Writing about trends in technology can be somewhat subjective and perhaps even more so when we talk about trends in FM Tech. Functional requirements for FM Tech differ from regionto- region and are based on not just the nature of the technology itself, but also the maturity of FM business practices within a region, or even a country within a region.

Today technology in general is evolving faster than ever and technology within FM is no exception to this evolution. AI, Big Data, BIM, Blockchain, Drones, 5G Mobility, Wearables, Machine Learning/Data Driven Decision Making and IoT are phrases we hear in the media, but do we within FM understand how to practically apply this tech? Is this tech relevant to the fundamental needs of facilities managers in the Middle East, or just a line in a tender with no proper business case? As a global provider of FM tech FSI sees variations and differences in the nature, speed of adoption and level of investment in technologies. As a regional market develops in terms of FM practise, we see increased levels of investment and more maturity in the detail of the requirements demanded by a client from technology. We also see less “box ticking” procurement exercises simply to fulfil a tender and more though about applying technology as a differentiator.

FSI continually invests into researching new technologies. The Knowledge Group - FSI’s team responsible for product direction- guides our business about what new tech would benefit existing users and new clients, and what features should be developed and incorporated into FSI’s CAFM software suite in the short, medium and long term.

Perhaps the biggest trend we should be discussing today is integration between technologies and deriving value from the data produced by each technology. Collecting data is fantastic, but a wavy line on a graph is just window dressing without true understanding within a business of what it indicates. Integration is not new, as I am sure many of you will have heard me say previously. FSI started integrating with BMS systems at the time of our foundation nearly 30 years ago and we increasingly deliver integration with ERP, HR and other platforms as part of a CAFM project delivery.

Today, we see increasing value in connected FM technology eco-systems with CAFM as the hub. Essentially CAFM becomes the main data repository between business systems, often with much untapped data which could be used to benefit facilities operations. This is why FSI has, over the last few years, been investing in developing an integration platform to facilitate exchange of data between CAFM and other technologies; something we are now beginning to practically apply on projects here in the Middle East.

How we use the data we gather in FM is evolving. For example, AI can be really simple. Colour coding tasks to indicate their status against an SLA time is nothing new in CAFM, a RAG indication against a grid of tasks provides a live report of which work orders to focus attention upon as they approach their due times is a fundamental feature. This is great but does the completion time indication consider the estimated time it will take to carry out a given task? Or should the job be indicated red earlier? By applying further logic, such as the system automatically taking into account data collated from your workforce mobility solution, an insight which shows that engineers are historically never completing the work quicker than “X” hours, RAG indication thresholds should therefore be automatically adjusted accordingly.

Using data to drive setup of CAFM systems based on information gathered over time is also a trend we anticipate gathering momentum. For example, understanding and applying automatically a maintenance regime for each asset of a given classification when mobilising its data into CAFM, whilst also considering maintenance standards agreed between the business and its FM provider, is increasingly called for.

To be effective AI has to understand and be told in the first instance. Information such as what tag to allocate to a particular object in a photograph is therefore required. With technology such the FSI GO Asset Manager app, we are using human sensors to collect and classify data into CAFM systems. This is something which learning platforms find hard, but by gathering and classifying asset information and tagging photographs with data, learning platforms will benefit greatly.

Whatever the trend, we should not forget the importance of contextual interpretion of data by someone who understands what they are looking at. Collecting data is great, but we need to comprehend what in the first place is the point of the wavy line on a dashboard. Disruption is also something we hear about across the tech world and I have heard claims that traditional facilities software has had its time. Is CAFM heading to extinction? No, absolutely not. However, the way CAFM is used and the extent of its reach will continue to evolve. Long live modern CAFM.

(The Author, Adrian Jarvis is the Director of FSI Middle East)