WEBINAR RECAP: Case Studies and Critical Strategies for Operating a Post-Pandemic Hotel

On Wednesday, 23 September at 5 PM (GMT+8), SensorFlow hosted a LIVE Zoom Webinar on “Smart Hotel Management: Operating with Energy-Efficient and Labour Productive Strategies” and featured a series of exclusive case studies on how SEA hotels have leveraged on key data to improve their operations and benefited from SensorFlow’s smart hotel management solution.

Our CEO and Co-Founder, Saikrishnan Ranganathan, presented the three critical strategies that hotels should implement to maximise energy efficiency and labour productivity in the current post-COVID-19 era. A total of 40 hoteliers across the SEA region attended the session and had an insightful Q&A session to learn about SensorFlow’s smart solution and how they can gain actionable insights from big data on their property to advance their recovery from the pandemic.

Here are 3 key highlights on the critical strategies shared during the session:

1. Minimising operating costs during the recovery period

As a survival strategy to keep businesses afloat amid the COVID-19 crisis, hotels worldwide have implemented cost-cutting measures across their top two largest areas of expense: labour and energy. In fact, international hotel brands like Marriott claimed that the hotel business was running almost 75% below their usual workforce levels. At the same time, when we look at a typical hotel’s energy bills, guestrooms HVAC consumption is one of the largest drains, accounting for up to 60% of the total energy costs.

Subsequently, it has the highest potential for energy savings, especially during a hotels’ recovery period post-COVID-19. Facing these new circumstances of having to operate with limited operational resources with a high demand for cost reductions point to the pressing need for hotels to implement solutions that optimise their resource consumption while maximising their operational efficiency and productivity.

An example of a relevant smart hotel solution is SensorFlow’s AI-driven room automation and big data solution. SensorFlow’s retrofit system helps hotels to save up to 50% on HVAC bills and improve a hotel’s total energy efficiency up to 30% by automating and optimising the guestroom air-conditioning (A/C) system to either turn off or change its setpoint to a higher setting when a room is not occupied by any guests. For example, before COVID-19 struck, a Singapore hotel with 154 rooms could easily achieve a significant reduction of 24.8% in their HVAC energy consumption simply by using SensorFow’s occupancy-based A/C automation.

Hotels can further maximise energy savings by implementing SensorFlow’s A/C setpoint optimisation strategies by leveraging key data and insights on average guestroom’s setpoint trends as collected by SensorFlow’s IoT-driven room sensors. Based on these data, SensorFlow is able to recommend hotels an optimal minimum setpoint limitation customised for each property to implement across all their A/C systems, thus preventing unnecessarily low setpoints from being used by guests. Not only does this strategy save a significant amount of energy, but this also allows hotels to also track how many additional savings they can achieve when implementing different minimum setpoint limitations across the property.

Furthermore, by constantly measuring and monitoring energy consumption data across hotels’ entire cooling system even at the individual room level, SensorFlow’s team of data scientists can easily identify critical trends in energy consumption and the respective cooling demand on any HVAC device. This enables the team to compare the performance of devices at similar loads and advise hotels where maintenance is required to improve performance and reduce their overall energy consumption costs.

As part of the case study series, Sai showed a comparison chart highlighting the patterns of unusual performance for different individual compressor units within a hotel. Based on that data, SensorFlow was able to help hotels advance towards predictive maintenance by enabling the engineering team to pre-emptively identify and repair potential faults in specific units and improve overall HVAC system performance and efficiency.

2. Maximising productivity for higher operational standards

With the new hygiene and safety measures in place, it now takes a housekeeper a longer time to clean the room compared to pre-COVID. It is key for post-pandemic hotels to implement solutions that leverage AI to help streamline any repetitive, labour-intensive housekeeping operations where possible to allow for a smaller team to still maintain the high hygiene and high-speed check-in standards that guests expect.

SensorFlow’s solution addresses these challenges by boosting a hotel’s housekeeping productivity with actionable occupancy insights. With live occupancy data and high-level occupancy insights, the operational team will better understand the ideal time to enter rooms without accidentally disturbing guests and thus ensure better compliance with the new contactless norms. In one of the case study examples, SensorFlow reported that in a typical hotel, the average daily occupancy rate was usually the lowest (20-30%) between 12 to 6 PM. With this insight, the hotel was able to optimise its housekeeping team to schedule room cleaning time with better agility and efficiency during those hours.

However, in this post-COVID era where occupancy rates have drastically dropped, a key challenge that hotels face is to maintain their room in optimal conditions during extensive periods of shutting down many of their rooms. With smart IoT-enabled sensors in place, SensorFlow’s system helps with monitoring those room conditions by collecting extensive room environmental data from the smart thermostats (e.g. relative humidity, ambient temperature, ambient humidity etc.) every few minutes on a daily basis. In fact, a hotel that implements SensorFlow’s solution receives monthly humidity reports and charts that highlight the top ten rooms with highest mould risk scores, allowing hotel staff to execute immediate maintenance services specific to these rooms. Furthermore, SensorFlow’s will assign dedicated Customer Success Managers to each hotel who will also help to identify factors contributing to this high humidity issues, such as poor room insulation, dripping fan coil and sun-facing location.

3. Balancing cost reduction with sustainable practices

Most hotels have mentioned that COVID-19 has their negatively impacted their green practices as a result of resorting to CapEx-driven strategies of cost-reduction (e.g. using more bio-degradable straws and utensils). This has led to the notion that sustainability is often a necessary sacrifice in order to cut costs during this recovery period. However, Sai pointed out that OpEx-driven sustainability can actually be profitable by help hotels save operational costs post-pandemic. 

Be a Smarter, Greener Hotel with SensorFlow

Smart solutions that reduce hotels’ energy, water or food wastage are also cost-reduction focused while simultaneously minimising hotels’ impact on the environment. In fact, operating more sustainably is a great opportunity to not only build long-term resilience and competitiveness but also to promote a more eco-friendly brand. Hotels can easily leverage on highlighting these sustainability solutions and initiatives to enhance their current brand especially if they also have the concrete savings data to back up those claims – which is provided with SensorFlow’s solution.

In fact, SensorFlow is fully committed to supporting hotels on these environmental fronts by providing concrete data on the projected amount of carbon emission hotels offset from using SensorFlow’s energy management solution every month. Furthermore, SensorFlow’s Corporate Social Responsibility program with One Tree Planted also helps hotels to double their positive impact on the environment by planting a tree on behalf of the hotel for every ton of carbon emission that the hotel has reduced with SensorFlow’s solution, so that we can build a smarter, greener future, together.

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