Dusit Thani Hotel Networking Event Sponsor FM Industry Market Pulse - - PowerPoint PPT Presentation

NETWORKING BREAKFAST MORNING September 11, 2019 8:30am-11am Dusit Thani Hotel

Networking Event Sponsor

Hosted by the MEFMA Strategic Sub-Committee

Francisco Ramalheira Director – Business Development & Marketing, Enova (MEFMA Strategic Sub-Committee Leader)

FM Industry Market Pulse

MEFMA Strategic Sub-Committes

Regional Legislation and Regulation in FM – Networking event April 15th Industry Body collaboration and co-operation FM companies and Licensing requirements Regulation / Standardization of Regulations Best Practices and Innovation in FM – Networking event June 26th Framework document development Classification of buildings / businesses Innovation as a deliverable FM Industry Market Pulse – Networking event September 11th Value of Human Capital & Training in FM – Networking event December 12th

FM Industry Market Pulse

Regional Market Overview Geographies Segments Maturity Opportunities and Challenges FM Market Landscape Segmentation Evolution Who and How? Trends in FM Competitiveness Blockchain AI / Blockchain / Data driven decision making Energy Management Smart Facilities Flexibility and Wellbeing in the workplace

FM Industry Market Pulse

Regional Market - Overview*

Egypt – 4 Total market value – 1.6 biUSD Private – 56% and Public – 44% Inhouse FM – 80% Outsourcing as a single service KSA – 1 Total market value – 5.5 biUSD Private – 67% and Public – 33% Inhouse FM – 62% 8% of Outsourcing as IFM Kuwait – 5 Total market value – 1.0 biUSD Private – 63% and Public – 37% Inhouse FM – 50% 5% Outsourcing as IFM Bahrain – 6 Total market value – 0.8 biUSD Private – 67% and Public – 33% Inhouse FM – 42% 8% Outsourcing as IFM Qatar – 3 Total market value – 3.9 biUSD Private – 69% and Public – 31% Inhouse FM – 39% 10% Outsourcing as IFM UAE – 2 Total market value – 5.4 biUSD Private – 77% and Public – 33% Inhouse FM – 35% 10% Outsourcing as IFM Oman – 7 Total market value – 0.3 biUSD Private – 60% and Public – 40% Inhouse FM – 57% 7% Outsourcing as IFM

* Frost and Sullivan, 2018

FM Industry Market Pulse

Regional Market - Segmentation

* Frost and Sullivan, 2018

1000 2000 3000 4000 5000 6000 KSA UAE Qatar Egypt Kuwait Bahrain Oman

Market value [miUSD]

Commercial Institutional Public Industrial Others

FM potential growth to 2% of GDP KSA – 0.8% – market could double in size UAE – 1.3% – market could grow 50% Qatar – 2.2% – market plateau Egypt – 0.7% – market could more than double in size Kuwait – 0.8% – market could double in size Bahrain – 2.2% – market plateau Oman – 0.5% – market could triple in size Commercial – office buildings, retail, F&B, warehouses Institutional – healthcare and education Public – government offices, airports, ports roads, railway as well as utilities Industrial – manufacturing and primary energy operations Others – leisure, entertainment, sports, theme parks

FM Industry Market Pulse

Regional Market – Maturity (1/2)

• 1. UAE – the least fragmented market from the group, extremely competitive, with a number
• f developers / portfolio managers with their ability to perform the FM spectrum of services.

There is a clear push for differentiation, innovation and value added services, which could lead to a situation of market desaturation.

• 2. Qatar – there is momentum created around outsourcing where a IFM models are used
• ften across all segments. Market is clearly dominated by regional FM players with local

companies having been established with international groups via local partnerships.

• 3. Bahrain – a small and relatively competitive market due to the number of FM service

providers that is lead by the easy establishment of corporation. Most opportunities rely on the private sector where there is awareness about FM in general.

• 4. KSA – very fragmented market, where some commercial opportunities are still centered in

input based contracts. Opportunities for the FM market in the public sector rely more and more in output based contracts based on the vectors set by Vision 2030. KSA seems to be converging faster in the last years using the UAE as a benchmark.

FM Industry Market Pulse

Regional Market – Maturity (2/2)

• 5. Kuwait – a market that historically relied on input based contracts but with the investment
• n the private sector (notably hospitality and mix use developments) and the demand around

customer service improvements is driving positively the FM sector.

• 6. Egypt – a promising market for three main reasons: economic development, willingness to
• utsource and the relatively low level of proficiency on service delivery. International

companies have difficulty to compete locally and require a service methodology that offers value added services.

• 7. Oman – offers immense opportunity if all development programs remain on track. The

market is immature and local work force vacuum to the public sector pegged with low penetration of technology on the building sector remains a challenge.

