Every time a Cleanaway truck picks up a waste bin, it also picks up data, lots of data – and it’s that information that is the key to efficiency, service reliability and profits.
For Cleanaway it’s a case of turning garbage into gold.
ASX-listed Cleanaway operates Australia’s largest waste management business. With around 6,000 people employed around the country, 5,300-plus vehicles – most of which are equipped with an array of data gathering Internet of Things (IoT) sensors – and 250 sites, the organisation has grown organically and through acquisition.
Each time it has bought a new business it has inherited its information technology and data. The challenge for Maayan Dermer, who leads data and analytics at Cleanaway, has been to develop a data and analytics platform that can bring together all that information from multiple sources – super-charge it with modern AI and advanced analytics, and turn it into insights gold for the business.
Running a waste management business is complex; there are people to roster on, to keep safe and pay, there are vehicle routes to be scheduled, trucks to be maintained, client contracts to be managed. Services can be impacted by truck weight, weather, locked bins, blocked gates, contamination and a host of other issues that impact efficiency and the customer experience.
Cleanaway needs transparency over all these issues.
Dermer joined Cleanaway just before the pandemic struck in early 2020. As an essential service, the business continued to operate throughout COVID-19, collecting more and more waste – and data – each day.
There was a clear opportunity to inject efficiency he says; “We are collecting data from all our services, if I’m going to pick a bin 100 times and I know now the average weight of it and I know all the average weights of all the bins in the neighbourhood, I could actually be much more efficient in how I route collections, price services, segment clients and more.”
The data available for analysis is immense – more than 150 million transactions a year detail Cleanaway’s waste streams and fresh data from Cleanaway’s fleet comes into the organisation every two minutes.
The opportunity for Cleanaway is to harness this data and use it to drive value through its operations. Cleanaway has begun investment in data and analytics using Databricks and Azure Synapse Analytics powered by Azure Data Factory to create the platform.
Now, Cleanaway has not just data – but genuine insights. Dermer explains:
“Missed services can occur because of locked gates or blocked bins, which we can record through the technology in the truck. With more ready access to data, we can proactively advise a customer of an issue and rebook that service straight away, rather than the customer having to call us to find out what happened. It’s more efficient for our drivers and schedulers, and a much better experience for the customer,” says Dermer.
Optimising services and schedules makes for a better experience all round: “The platform can see if a customer is actually generating more material than first thought. We can use that insight to adjust their service levels or work with them to reduce their weight through more recycling and resource recovery,” explains Dermer.
“A client may have a scheduled collection service on a Tuesday when actually you are going to be more efficient if you do it on Wednesday. It’s a tiny change for the client but for Cleanaway, we’re getting our resources better aligned to the service,” says Dermer.
The timing couldn’t be better as Cleanaway is in the midst of a customer experience transformation and preparing to kick-off a significant digitisation program that will see a number of manual process be automated and digitised.
Cleanaway’s data, coupled with our digitisation program has the potential to produce an all-online self-service experience allowing customers to go to a website, get a quote and order a waste collection service.
“In Cleanaway, I would like to get dynamic pricing and personalised pricing to a customer through a self-service portal, utilising previous history, service priorities, recommendations, location. We are actually laying now, all the foundations to build this service.”
Cleanaway is also exploring opportunities to integrate third party data. Knowing weather forecasts for example could be very useful for scheduling recycling runs when a wet weekend is forecast that could risk ruining the recycling value of cardboard recycling.
Add in artificial intelligence that is able to interpret images collected from on truck cameras, and the opportunities to extract value from Cleanaway’s data continue to grow, says Dermer.
While he has the big picture sketched out, Dermer says it makes sense with any data and analytics journey to start small and; “Don’t try to boil the ocean. Even if you have quite a big journey to go through, make sure that along the way between the milestones, you are aligned with other business programs, such as customer service and digitization, while also making that commercial argument for the data and analytics initiatives.”
By delivering a clear benefit it’s possible to build traction with the business, delight the customer, boost the appetite for innovation, and continue to invest in the digital alchemy that turns data into gold.