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Planning Your Machine Learning Revolution

August 27, 2019

Machine learning, robotic process automation, artificial intelligence; a convergence of technology innovations are promising another revolution and a wave of disruption for businesses of all sizes. By integrating machine learning into their enterprise software ecosystems, companies are able to increase performance and productivity over existing systems and processes in a way that boosts the ROI of prior technology investments while elevating the roles of subject matter experts and process owners. Compared to the past, where new ERP upgrades and updates might offer a one-time benefit, new machine learning-driven capabilities promise to offer continuous advancements and improvements by adapting and evolving to changing business conditions.

That all sounds great, right? The real question at hand as we enter a new year is, “What is your company doing about it? And “How can you best take advantage of these innovations quickly and cost effectively in a way that produces meaningful results?”

To get started, organizations need to begin experimenting now, with small scale projects that can produce measurable wins, so they can build internal support and acceptance to these innovations in a way that overcomes the cultural headwinds that threaten to drag on the innovative potential of digital transformation within their organizations.

Elevate Your Enterprise Systems

Enterprise Resource Planning Systems, Customer Relationship Management Systems and Enterprise Content Management Systems deliver capabilities and process visibility throughout an organization. Integrating process automation systems with these enterprise-wide platforms creates an opportunity to share knowledge across multiple business units and departments.

Intelligent enterprises plotting their course for the future can experiment with new combinations of versatile machine learning applications, allowing the machines to learn how to improve processes and enhance productivity by interacting with enterprise systems—without spending tons of time, effort, money and energy on planning, coding, implementing and integrating systems like that had to in the past.

In other words, firms that want to embrace new innovations in adaptable, intelligent systems won’t have to focus as much on platforms, integrations and code—they’ll finally be able to put performance, metrics and results on the center stage and allow their human subject matter experts to take the reins.

Streamline Existing Processes

At Artsyl Technologies, we’ve applied self-learning technologies to the problem of creating flexible, adaptable, self-learning platform that can examine a document or data source (like a digital form), identify what it is, what process it supports, what relevant data it contains and what to DO with it.

On top of that platform, called docAlpha, we’ve created applications to support document handling, data extraction, validation and workflow for things like vendor invoice and customer sales order handling. Both represent common use cases within most organizations that can deliver ‘quick wins’ for new technology implementations, that can leverage existing ERP/ECM/CRM systems.

But they’re just the beginning. For our customers, embracing a system that can be implemented quickly with minimal configuration and no custom coding or complex integration is a win unto itself. The fact they can get up and running in 90 days and achieve ROI within 180 days, just through process efficiency, sets the stage for the real revolution to come.

Igniting the Revolution

With self-learning tools in place that contribute to the organization by eliminating routine manual tasks like document handling and data entry for high volume of vendor invoices or customer orders, companies can explore other opportunities to innovate where the volumes or velocity of information may not be as high, but where there may be significant rewards for further automation.

In the past, companies tolerated inefficiency within certain processes because the cost and effort to tackle them was simply too high to justify automation. That is the REAL significance of today’s self-learning systems—it is as much about WHAT they can do as it is about HOW MUCH effort it takes to achieve the desired result in a way that is scalable and adaptable.

Let us know what process pains YOU would tackle if those obstacles were removed—and let’s discuss the path to YOUR company’s process revolution.

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