Category: Operations & Maintenance

The argument between Open Standards Data Architecture and Proprietary Ecosystems of Application and Hardware has been heating up recently, especially as we now have more options to choose and customize the facility’s technology stacks. 

Similarly this argument resembles the one we all witnessed, when Google came up with android to compete with the Apple ecosystem, and that turned out beneficial for both the competitors, and more importantly for the users, as it clearly laid aspects such as security, connectivity, exclusivity and functionality for everyone to choose as they want. 

Well, when it comes to commercial building space, the term ‘separate data layer’ has been at a central point of many discussions recently.

In a typical building, one has systems like BMS, BAS, Energy monitoring, and metering systems to collect energy and asset-related data. Then the integration layer where a set of hardware communicates and transfers the data from individual sources to a designated location. Further historian layer stores time series and metadata on the database. Then the individual 3rd party tools in the application layer fetch the read-only data from the historian layer, processes it (Edge/cloud), and provide insights in the dashboard. Users then make decisions whether to stop there or put in the control system for complete automation.    

Now there are some limitations when one chooses to go with the above stack. That is, the entire stack often comes with the vendor ecosystem, and if you are not getting the expected results from the application and choose to move on with another, one might lose all the data that has been tagged before and restart the cycle once again from the scratch.   

Addition of data layer

Addition of the data layer is a way to make the stack open and available for the data lake. That’s separating the historian layer from the application layer and maintaining the raw data tags in the data layer. This way one need not follow the vendor’s ecosystem for one application only but can prefer another set of applications as per their requirements evolve with the period of time.

How does this work?

Whenever data is stored in a historian layer, it comes with a common auto-tagging so that one will have the complete library of asset and location-specific datasets ready at all times (It need not be structured with a proprietary application). 

Later one can add applications to it that will fetch in required data from the data lake and provide the insights. If not satisfied with the insights or the capabilities then one can be moved to another application without disturbing the data set up.

Key Benefits of Having the Data Layer:

1- Reducing the dependencies on vendor ecosystem:

One can have the flexibility to look into the data whenever you want something that’s difficult with the vendor’s stack. You would not need to subscribe to another application or tool to access your data. 

2- Easy to switch:

Don’t find the insights useful anymore? Or have you Identified the loopholes in the application which the vendor is ignoring or are not able to fix? With the new stack, you can move on with the new application whenever you want without losing the data structure. 

3- One data model for all:

It creates a single source of truth by applying the one data model for all the applications promoting interoperability.

For a facility manager, one of the important tasks is to keep the asset and operational data accessible to the O&M team for retro or predictive analysis. And with the separation of the data layer he can share it with the team as well as use it for any 3rd party asset performance management application trials. 

Sounds perfect and easy right?
Well, that depends on some critical decisions and aspects you should consider before selecting. 

1- Increased Complexity:

As you are customizing your tech stack it will increase the data complexity as your dedicated IT team would need to get involved in commissioning or decommissioning of the third-party applications. Needless to say, it will also increase the time to get started with the new application.

2- 3rd party application’s use of data:

If the application is expecting a different set of metadata or tagged data then your standardization would not work. There are few applications available that can follow the standardized asset tagging. 

Well, every facility management team has different goals, capabilities, budget and technology roadmap to follow and as far as the tech stack is concerned, tenant’s expectation, contract terms and team’s vision to create an ideal facility plays an important role. All the insights shared in this article including the pro and cons of a separate data layer should be evaluated thoroughly with the team and then the decision should be taken. 

Introducing a separate data layer will improve the ability to experiment with various use cases and applications (such as analytics, which leveraged the existing data layer and sit on the top of the value chain) ultimately adding greater flexibility and scalability to the tech stack.

In July this year, IBM joined hands with one of the leading facility management firms CBRE, to provide AI-based maintenance services to CBRE’s data center clients. And this is not the very first  CBRE’s first partnership with a tech giant to come up with a collaborative solution. They have worked with Microsoft for interactive people management applications, and power platform as a workplace solution, and if you look at CBRE Global’s past investments and partnerships, they have done multiple tech acquisitions along with in-house dedicated DT Centres. They also have numerous applications listed under the CBRE Vantage, a suite of enablement technologies. 

