WASH Multifamily Laundry Systems provides outsourced laundry services to apartment buildings, at university housing environments, motels, hotels and more. With an installed base of over 500,000 machines in 75,000 locations, over 5 million people depend on WASH to do their laundry every week. Yet, the real product at WASH is not so much laundry as much as it world class technology, logistics and superior customer service.
On the one hand, WASH embraces its family-owned legacy, culture and dedication to service excellence, but, on the other, they also set the pace with the changing times. They take pride in being a metric-driven company. They pioneered new advances in laundry room technology and have found ways to modernize systems to make their employees more efficient and serve their customers’ needs better.
A core foundation element of the technology stack at WASH is Microsoft Dynamics. All key aspects of the business – customers, equipment, locations, payees and more – get instanced in Dynamics. Over the last ten years WASH has dramatically driven productivity in their organization by standardizing on Dynamics as their single enterprise-wide “source of truth”, one in which all key assets, customers, transactions and much get captured and shared throughout the organization.
Over the last two years, WASH is starting to transform the way they work with cloud-enabled technology. Specifically, through the use of Azure and Office 365 WASH is getting out of the business of worrying about server and networking infrastructure, wiring, packaged software installation and maintenance, and instead focusing on their core business so they can zoom further ahead to the next generation of service delivery. Play the video below to learn more:
Using Power BI, for instance, their finance and operations are able to take information out of data warehouses and pivot, slice and dice that data and share it via drag and drop – and all of it without involving IT, which they find liberating. Power BI also lets them access public data sets and marry it with internal data – for instance, things like demographics, gas prices and location-specific factors such as the weather which may influence usage.
To help improve customer service WASH is tapping into the power of Azure Machine Learning to unlock even more insights into their business on an automated basis and – importantly – integrate those insights into their everyday applications. For instance, they are eager to discover problems in advance through the power of predictive analytics. It’s critical that a field service technician arrives with the right parts in his or her truck, and that they fix the problem the very first time. WASH also wants to determine, when a service call is open, whether or not a real problem will actually be discovered. For instance, in some situations, service technicians get dispatched but there are no underlying problems found. If the system dynamically determines that there’s a likelihood of there being no real underlying problem, WASH would keep the customer on the phone a little bit longer to walk them through their issue and solve the problem remotely.