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Featuring Forrester Research
The Rise of the Citizen Developer
K2 has everything you need to quickly deliver simple and sophisticated process automation solutions across your business.
As we gain access to more content and context, we’ve created a need for greater analysis of that data. Like so much software in the enterprise has evolved, the future of BPM and process will be a far cry from the traditional technology we think of today. Rather than manually correcting our paths, machine learning will enable processes to write themselves and adjust in real-time to changes in the environment to maximize efficiencies, create business opportunities and meet compliance.
As businesses take into account new data feeds from IoT sensors and devices, we’ll continue to witness change in our processes. Many of the things we think about manually automating today will be done so automatically as machine learning finds its way into more business applications. This is not to say that more traditional process and automation will be gone completely, rather that the way we write and manipulate those steps will be better informed.
This next generation of self-writing process will depend on the following factors.
Data, data, data
First and foremost, this automation will depend on the proliferation of data coming from a host of new sources (ie. people, devices and sensors). The good news is much of this information is already being generated. As businesses navigate privacy and regulation, they’ll be able to responsibly receive loads of relevant data to use to improve process and decision-making.
Once this data in the hands of the organization, business users will require access to smart technology, like machine learning and predictive analytics, in order to process that data and translate those massive incoming data flows into something digestible. Data is only valuable if you can analyze and make sense of it, so tying machine learning capabilities to predictive analytics will be the key to feeding process with the right information to make real-time, educated improvements. We’re already on our way there as machine learning becomes more pervasive and capable of filling in on behalf of people or systems.
The final step in making self-writing process a reality is the ability to take the outputs of those efforts and turn them into actionable outcomes. It isn’t enough to deliver an analysis of process inefficiencies, or even to identify recommended actions. Soon these tools will be capturing data and managing process seamlessly, and in a way that is in no way an overhead to the business.
What we traditionally saw as a structured process in the past - based on people making decisions - will become more ad hoc and flexible to allow for more rapid and intelligent business decisions.
To learn more about the future of business apps, read the white paper: “Are low-code platforms fast and scalable?”