FM Industry Market Pulse

Opportunities The regional growth – GDP set to grow between 2-4% Public but mostly private development and investment will continue to occur – which eventually creates opportunities in the FM sector Eagerness for “purchasers” to learn about and outsource FM services Demand for digitally enabled solutions Provision of added value services Challenges Competitiveness Market saturation Attract talent Change of law Geopolitical situation Divestment Regional Market

FM Industry Market Pulse

Competitor Landscape – Segmentation 7 main segments but often companies provide services beyond the traditional definition of FM

O&M Services (Hard FM)

M&E HVAC Mechanical systems Building fabric Fire detection and protection BMS Vertical transportation (…)

Support Services (Soft FM)

Cleaning Pest control Landscaping Security Reception services Catering Laundry (…)

Environmental management and compliance

Waste management Recycling services Energy Management Water treatment and recovery (…)

Value Added Services

T&C PAT testing Drone inspections Condition audit surveys Green building certification Indoor air quality auditing and monitoring (…)

ITC

Establishment

• f IT

infrastructure Maintenance of ITC systems System integration Digital tools development (…)

Property Management

Asset management Leasing Space planning Authorities liaising services Property acquisitions and disposal (…)

FM Consultancy

Delivery strategies Budget preparation and service charges allocation Design review Processes and Procedures development Development supervision Transitional services

FM Industry Market Pulse

Competitor Landscape – Segmentation Volume driven business (Hard, Soft and EMC) Across the 7 geographies portrayed we estimate the presence of over 100 companies Less than 10 companies operate in more than 1 country With some exceptions decision is made based on price - commoditization We estimate than more circa 90% of the FM market value is here Specific opportunities (Value added, ITC, PM, FM Consultancy) Limited number of companies because services delivered are specific Typically and because of the nature of the service delivery methodologies and market opportunity these companies

• perate across the 7 geographies

Commissions are of added value so decision making is based on technical capability and after sales support Market value is smaller but typically with better margins

FM Industry Market Pulse

Trends in the FM industry Competitiveness Purchasing pressure as led to a commoditization of the FM industry with companies having to optimize operating strategies to remain successful. Mature companies are adopting a proactive approach on the development

• f strategic partnerships, on value creation (rather than just service

delivery) and leveraging on the use of technology. Blockchain This disruptive technology, defined as a cloud-based, permanent, distributed digital ledger of activities between parties can enable real-time visibility and security in contractual obligations and accelerating transactions while enhancing accountability. Challenges remain with the transition from an non-existing or diversified information status into a fully integrated mode – structure, fields, language, permissions, etc.

FM Industry Market Pulse

Trends in the FM industry Artificial Intelligence AI has developed rapidly over the last few years with the major advances being in the area of “deep learning” techniques that employ multi-layer artificial neural networks to model complex real-world situations. This could lead to the adoption of AI to model complex processes with the aim

• f optimizing them, segregation of duties between human and machine

and allocation to what they do best, and development of complex predictive models that map solution scenarios. Energy Management With the rapid increase on utility prices, the environmental pressure around traditional solutions to generate utilities and with the creation of Super ESCO’s, utility management in general is a service required / offered by FM companies, creating multiple opportunities within the sector.

FM Industry Market Pulse

Trends in the FM industry Smart Facilities Buildings are evolving with the development of technology and the need of connectivity, becoming increasingly more efficient and easy to operate but increasingly more complex to maintain. This will lead to the need of different service delivery methodologies as well as the necessity to develop human capital competencies to address the new maintenance requirements. Flexibility and Wellbeing in the Workplace Smaller enterprises continue to be the predominant users of flexible workspaces but large organizations are continuously assessing how to accommodate a growing workforce and manage spend during times of transition, which puts pressure on the commercial models for service

• providers. Concurrently there is a growing demand for employee wellbeing

and the need to maintain proper indoor environmental conditions.

FM Industry Market Pulse

Key Takeaways and way forward Regional market: expansion of the knowledge it exists to geographies that are less well known, assessing and summarizing available information on the market. Work towards the vectors that can be addressed (e.g. talent development and applicable law watch). Competitor landscape: generation of a database (similar to that existing) but encompassing general information based on a set criteria to help those seeking services from the different segments to know who to approach. Trends in FM: regular assess the market for new trends, evaluate the penetration and adoption of new technologies / methodologies, and promote the discussions around what affects the industry.

The Potential of Artificial Intelligence in the GCC FM Industry

Alistair Stranack Managing Director

ROSMEAD

ROSMEAD BUSINESS CONSULTING

FM Leaders’ Perspectives on AI (Rosmead / / MEFMA In Industry Su Survey) Current sit situation

0.0% 20.0% 40.0% 60.0% 80.0% 100.0% 120.0% CAFM BMS Mobile solutions Remote monitoring Internet of things Robotics Artificial intelligence Always Frequently Generally Rarely Never

To

• wha

what extent was as tech echnol

• log
• gy incor
• rporated into con
• ntracts you
• ur fi

firm rm won

• n in

n the the pas past 12 mon months?

