Sangeeta Ray, Vice President, Siemens Real Estate, Asset Management Unit India & Bangladesh
“We are creating work environment history” — These words of Sangeeta Ray, Vice President, Siemens Real Estate, Asset Management Unit India & Bangladesh, summarise the contents of this far-reaching interview with Mrigank Warrier, Assistant Editor, Clean India Journal. Recently recognised by Corenet Global’s India Chapter as CRE Executive of the Year 2021, she shared her thoughts about the role of data in CRE FM and how she is leading her organisation’s efforts to pivot to the post-pandemic office.
What role do remote sensors and the data they gather play in CRE FM?
Over the last 4-6 years, we have executed many life-cycle replacement and renovation projects at our 22 factories across India. Whether it is for monitoring of power or water consumption or air quality, we have put in place meters that can be monitored remotely. We use Supervisory Control And Data Acquisition (SCADA) and applications built using Siemens’ MindSphere IoT platform to get qualitative information about all these key elements.
We have a suite of Siemens products which have been implemented across offices and factories, which are remotely monitored from our Kalwa campus (near Mumbai). For example, a majority of the facilities in our 7-storey premise in Kharghar are monitored primarily from Kalwa. We can even trigger fire test-alarms remotely! In case of a fire, we would be able to handle the emergency at Kharghar from Kalwa itself. We enabled this by installing the right type of cameras for monitoring, and a public announcement system that can be commanded from elsewhere.
Similarly, we are monitoring our Aurangabad factory’s solar power generation and power, water and air consumption from Kalwa. All the equipment has been connected by SCADA to a virtual tool through which we monitor behaviour. This in turn helps us detect seepage, leakage or any other issue which can then be rectified on-site.
What role do Key Performance Indicators play in CRE FM?
Let’s say we have a solar plant at both the Kalwa factory and the Aurangabad factory. When we set up such a plant, we have a mandate to generate a certain amount of solar power every year, so that the savings provided by solar helps us achieve break-even of the investment made. If we want to ensure that the solar plant is working at the required efficiency level, we need to monitor the actual output against the standard output to know how the power generation per day goes above or below normal. This could be because of weather conditions or product failure.
The KPI definition here would be the standard amount of power that needs to be generated, against which we compare the actual amount generated. Using this, we find out when a plant is not performing, or performing when it shouldn’t be, for example, when the factories were closed.
What does the data you collect tell you about the need for preventive maintenance and life-cycle performance?
As an example, the team is continuously monitoring the fire detection system. They are able to detect where the sensors are not working, and can alert maintenance to take a look immediately, rather than wait for someone to check as per the schedule.
For life cycle maintenance, the data will come in gradually. We will study historical charts of breakdowns and uptimes to finally reach a stage where we can conclude whether the life cycle is prolonged or not, if we were running it at part-capacity, etc. We have been doing digitalisation at Siemens Real Estate for the past few years. We need more history than two-years data for that. We are watching this space.
Will AI be integrated into your FM systems?
We must always remember that when we digitalise gradually, we do not have to explain the business case too often. Evolution is smoother than revolution. We are evolving by using life-cycles logically. If I were to bring in a revolution, I would bring in AI much faster.
What is very important in this area is domain expertise. At the moment, we are ensuring that our domain experts become digital-oriented, instead of the reverse. If I were to take a standard product developed elsewhere, we would have AI-driven results immediately, but here, our team consisting of domain experts equipped with digitalisation solutions first stabilize the data before AI sets in. A year or two from now, AI will be completely integrated as AI without data would be garbage. At the end of the day AI needs data to show results.
With social distancing set to be the norm, how are you using data to optimise available office spaces as well as make them available to employees?
We did reopen our offices for two months before the second wave. We did a gradual opening; not only did we control numbers based on government norms, but we also tailored our plans based on the number of people required to be in office.
We use our own workplace experience solution called Comfy, which is also available for customers to future-proof their digital workplaces. Siemens India is using Comfy to enable a safe return to the workplace for employees and also as a foundation for our future-oriented way of working. We did the usual layout testing, what office seats would and wouldn’t be available and so on; that was the capacity we loaded into Comfy. We also made it mandatory for a person to display their health app before entering — another Siemens solution which confirms one hasn’t come close to a Covid-positive person, gone to a public place, etc.
Along with this, each person had to show they had booked their presence in the building for the day. If this wasn’t done, security would not allow the person in. This applies even to me, who oversees all the properties! We also tracked the quality of bookings. For example, were some people booking and then not showing up?
Statistically speaking, how do you view the requirement for office space in the future?
At Siemens, we have come up with mobile working principles. If a person has to come to the office, say for two days a week, it means we don’t require more than 40% of our classical working space. But since the future is about more collaborative working, the classical working space area will be 1.5-2 times of the current area. Hence, even if people come in just two days a week, I will still need 70-80% of the total workspace.
The post-pandemic office will need to put office occupants front-and-centre. How can digitisation help?
First things first, I need to make my office a physically attractive space and only then, in a digital sense, also a smarter place. We have city-by-city blueprints and timelines, with a logical life-cycle replacement plan. We were actually using the office closure due to Covid-19 period wherever possible to create new and safe work environments, followed by digitally-safe work environments.
More than 60-70% of our offices will have new work environments in the next two years; the smaller offices will be redesigned sooner, depending upon the lead time of the project. First we need a good-looking office, then a digitally smart office; otherwise it doesn’t make sense.
What will these redesigned offices look like?
The share of concentration areas/classical work space will reduce and the share of collaborative areas will increase. Today, our offices have an 80:20 ratio of concentration areas to collaborative areas. Tomorrow, it will be almost 50:50. The underlying principle is, work that can be done alone can be done at home or anywhere else; work that needs teamwork will be done at the office.
When Covid-19 started, we knew it would be a game changer. We are creating work environment history.