Overall they have collaborated with numerous technology providers to try to fit into their client’s requirements needless to say they have built, brought and partnered with third-party tech providers whenever is necessary. But is this strategy applicable for everyone across the verticals? What are the layers, CXOs would need to unwrap before reaching the decision?.

Facility management teams never before have faced issues they have faced like this year with tech integrations when adding up their tech stack with workplace management and remote asset monitoring applications. Some of the buying decisions were obviously Adhoc which came in with a response to safety and social distancing protocols. But now when things are settling down with the new normal in most parts of the world, they can certainly ponder upon their future tech stack and suite of new services and decide whether they should build them or buy them?

Discussion on Build vs buy or an argument over the same, is not new to facility management firms, which is running on outsourcing tasks for their partners. It has evolved from an in-house to consolidated services and ultimately, integrated facility management solutions, that have excelled in making partnerships and managing people. However, when it comes to deciding the digital strategy for themself and their clients it has been facing fierce competition from the incumbent tech startups and consulting firms. 

Easier said than done, for an FM firm to decide on building a suite of applications or subscribing to one can be a far complex decision, there are multiple layers of hierarchy and deciding factors that come into the picture. It’s Obvious, there can’t be a common strategy that fits for all despite the well-known pros and cons of each decision. 

Let’s assess the aspects that help in simplifying the decision: 

Strategic roadmap for the FM tech stack

For a tech-enabled FM firm, it’s Important to do research on the ideal tech stacks for different types of clients regardless of the client’s expectation from one. For operations and maintenance, that includes data acquisition hardware, data storage & processing applications, visualization and control mechanism. 

• Understanding client’s pain points, 
• leveraging internal and external capabilities to come up with a solution
• Standardizing an application/software based on demography and competitive market conditions
• Keep experimenting with a healthy combination of partnerships and a homegrown application suite        

For a CIO, building an application or buying one is not like head or tail decision. here are two primary aspects that involved in each decision 

1.Strategic decision

Competitive

A set of applications or services providing the unique value proposition to the client, that can help them secure a contract or help them estimate efforts for successful bidding.  

Leverage

Partnership with a techfirm to create an ecosystem of applications, based on their platform which can only be available to their clients. Leveraging FM’s understanding of operational needs and domain expertise of technology partners.   

2.Technical/functional decision

Competency

In house team of data analysts, programmers, SMEs, and business analysts to research, ideate, test and successfully deploy a new application

Well that’s not all, there is one more aspect to simplify decision making, that is Lifecycle analysis of the application/ software

According to Gartner’s Pace-Layered Strategy, which is used to categorize applications in three layers based on complexity, usage 

• Systems of record: 

These applications help in building the foundation to  technology stack and the capabilities of a firm. These are roughly standardized across the sector and leave little scope for differentiation. For example, in facilities BMS, ERP and CMMS would be the bare minimum yet fundamental tools required for effective O&M activities.    

Suggestion: No need to build it in-house, can be brought from a leading vendor.

• Systems of differentiation: 

Solutions that define one process from another, or give a competitive advantage to efficiency and scale, for example – two different Analytics applications that use similar asset data inputs and provide different insights, one of the application, provides more accurate and contextual recommendation because of the unique logic it possesses. 

Suggestion: Can be customized/ white-label or build depending on the decisional framework. 

• Systems of innovation: 

A unique approach that has never been tested or experimented with, application or technology that is in the nascent stage but holds promising use cases and can only be deployed as PoC.

For example, digital twins or AR-based remote asset management applications 

Suggestion: regardless of the client’s needs forward-thinking FM firms invest a lot in creating such a niche application to project their vision and capabilities.  

In this Gartner model, each layer suggests whether one should build, buy, or partner with a technology vendor for. 