%

• f respondents

FM Leaders’ Perspectives on AI (Rosmead / / MEFMA In Industry Su Survey) Fu Future Im Impact

0.0% 20.0% 40.0% 60.0% 80.0% 100.0% 120.0% CAFM BMS Mobile solutions Remote monitoring Internet of things Robotics Artificial intelligence Critical Very important Important

 2018 survey %

• f respondents

Ho How w imp mpor

• rtant wi

will l eac each of

• f thos

those technol

• logi

gies be be to

• suc

uccessful FM FM bus busin iness over the the ne next 5 years?

FM Leaders’ Perspectives on AI (Rosmead / / MEFMA In Industry Su Survey) In Investment Pr Prio iorit ities

0% 5% 10% 15% 20% 25% 30% 35% 40%

• “Better use and utilization of CAFM, CMMS &

Mobile solutions through up-to-date applications. It helps to facilitates daily procedures, data analysis and customers trust”

• “CAFM with mobile solutions, and remote

monitoring are important areas. These allow

• ptimisation of human resources and at the same

time being effective. IOT, Robotics, AI are new to

• ur Industry and need to be studied further

before an investment is made”

• “Our focus is on Artificial Intelligence - advanced

analytics enabling intelligent situation recognition, prediction and autonomous service delivery”

• “CAFM, for control and coordination; Artificial

intelligence for the implementation of predictive and RCM techniques”

%

• f respondents

Wha hat do do you

• u con
• nsid

ider to

• be

be the the pri priorit ity ar areas for

• r technol
• log
• gy investment over the

the ne next 3 year ears?

FM Leaders’ Perspectives on AI (Rosmead / / MEFMA In Industry Su Survey) Ar Artif ific icia ial l In Intelli ligence in in FM

Yes

No: No: will ill tak ake long longer No: No: othe

• ther

r pr prio iorit ritie ies No: No: no not rele levant Don’t kno now

• “Machine learning will give us a better understanding
• f the behavior of tenants, guests and the building

itself, allowing us to create a predictive model as the basis for proactive - rather than reactive - actions“

• “I can see AI can take over at least 40% of the human

requirement in field workforce environment”

• “AI is very advanced technology which will take time

to incorporate with the industry. Not in 5 years, maybe in 10 to 15 years.”

• “I think in 5 years time they will be starting to be

present however due to the cost of upgrade I don't think they will be common place”

• “Buildings are not ready to accommodate the
• technology. Landlords are not ready to invest"

Do Do you

• u bel

belie ieve th that AI AI wi will l pl play a a sign gnifi ificant role

• le in

n the the FM FM ind ndustry ry over the the ne next 5 years?

FM Leaders’ Perspectives on AI (Rosmead / / MEFMA In Industry Su Survey) AI AI Ap Appli licatio ions

Predictive maintenance Energy efficiency Autonomous service delivery Planning & logistics Other

• “Predictive maintenance tools, assets

condition reporting and communication”

• “Understanding equipment usage and

performance patterns and take action before failure occurs. Also energy conservation, manpower and resource utilization”

• “Routine cleaning activities using autonomous

robots if it becomes economical. Ducts Cleaning, security services, helpdesk services, energy management”

• “Fault diagnosis so that field staff are

equipped with the right information prior to attending a maintenance call out”

Wha hat do do you

• u con
• nsid

ider wi will l be be the the mo most ben benefic icia ial l app applic ications of

• f AI

AI to

• the

the FM FM ind ndustry ry?

Pr Prim imer on

• n AI

AI Technologies Key AI AI Technologies

“Taking instruction” - Giving a machine detailed instructions as to how each task that it has to perform is to be carried out

Trad aditional com

• mputer pr

prog

• gramming

“Learning from experience” - Teaching the computer to learn from experience, then “training” it with historical input data and

• utcomes which it uses to predict correct
• utcomes when tested with new data

 Three key AI technologies – based on “neural networks” and “deep learning” algorithms that enable machines to learn from experience - underlie recent advances in AI: – Machine learning – Natural language processing – Autonomous robotics

Art Artificial intelligence

Pr Prim imer on

• n AI

AI Technologies Machin ine Le Learnin ing

High profile example: Goo

• ogle image cap

apti tioning FM-relevant application: Pred edicti tive mai aintenance The computer is “trained” to recognize the content

• f photographs and provide suitable captions

The computer is “trained” to recognise trends in multiple sensor readings and predict the need for maintenance interventions

• Prog

rogramming tec techniques tha that t en enable com computers rs to to lea earn from rom exp experi rience rath rather r tha than jus just taki taking di directi tion.

