Although there is much to be gained by a data-driven approach in business, not every company is unlocking the full potential of their data as of yet. In this blogpost series, we take a look at some of the benefits that accompany data-driven solutions. To illustrate these benefits, examples are provided of customer cases. This blogpost is all about process automation and saving time.
This is part 2 of a blog series. Part 1 can be found here.
Business process automation or robotic process automation is basically the technology-enabled automation of complex business processes. Most of the time, businesses face predefined structured and repetitive tasks or processes that take up a lot of time to perform manually. By writing pieces of software code these tasks can often be carried out fully automatic, resulting in a lot of saved time and in most cases better decision making as well.
A business case at one of our customers serves as an excellent example of automating business process. This customer offers payment and financing solutions for consumers and businesses. For these parties to qualify for a loan, they must satisfy certain legal conditions. To check all these conditions manually was a very labor-intensive job. Therefore, they sought after a more efficient way to review loan applications. We as Notilyze automated a lot of processes involved by using our decision management service. By integrating several API services and machine learning models into this service we were able to save a lot of time invested in repetitive tasks and improve their decision making as well. The result of our solution is that appliances for loans of up to €1000 can now be accepted, rejected, or decided to investigate further based on various external data sources, business rules, and models.
Another customer of ours believes in a world without disposable devices and works in accordance with the circular philosophy. That means their consumers pay to use devices rather than to own them. This company offers various subscriptions to washing machines, dryers, dishwashers, and coffee machines. Users pay per wash or per cup of coffee. The supplied devices are connected to the internet via special plugs, which are used to measure the power consumption of the device. The challenge that was faced was to accurately determine the number of washes and cups of coffee, considering the different types that can be distinguished (e.g. cappuccino, espresso, etc.). By using machine learning models, we were able to analyze the power consumption patterns. This formed the basis of a fully automated process, in which consumers are invoiced based on their usage. Moreover, customer experience is improved as well since the usage data is also exploited for personalized recommendation.
In both examples mentioned above, as well as in many of our other customers’ cases, there are processes that could be optimized by using data to go along with experience and gut feeling. Most of the time, enough data is gathered but not put to best use due to a lack of knowledge, tooling, or resources in a broader sense. No matter the industry, data can add significant value to your business.
Is your organization getting the most of its data? Contact Notilyze now to learn how a data driven approach can significantly improve decision making across your organization.
Stationsplein 45 A4.004
3013 AK Rotterdam
+31 10 798 62 95