Building on core competencies and niche areas and outsourcing or buying standardize applications that are responsible for building a basic data infrastructure. This way CIOs can follow a pragmatic approach to decide on build, buy or partner. 

Want to know SERCO’s take on the Build Vs buy argument? Attend this virtual session of Re: CONNECT organized by UNISSU (sponsored by Xempla) on Jan 07th, 2021 REGISTER HERE

The scope and depth of digital twins are far different than the asset management or facility management platforms. They do now have specified modules like the lateral ones hence digital twins are mostly referred to as products, platforms, or processes. This differentiation depends on the aspects/ use cases that have been in focus likewise the purpose to implement it.

In the previous article, the building blocks of digital twins, and when to opt for them were discussed. In this, a deep dive into the classifications, finding out what’s suitable for your facility is being shared. 

Digital twins could be available from basic to complex nature and organized into 3 major categories. The digital twin may use 2D or 3D simulations, a mesh of IoT devices, local or 4G networks, and another bunch of technologies such as blockchain, edge computing, cloud computing, etc. Depending on its complexity, each digital twin may have access to past, present, and future operational data and increased predictive capabilities

One cannot reinstate enough on the fact that whatever the platform or application is chosen for developing digital twins, has to improve your decision-making ability. Regardless of autonomy, one should be in a position to reduce unplanned breakdowns, improve efficiency, and ensure a pleasant tenant experience.

The digital twin and its ecosystem may vary in scale and complexity for size and scope. 

As per the requirement categorising goes as mentioned below. 

Assets twinning:

Operational data from critical assets such as chiller, cooling towers, or elevators are continuously collected and monitored on a central platform. Design specification from the OEM is used to build the replica of the asset. Note that, it is not necessary to have the 3D model. However, It should exhibit the physical characteristics of the assets in most of the cases and could be programmed and displayed in a 2D. 

From the digital twin of the assets, one will be able to analyze changing patterns and answer to

• What are the failure modes? (How does an asset break)
• What are the consequences?
• What are the mitigating recommendations? 

Important KPIs for a digital twin of an asset can be listed as Availability, Uptime, Productivity, Cycle Time, OEE Lead Time, and Equipment Failure Rate.

Since the digital twin can communicate and control the physical asset it can help monitor and optimize the performance of individual assets with a greater level of autonomy.

System twinning:

Moving  from asset to a set network of assets, such as HVAC networks where operations of AHU and chillers are interlinked and can be affected if one of them deviates from its course. Data Inputs in such twins are extended to external factors too such as room temperature or humidity. Hence the model has to respond to all the possible scenarios where external parameters drive the change.    

System twinning allows facility managers to operate the entire system (collection of dependable assets) to achieve a result at a system level. They combine individual Asset Twins and provide the opportunity to check how individual assets work together. 

A network of systems:

Twinning the network of systems optimize the operations involving asset data, building’s design aspects as well as occupancy and workflow processes. These types of twins process complex data, exchanges by harnessing real-time data, and the platform adds value by optimizing the performance to drive savings through actionable insights and predictive maintenance. 

Facility management teams can use the platform to learn about how occupants behave and automatically predict future needs.

The maturity metrics of digital twins  

Scope and usability of a digital twin is evaluated based on 3 parameters

Autonomy: 

It can be defined as the ability of a twin to operate independently without any human interventions. For example, by predicting the cooling demand automatically changing the chiller sequence to an optimum level. 

There is always a provision to select from semi autopilot, manual or complete autonomous mode. However, in most cases facility operators go for the semi autopilot mode where routine activities are controlled by the system while for the critical assets operator receives notifications and alters on maintenance tasks whenever an issue arises. Ultimately one holds the authority to plan and act on it at the right time. 

Intelligence:

Intelligence can be defined as the ability to execute multiple logics. It can also quantify based on the processing or computing speed of the system. As you go up from asset twinning to network of systems you would need higher computing capabilities as the complexity of the logic goes up when multiple systems are involved.  

Learning:

Self-learning ability of the system remembers historical tasks and influencing parameters to create possible scenarios and suggest optimum settings. Twins logic is based on Machine learning and Artificial intelligence which help them to automatically learn from data to improve performance without being explicitly programmed to do so. 