Pr Prim imer on

• n AI

AI Technologies Na Natural La Language Pr Processin ing

High profile example: Amazon Alexa FM-relevant application: Do Document scr creening an and cla classificati tion The computer can recognize and interpret unstructured verbal commands and initiate a wide range of applications The computer can recognise and interpret unstructured document content and screen for relevance

• Prog

rogramming tec techniques tha that t en enable com computers rs to to reco recognize an and resp respond to to com commands an and qu questi tions in n unst unstructured spo poken and and writt ritten form

• rm

Pr Prim imer on

• n AI

AI Technologies Au Autonomous ro robotics

High profile example: Tesl esla aut autonomous veh ehicles FM-relevant application: Dr Drone-based rem emote / ha hazardous insp nspecti tion The computer can determine a safe course to its destination, recognizing and avoiding dynamic hazards as they occur The computer can guide a drone to inspect remote equipment, recognising and avoiding dynamic hazards as they occur

• Prog

rogramming tec techniques tha that t en enable phy physical inte nteracti tion of

• f mac

achines with hum humans and and the the env environment t tha that t can can take take into nto acc account t un unpro rogrammed / un unexpected eve events ts

Ap Appli lication of

• f AI

AI to to Busin iness Pr Processes Enhance, Re Redesign, Tra ransform

• Use AI analytics to improve

existing processes

• Modify processes to divide

activities between AI and people - each taking on the activities they do best

• Create completely new

processes that are impossible without AI

• The value of AI applications is typically greatest where effective decision making is enhanced by consideration of

a large number of data points and / or the inclusion of complex multi-dimensional data sources such as video or audio feeds

Enhance

(c. 80% current use cases*)

Redesig ign

(c. 15% current use cases*)

Tran ansform

(c. 5% current use cases*)

* Source: McKinsey & Co 2018

• AI can impact business processes in three ways:

• The use of AI with large quantities of

high dimensional data – including audio and video feeds - can take existing systems to a new level of performance, e.g:

• Power grid optimization (utilities)
• Predictive maintenance

(aerospace)

• Elevator optimization (buildings)
• AI can reduce costs considerably by

dealing with routine activities, leaving people to pick up more complex or challenging situations, e.g:

• Call centre optimization (financial

services, transportation)

• Document analysis and

classification (legal services)

• CCTV monitoring (security)
• The ability of AI to analyse and make

predictions based on high dimensional data inputs is enabling the development

• f entirely new business processes that

were previously impossible, e.g.

• Service failure prediction (airports)
• Autonomous inspection and parts

delivery (shipping, oil & gas)

• Call sentiment analysis (insurance)

Ap Appli lication of

• f AI

AI to to Busin iness Pr Processes Use se cas ases in in re rela lated ind industry se sectors

Enhance Redesig ign Tran ansform

• Predictive maintenance
• Spares stock level and distribution
• ptimisation
• Building energy / utilities

management

• Autonomous inspection of remote /

inaccessible / hazardous areas

• Call centre optimisation
• Automated dealing with

standard questions / requests

• Escalation to specialists
• Autonomous delivery of routine

services (e.g. cleaning, security)

• Automated management and update
• f standards, manuals and

performance records and reports

• Service failure prediction and

avoidance

• Autonomous distribution of spares and

tools to jobsites

• Customer / end-user interface

enhancement

• Tailored service offerings
• Sentiment analysis in

interactions

Ap Appli lication of

• f AI

AI to to Busin iness Pr Processes Po Potentia ial l FM FM ap appli licatio ions

Enhance Redesig ign Tran ansform

Ap Appli lication of

• f AI

AI to to Busin iness Pr Processes Im Implementatio ion chal allenges

Ch Challe llenge Miti itigation 1. Inadequate / poor quality data capture

• Policy / standards initiatives
• Increasing availability of IoT connected devices / remote sensors
• Wider cultural change in industry recognising value of data analytics

2. Lack of historical data for AI training

• Leverage international data / experience
• Initiatives by Government / Industry associations to consolidate training data

sources

• Advances in AI algorithms reducing “training” requirements

3. Lack of decision “explainability”

• Developing codes of professional practice
• Dual / structured decision-making

4. Investment economics

• Focus on areas of greatest marginal AI benefit
• Performance contracts to reward productivity improvement
• Co-investment / gain-share arrangements

PANEL DISCUSSION

Trends in Facilities Management

Moderator:

• Abid Ali – Operations Director, Apleona HSG

Panelists:

• Abhay Bhargava - Director Industrial Practice – MEA (Regional

lead FM Advisory), Frost & Sullivan

• Adrian Jarvis – Director, FSI FM Solutions Middle East FZ-LLC
• Alex Davies – COO, Dubai Properties
• Mohamad Abou Laban – CEO, Deyaar Facilities Management LLC