantly under-perform – resulting in less reactive work and more uptime, leading to significantly lower costs and increased customer satisfaction. 

This data also allows AI to provide greater insight into the root causes that lead to asset failure. This can be useful for Capital Asset Investment Planning and Estate Management, enabling organisations to better forecast cost, depreciation and exit plans.

Improved first-time fix rates

Similarly, the history, documentation and photographs of work on assets can inform planning if a particular tool or part is likely to be required, ensuring that the attending engineer is prepared with the necessary prerequisites prior to the visit. This dramatically increases first-time-fix performance, and helps organisations meet their SLAs and avoid penalties. EAM systems can target this information, using mobile apps, to make it readily available to maintenance teams in the field.

With these kinds of solutions, you can leverage AI and Business Intelligence tools to serve your most important data and insights directly to the people who can make best use of it. This puts smart facility management strategies in place, helping to tackle the coming months with confidence.


John Green is head of solution architecture at Peacock Engineering


 

Filed in:
Explainers
Also filed in:
CAFM
Internet of Things (IoT)
Software & Systems

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