There are several stages of advanced learning, however only a network of system or process twins need such ability. Asset twinning can easily be processed without self-learning features.

As you go up from assets to network of systems, importance to feedback and prediction increase. At higher levels, machine learning capacity, domain-generality and scaling potential all come into the picture. 

When to settle?

The digital twin allows “What if?” scenarios to be run automatically to determine possible strategies that optimize resource usage. A critical part of decision making can be taken care of by the twins and on-site facility management teams can then review the recommended strategies to assess the impact of each recommended approach. 

By now one would have realized that digital twins are continuously evolving in terms of intelligence and applications. There is a high chance that your first one might just set the foundation for the latest to come, hence it is wiser to focus on scalability and start with asset twinning and once you see the expected outcomes go for the entire network of systems.   

Want to explore about Asset Performance Strategy for CRE? Attend the virtual session Re: CONNECT organized by UNISSU (sponsored by Xempla) on Jan 07th, 2021 REGISTER HERE

Recently the world has witnessed many climate-driven disasters like wildfires in Australia & California, floods in Africa, cyclones and heatwaves in India. Amidst all of these, there are a couple of announcements that came out surprisingly well for the environment and future businesses. In October the EU passed the bill that makes net-zero emission 2050 target, into law. With that announcement, Europe became the first continent to aim for carbon neutrality by the end of 2050. Besides the EU, one of the recent reports published by the new climate institute, the number of commitments to reach net-zero emissions from local governments and businesses has roughly doubled this year, that includes some of the leading businesses and companies with combined revenue of over $11.4 trillion. Vowing to net-zero carbon emission, the biggest and leading companies like KPMG, JLL, Capgemini or even Siemens have committed to carbon neutrality or net-zero by 2030.

Net-zero as a term has been there for quite some time. Describing it with emission of carbon footprint it can be described as the reduction in the demand for energy and materials to a level that can be met solely by resources that do not emit greenhouse gases. In simple terms, it is a function of resource consumption during the design or construction and the operational phases.

What does net zero mean for CRE?

As per the Paris Agreement signed in 2016, most of the private and public listed enterprises have committed to achieve carbon-neutral or carbon positive, science-based targets between 2030 – 2050. As a known fact, buildings are responsible for almost 40% of the world’s total direct and indirect CO2 emission, in fact buildings in the USA emits over one-third of the greenhouse gas emissions, which is more than any other sector of the economy. 

Evidently, a larger part of the net-zero commitment comes under the commercial building spaces and supply-chain (warehouses to mobility). Companies in the IT, retail, consumer goods manufacturing and financial sectors are focusing on developing a portfolio of net-zero carbon buildings and also ensuring, new buildings to operate at net zero carbon by 2030 and existing buildings by 2050. That’s a humongous task considering that almost 80% of the buildings for 2050 have already been built.

JLL was the first property consultancy in the UK to sign the WorldGBC’s Net Zero Carbon Buildings Commitment (NZCB) in 2019. Later they went ahead and announced a global net-zero carbon building commitment which covers a portfolio of 460 buildings with a total floor area of 474,967 square meters. 

Eventually, if developed economies want to follow the path of net-zero carbon then they will have to focus on the buildings, specifically commercial real estate, where most of the resource consumptions can be controlled and monitored in a better way. 

Where can commercial buildings apply brakes on carbon emissions?

Carbon Emissions by the buildings can be seen in two phases

1. Design and construction phase (short and one-time)
2. Operation

In most of the cases, carbon emission during the construction phase makes a significant contribution – between 30% to 70% of a typical building’s total lifecycle emissions considering the selection of the raw material or any resources used for construction, and design aspects of the building being the most critical part of the process. This type of emission is termed as embodied carbon emission. Since most of the portfolio of net-zero committed businesses consist of existing buildings, the focus is on the emissions that happen during their operational phase. 

