Data, AI and IoT are buzzwords that have been thrown around in several industries for a while already. However, even in low-key businesses, such as facilities services, collecting data and benefitting from it is something facility services providers have seemed to be struggling with. Facilities present service providers with tons of interesting data, that we already now are able to visualise on fancy dashboards and use to base our suggestions on. For example, how to improve the indoor air quality or find minor repair projects for facility workers to take on.
So what is the issue? In our opinion – the lack of actions taken and executed by service provides, for example, technical service and repairments, cleaning and waste collection, that actually would be based on the extremely valuable insights and data from our facilities.
At Lassila & Tikanoja, we have tackled this by not only collecting data and analysing it, but also by providing our clients with measurable actions that aim at creating better working environments, energy use, or an improved service quality level. Our colleagues at Technical Services have launched the Smartti Automaatio -service, which aims to provide intelligent energy management without large investment needs. Similarly, we at Cleaning and Support Services have launched a service called Data-Driven Cleaning, which utilises facility data for the benefit of our cleaning personnel’s work. In short, we are using a digital twin (Empathic Building provided by our collaboration partner Haltian) that contains both a real-time view of the spaces we are cleaning, as well as a view for our cleaning personnel displaying the areas in need of cleaning. The digital twin is accessible to all our personnel through phones, tablets, PC, or other similar devices.
Improved service quality and employee satisfaction
In the fall of 2021, we launched one of our first data-based cleaning pilots at the Maria 01 Campus. A campus serving as the home to over 180 tech-savvy startups and with a total of over 20 000 m2 to clean seemed like the perfect challenge.
What does then data-based cleaning include and mean in practice? At Maria 01 we are on continuous bases collecting data on the facilities’ usage, such as meeting room use, phone booth occupancy, and hot desk utilisation, as well as restroom usage rates and consumption of paper towels. Our cleaning personnel use tablets displaying real-time data of the entire first floor of the Maria 01 Campus and make day-to-day decisions based on the statistics on where to clean in order to ensure the best possible quality. For example, if data from our IoT sensors show that a certain meeting room has not been used since last cleaned, our personnel can use their time to clean spaces, that based on the collected data show to have been used at a higher frequency.
During our pilot, we have learned that thanks to a data-driven cleaning approach, we can offer our clients a higher quality of service. We are cleaning spaces that actually are in the need of cleaning, and not spending our time cleaning areas that already are clean. Our data-driven cleaning services also provide our clients with better reporting, as we also offer them access to a digital twin that shows statistics on e.g. currently available hot desks, meeting room utilisation rates, and which restrooms have been used the most. The fact that we are able to put our resources where they evidently are needed, has also improved employee satisfaction by a mile.
Meeting rooms and window seats at the top of the list
A couple of weeks back, we at Maria 01 invited the team from L&T over to have a deeper look at the data collected from our facilities. We wanted to get a better understanding of how our spaces are used, is there a day or time that shows to be more popular than others, or do we maybe even have some spaces our members don’t seem to use at all? We, of course, had our own assumptions, but some insightful findings were definitely made.
On the Thursday morning we logged in to the system to check out the utilisation rate of our hot-desk, or Flex Desk, area as we call it, it was quite a surprise to see that all but one of the available desks were already occupied at 11 in the morning. It’s of course nice to see our spaces being used to their fullest capacity, but do our members know where to head to if they can’t find a free seat in this area? We will be improving signage in the space, directing people in the direction of where to find an available space to work from if this area is full.
Where we’ve identified Wednesday to be the busiest day at the Maria 01 Campus based on the data we ourselves collect, the sensors placed out by L&T in different meeting rooms and phone booths showed no significant difference in the usability rate depending on the day of the week. We know from before our members host a lot of meetings, 952 during 2021 to be precise, and according to the data provided by L&T, Maria 01 has a much higher meeting room utilisation rate compared to similar facilities. One of the meeting rooms found in one of the common areas on Campus had during a week in January a utilisation rate of 80% – I guess we found our members’ favourite.
That people prefer the desks closest to a window did not come as that big of a surprise to us. However, when checking the occupancy and utlisation rate of the desks in a few of the common areas, the desk next to the one closest to the window was almost always empty. A very common phenomenon according to L&T. This piece of information came at a really good time since we’re in the process of improving the Fixed Desk area, where our members who prefer to have their own designated desk sit. With this information we will look into the placements of the desk, and whether it makes sense to place e.g. a green wall next to the window seat rather than another desk.
If you are interested in finding out more about data-based cleaning, reach out to Jaakko Sarpo, Development Director at L&T: +358 505940955 or jaakko.sarpo [@] lassila-tikanoja.fi