The Truth About Machine Learning In Enterprise Software

There’s a lot of hype around machine learning, but what does it really mean in the context of enterprise software? How does it work, where is it adding business value today, and what should we expect from it in the future?

Let’s start with some definitions. Artificial intelligence (AI) is an umbrella term that includes machine learning (ML), deep learning and cognitive learning. The part most relevant to enterprise software is ML, which in this context is the ability to create automation through AI algorithms.

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Data Integration For Good Decision-Making Is More Than A Technology Issue — The Human Factor Is Crucial

Good decisions require good data, but pulling it all together and getting it into a format you can analyze isn’t easy. One of the biggest factors isn’t technology, it’s people. Here are three steps for getting data into a form you can analyze, including the technology you need to process it and the data culture necessary to make it happen.

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What Kind Of Enterprise Software Will Be Right For Your Business In The Future?

Think for a moment about how organizations are evolving. They all want to be lean, fast and specialized. They’re trying to become more adaptable, intelligent and resilient. Wherever you look, it’s a pretty consistent pattern.

Now, think about the main trends in enterprise software. It seems to be evolving in 20 directions at once: AI, ML, SaaS, PaaS—it feels like you’re drowning in alphabet soup. Even when you spot a recognizable word like “cloud,” there are half a dozen different flavors.

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A New Sense Of Urgency: The Evolution Of Enterprise Application Strategy

The last nine months have imposed many changes on organizations. They’ve found that they can change dramatically overnight if they have to.

The need to be agile in both financial planning and corporate action has come into sharp focus. As McKinsey noted in an article on performance management under Covid-19, “Companies need a new approach to financial planning and performance management — one that informs rapid realignment of plans and actions and ensures organizational resilience.”

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RPA is dead, long live RPA

Is there a revolution, a significant evolution or at least a new generation of Robotic Process Automation (RPA)? This was the subject of a conversation with Claus Jepsen, CTO of Unit4. Unit4 recently announced ERPx, what it calls a self-driving ERP. The architecture of this new product is micro-services based and considerably different from anything than has been before. Jepsen explained how RPA is woven throughout the new solution with threads extending well beyond it to connect to other solutions and more traditional ERP and RPA systems.

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There’s No Automatic Choice In Business Process Automation

Automating business processes saves time and money, but what’s right for one organization might not be right for another — what you automate, how much you automate it and the approach you take all need careful consideration. 

Robotic process automation (RPA) of enterprise resource planning (ERP) software isn’t anything new. It’s possible to automate simple, rule-based business processes like workflow steps, completing time sheets and invoicing. Doing so speeds up processes, improves accuracy and compliance, and frees people to get on with more interesting and valuable work.

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