Building’s operational aspects that are associated with unwanted/extra resource consumption

• Operational efficiency: Inefficient assets, lack of monitoring & control systems, and the mismanaged workforce leading to higher energy consumption

• Asset life cycle: Poorer maintenance practices can severely compromise the asset life cycle ultimately leading to uncontrolled energy consumption or new asset installations 

• Demand management: Not knowing the incoming demand inflow could lead to mismanaged assets and their capacity. This could cause higher energy losses due to unplanned chiller sequencing.  

• Tenant’s behavioral aspects: It has been observed that the environmental aspiration and comfort expectation does not go in hand causing higher resource consumption than the expectation. Misaligned priorities and improper communication on sustainability goals make policy or the implementation weaker.    

Net-zero turning into reality or a chase to the Race to Zero campaign?

Initially, net-zero emission targets were more aspirational than practical in nature and there was no technology blueprint or policy framework available to support them. But the recent market-driven approach, climate-conscious thinking is not only enabling faster adoption of such practices but also motivating enterprises to race to net-zero.          

Changing perceptions:

• Awareness of operational environmental impact is increasing among some commercial occupants, particularly larger organizations with internal sustainability commitments. Although it will take time for mid-size businesses to adopt carbon-neutral practices, certainly we can see the change in perception.  
• There is this constant fear that the Carbon intensive assets may become “stranded” if action is not taken to decarbonize them. Currently, the market is not yet accounting for carbon intensity in property valuation, still property management firms and owners need to be aware of this risk/ opportunity.
• As the scope of sustainability reporting is expanding, the importance of facility lifecycle data (Asset + Material) to analyze and optimize lifecycle and carbon emissions is also growing.

Performance Contracts:

• Transforming existing facilities to net-zero requires a planned approach and strong partnership between owners, occupants, and facility management teams. Digital tools and mobile applications have been strengthening communication and improving operations and team productivity.   
• The long-term business plan for an asset lifecycle maintenance is aligning with other business objectives. Value of resource performance is increasing as O&M contracts are turning to performance-based.

Digitalization:

• A data analytics-driven approach to operation and maintenance is demonstrating significant value addition over the conventional approach helping to improve energy sustainability
• Cloud applications, open data infrastructure and API based approach to select a relevant application to manage asset performance is making it easier to try or scale. 
• Efficient systems combined with operational tools/applications to allow operators to choose how they will maintain net-zero performance. 

These three drivers are setting up the ecosystem which is required to race for the net zero, a solid market driven approach to go for sustainability, supporting technologies such as IoT, data analytics and change management.

Asset performance analytics – Enabling the Race to Zero Campaign:

As far as achieving net-zero is concerned, the ability to harness renewable energy would always help to meet the carbon-free energy demand. But that comes with constraints of space for PV cells, geographical location for the good wind, and time for adoption and implementation. 

On the other hand, focusing on the existing buildings to better manage or reduce energy consumption in a data driven way makes a great approach to the race. In Fact, It wouldn’t be an overstatement to say that almost all the emission that happens during the operational phase can be monitored, controlled, rectified, and reduced to achieve net-zero or carbon positive status, and the first building block towards net-zero journey is to have the access to facility O&M data.

From the data flow pyramid we realize that to access any of the use cases, we would need to climb up 4-5 steps, and in that process, we would be able to lay the foundation for multiple digital transformation initiatives.  

Asset performance management – Leading Facility managers one step closer to net-zero buildings:

1. Predictive maintenance: With the right asset performance data facilities one can move to proactive maintenance practices reducing the unexpected breakdowns and cutting down operational cost. Of course, that wouldn’t be possible without unified energy and asset data strategy.

2. Fault detection diagnostics: Buildings generate tons of data & insights through BIM, BMS, workplace management applicants such as CMMS, CAFM. Correlating with the team with such insights to make sense is not an easy job to get it done and hence finding the operational irregularities without having a strong FDD engine on the analytics layer is next to impossible. An in-house FDD improves the operation and maintenance team’s responsiveness to anomalies and energy leakages.  

