Automation Platforms and Process Mining: A Powerful Combination
When you need to replace a legacy system by a modern IT system, process mining can help you to capture the full process with all its requirements to ensure a successful transition.1 However, once you have moved the process to the new system, you can continue to use process mining to identify process improvement opportunities.
This is exactly what Zig Websoftware has been doing. Zig creates digital solutions for housing associations. But once their automation platform is running, it also collects data about the executed processes. Based on this data, process mining can be used to analyze the process and substantiate the gut feeling of the process managers with hard data. The beauty of the application of process mining in an automation platform environment is that the insights can be immediately used to make further changes in the process.
Time is Money
One of the first customers for whom Zig has performed a process mining analysis is the Dutch housing association WoonFriesland. With approximately 20,500 rental apartments in the province of Friesland, WoonFriesland wants to offer its tenants good services in addition to good and affordable housing. An optimal and efficient allocation of housing is an important part of this service.
Every day that a rental property is vacant costs a housing association money. Through process mining Zig Websoftware zoomed in on the offering process of WoonFriesland. Some of the questions they wanted to answer were: How long does each step in the allocation process of a property take? What takes longer than necessary, and why? What can be more efficient so that the property can eventually be assigned and rented more quickly? In short, what can be improved and what could be faster. After all, time is money.
The Analysis: Bottlenecks
During the process mining analysis Zig found that much time was lost in the following three areas of the process:
- The relisting of a property, see (1) in Figure 1
- The time a house hunter gets to refuse, see (2) in Figure 1
- The number of times an offer is refused, see (3) in Figure 1
Figure 1: The time loss is visible in: the relisting of a property (1) the reaction time of a house hunter (2) and the number of times a property is refused (3).
The process map above shows that it takes an average of 16.4 hours to launch a new offer, which has occurred 1622 times. In addition, each offer takes an average of 6 days to be refused. In the meantime, nothing happens with the property and the corporation cannot continue either.
The Solution: Housing Distribution System
To address these problems, WoonFriesland chose to further automate the digital offering process in their system. When a property becomes available, a new offer is automatically launched. This reduces the waiting period from 16.4 hours to 64 minutes (see Figure 2). The ability to offer the property manually remains active, so that WoonFriesland can create new offerings both in the old and in the new way.
Figure 2: The automatic offering shortens the waiting time from 16.4 hours to 64 minutes (click on the image to see a larger version).
In addition to the automatic offering, WoonFriesland has also chosen to provide house hunters the option to register their interest in a rental apartment through the website. Once an apartment is offered to a candidate, they can let the housing association know whether they want it or not within three days. This allows WoonFriesland to shorten each refusal by at least 3 days (see Figure 3). Furthermore, the website-based process saves WoonFriesland a lot of time because they do not need to call back every candidate to see if they are still interested.
Figure 3: In the old situation a refusal lasted an average of 6 days. Now a house hunter is required to indicate whether there is interest within 3 days (click on the image to see a larger version).
Overall, the new solution has ensured that – with less time and effort – WoonFriesland has a faster turnaround and assigns its properties on average 7 days faster than before. A great result!
This results in significant savings in vacancy costs:
The results of the use of automatic digital offering in the first half year were that, on average, the duration of the advertised 583 properties was approximately 7 days shorter. We are talking about a total of 4000 days. In addition, we have new insights in which areas we could improve the process even more.
– Steffen Feenstra, Information Specialist at WoonFriesland.
WoonFriesland knew there were aspects of the housing allocation process that could be done faster, but they could not precisely tell where the main problem was.
The process mining software Disco allowed Zig Websoftware to substantiate the gut feeling of WoonFriesland with facts and hard figures. The results of the process mining analysis justified the investment in the optimization and further automation of various processes in the apartment allocation of WoonFriesland. As a result, they could significantly reduce their vacancy rate, which allowed WoonFriesland to realize considerable cost savings.
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Read this interview about how Process mining helped to replace a legacy system at a large Australian government authority and this example based on AS/400 IBM systems. ↩︎