3. Energy forecasting: As discussed earlier, demand management and tenant’s behavior aspects can affect the energy utilization. Hence understanding tenant’s consumption patterns, comfort metrics and predicting demand peak can help O&M teams to prepare for it.   

There are a couple of other use cases(asset life cycle management and tracking) that could help facility managers to improve the utilization of the asset and monitor the life cycle of carbon emissions.

As we realize, with every step a facility goes closer to net zero, it increments the importance of stopping every cubic meter of carbon release into the environment, which can’t be reached without having a data driven portfolio operations and a 360 degree asset performance management strategy. It has to be a synchronized effort of digital initiatives, well equipped O&M teams and conscious tenants taken together.

Aiming to net zero is an ambitious start, but the planning and implementation should take the center stage and that’s where the actual race starts involving skill management, digital and commercial aspects of the facility operations.
Stay tuned for upcoming blogs and explore the 360-degree approach to the race to Net-Zero Campaign. 

Want to start the APM journey and stuck on planning? This CXO’s handbook will guide you to plan, execute, and evaluate Asset performance analytics trials. 

Fear of missing out (FOMO) phenomena is generally associated with the millennials of the social media age. It’s a feeling of lagging behind in the competition, missing out on something important although not knowing what it is exactly.

Nowadays whenever we come across a blog post on CRE Technologies or Operation & maintenance best practices we often get the feeling that there is so much happening around digital transformation which of course has only accelerated post COVID but also there are other factors that have contributed to this growth. And then from somewhere, this FOMO pops into our mind and we start thinking, are we on the right track? Are we doing enough to reduce Operational cost? What insights am I missing on? How to optimize BMS data? How can I introduce predictive analytics to reduce reactive calls? Well if you’ve ever been to this situation then trust me you are not alone!

Facilities management is shifting from a low margin, labor-based business to a sustainable technology-driven one and as a result margins are shrinking, more contracts are being signed based on performance targets which have made FM to add digital thinking into their DNA. Let’s look at how to optimize your asset performance management.

Set up your goal:

First, identify what you want to drive from the transformation? What should the end result look like? Satisfied tenants? reduced reactive calls? Reduced unplanned breakdown? Gain a single view of all aspects of the facility? Most of the O&M teams find cost efficiency, energy management, and operational risk management as key baseline goals to achieve from digital transformation. Accordingly, plan for the budget, involve stakeholders who will be responsible for the transformation, and finalize a tentative timeline for each step.

The implementation roadmap should describe short and long-term expected business outcomes, scalable solution architecture, and strategies to address essential needs and gaps, such as data or system integration.

Asset Data and IT infrastructure:

Once you zeroed down on the expected result start thinking about how you will get there? What data is important and which applications will help you to deliver expected use cases? Do you have the dedicated IT team to support this transformation? Or which part would you like to outsource? This exercise will also determine which solution would be ideal for you on-premise or cloud-based. You will have to finalize this before you take the first step as your entire journey could crumble due to the weak IT strategy.

When it comes to data different sources could provide you valuable insights when interlinked. There is the performance and energy data of the assets, then there is data on how people are interacting with building services (such as work order, occupancy related information) that could draw interesting insights if clubbed together. One should refrain from analyzing them in a silo! I repeat do not keep them in a silo! This is a sweet spot where your operations, energy, and maintenance team can collaborate.

According to the report on smart spaces by cognizant “Many organizations have limited visibility across their real estate portfolio, with data about the status and maintenance of key processes and systems (such as HVAC, power, safety, and security) locked in siloed systems.

If you have invested in BMS then ensure you’re utilizing all the functionalities and most importantly extracting the asset data to be assessed independently. 

Connecting building infrastructure assets to a BMS allows for data analytics, asset optimization, and performance and cost efficiencies _ research done by mitie technical services.

That can be further amplified by allowing third-party applications to inspect and analyze the data. The more open your data architecture is better for further integration and scalability.

Start small think big:

Considering the whole pandemic situation, we don’t have the liberty to take more time for brainstorming and come up with a comprehensive plan. We have to act NOW so start with the pilot projects, breakdown your transformation journey into small steps that align with your current immediate business needs. allocate a budget and team to monitor the progress. Do not shy away from taking a demo of an application even if it comes into the third or fourth step of our journey, that will only help you understand whether you are on the right track or not.    

We hope this article would help you reduce that FOMO and show you ways to lead digital transformation at your facility. If you like this article and found it insightful enough to share it with your peers then don’t hesitate a bit! If you have any suggestions or want us to talk to our facility management team on what’s inevitable in digital transformation then feel free to write to us at [email protected]

Just like any proactive facility manager, Henry had been managing a large commercial facility in UAE, over 2 years of his contracts he had managed to impress his client and delivered everything that was asked by the client. He had been planning to centralize all his data resources which would connect work order-related data, asset specific parameters as well as tenant billing details. This initiative would have given the much-needed push to his O&M teams to be able to maintain assets and deliver exemplary customer satisfaction. However due to budget and contractual constraints he wasn’t able to give time to work on this plan.

Then came the pandemic followed by a global lockdown. As there was no centralised platform available to remotely monitor and control the health of the assets, Henry had to rely on a limited number of technicians at the site. Despite his busy schedule If he could have been able to give some time to his digital transformation strategy, he could have been in a better position to maintain his assets. and have a better asset performance management strategy.

You might have come across a similar story after all this pandemic has introduced us to many of such stories about the people who procrastinated on digitalization and now they have to double down their efforts on the same. This statement by Carlo Alloni, managing director of Mitie Technical Services (UK based one of the oldest and biggest facility management companies), is so much similar to this story which explains:

 “The real value of digital transformation is not collecting that data; it’s about analyzing it and drawing out prioritized and actionable insights”

For those who haven’t thought about facility-wide digital strategy, it’s high time to think about it rather start implementing it and if we want to pen down the specific drivers for digital transformation today then there would be the following two of them:

Resilient buildings:

For the optimum performance of the assets, it is important to have a predictable operating pattern but since the lockdown, facilities have been running on sub capacities which disturbed the preset conditions on BMS systems and with the limited workforce to monitor assets it became a difficult task to manage

 This problem could have been solved with the help of an application that correlates occupancy data with the asset performance which could detect the slightest variation in occupancy and adjust the HVAC parameters automatically to deliver the optimum performance or expected air quality while saving energy cost. 

Now, occupancy is just one factor that has changed here but if we look around there are other factors such as changing climate conditions, grid stability and distributed energy sources that can cause an adverse effect on the facilities if not prepared for them.

Changing contracts:

As cost-cutting measures will be implemented across the portfolio, productivity and operations excellence will see a sudden up-shoot. As performance-based contracts take over the conventional contracts, margins would get the hit as you can not rebid to deliver high asset performance targets with old legacy technology. Constantly upgrading the way we share, analyze and interpret the asset data would be the only way to stay relevant in this fast-paced world.

According to Mitie-Verdantix’s research on digital transformation in facilities management, 84% of facility management companies are embracing new digital transformation technologies and solutions at various levels of maturity however only 7% of businesses are constantly taking trials of the promising solutions while others are implementing proven solutions only.

If you already have that in place and want to plan for the Asset performance analytics Proof of value trial? Then our next article will guide you through. Also if you like this article and found it insightful enough to share it with your peers then don’t hesitate a bit! 

If you have any suggestions or want us to talk to our facility management team on what’s inevitable in digital transformation then feel free to write to us at [email protected]

You don’t know what you don’t know, you might have heard this line before. Simon Sinek (presenter of one of the most popular TED videos ‘starting with why’) once mentioned this line in one of his blogs. Whenever you kickstart a digital transformation journey (personal or corporate) it’s always recommended to realize the fact that you don’t know everything and should strive to constantly learn new things because you don’t know which skill will make the long-lasting impact on your career or personal life.

Wait a min. Why am I talking about career, learning new skills on the blog that is focused on operations & maintenance in the CRE space? Well, Isn’t that what we all did during this unfortunate lockdown? We tried to learn new skills, finished a few online courses, refined our resumes, and added a couple of certificates to it. As we were experiencing this change, enterprises and organizations were also reshaping or refining the way they structure P&L strategy, or rather pressing the acceleration button on cost-cutting measures and focusing on improving productivity in every aspect of the business as possible.

As an O&M engineer, one would know what happens when the O&M dept comes under the radar of a portfolio manager to reduce excess expenditure?! Or reduce energy consumption, since facilities management and sustainability goes hand in hand. Unfortunately, maintenance is that unlucky department that faces the most heat and negligence while in reality that could be turned into a profit center if planned right.

So let’s compile the list of things which will be expected from an O&M dept in the coming times and find out ways to excel in them. (Some of the points might not qualify as pressing issues in the past but it won’t be “business as usual” scenario anymore these will come under must have skills in the recent future to stay relevant with the changing time)

A) How do I find the right asset-specific data when needed?

Now the building management system (BMS) is supposed to be the holy grail of O&M engineers if all the features are functioning and assets are connected to it but we rarely find that combination everywhere. So it’s imperative for an O&M department to have the basic infrastructure available to monitor and store the asset data. We know there are budgetary and contractual constraints to build the data acquisition and IT-related infrastructure but the performance-driven strategy can make it possible.

Now let’s, Imagine a situation when a portfolio manager or department of excellence (DoE) asks for the report on the effectiveness of maintenance activity you worked on last month? Now, do you have the data handy? How soon will you coordinate others with departments to share the data with you? How will you do the analysis? Will you use an excel tool or the software? I know it will be a hell of a task for you to perform in a short period or risk your reputation.

In this case, you would wish for a solution that will bring all that data (right from asset specific parameters, energy & maintenance related scheduling of that asset) to a central location and share the customizable reports with you which you can present to your seniors. BMS may be able to provide you asset data but for the other parameters, you still have to extract them from different sources.

B) How do I move to Predictive maintenance? and reduce my reactive calls?

Predictive maintenance is one of the highly misused words you would come across in the O&M industry. According to Gartner’s hype cycle report 2017 it was on the ‘Peak of Inflated Expectations’. It is like the stock market for a Robinhood investor ‘everybody wants to get in but rarely understand it’ and the sad part is that it is often used as a bait to promote not so smart applications.

But it’s not all gloomy there so whenever you decide to go for predictive maintenance get some of the facts correct, ask yourself the following questions: Do I have the right sensors installed to get the granular level of data? What is the predictive analysis this application claims to perform (on which assets)?

What are the insights am I supposed to receive? Will those be actionable operational insights or CAPEX based investment will be required? Will I be able to integrate other applications with this platform in the future? Once you get satisfactory answers to all these questions you can go ahead and invest in it.

Ideally, an application should be able to provide prescriptive as well as contextual insights as in where is the saving opportunity, what will be the impact, and how to act on it so that you don’t have to keep looking at the dashboards all the time and figure out what is happening.

C) How to ensure that I get the credit of my work and impress my facility manager with saving numbers?

Transparency will be at the center of the digital revolution in facility management, every task that you perform or every interaction that you will have with the tenant or customer will have digital imprints. Imagine a scenario where your facility manager will have the numbers on saving opportunities you have identified, the number of assets related insights that you act upon and the average time it took to finish the work orders. With all that data you won’t have to worry about performance-related issues you can focus on your work and keep fixing things.

Of course during all that you can learn tons of things at a self-pace such as how to make calculate complex data sets and make templates (try Power BI) how to visualize your data (again Power BI & Tableau) want to get your hand on regression analysis and time series forecasting? (Try OMI — a personal chatbot for O&M engineers and I am sure if you will know where to look for)

If you like this article and found it insightful enough to share it with your peers then don’t hesitate a bit! In such times sharing is truly caring 🙂 If you have any suggestions or want us to talk to our facility management team on what’s inevitable in digital transformation then feel free to write to us at [email protected]