Programming is sometimes seen as more of a “dark art” than an engineering discipline. Developing programs that can be read and used by non-programmers is an “El Dorado” that many businesses have longed to reach.

Enter low-code/no-code development: intuitive tools designed to allow business users to build applications and therefore reduce IT staffing costs, accelerate innovation and provide businesses with greater agility to respond to change. They’ve seen an explosion in popularity in recent years, but what are they, and are they really the future?

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Programming has made more farewells than Frank Sinatra, but the difference being that “Old Blue Eyes” eventually played one final concert, whereas programming isn’t going to go away.

Year after year, pundits float a new meme: low-code/no-code systems will mean the end of the need to hand code or (the latest universal panacea) ChatGPT will become all-powerful and obviate the need for software engineers. Let’s be clear: there is no prospect whatsoever that at some point in the future we won’t need to code. Indeed, quite the reverse is true. But what is also true is that we have come a long way in reducing bespoke coding and replacing that with software extensibility.

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Even standard ERP systems aren’t one size fits all—here are 5 tips for choosing a solution.

Every business runs on a set of processes. These are so integral to your operations that they can be easy to overlook—but they can be vital to finding efficiencies, protecting your bottom line and satisfying customers. When choosing a new ERP system, businesses face a choice: to customize their ERP system to their existing processes or to select an out-of-the-box solution and adopt processes based on good practices for their industry.

Standard ERP solutions are best suited to organizations with a certain set of priorities. One is speed to market: you can “hit the ground running,” streamlining the implementation process by using the standard configurations provided by your vendor. The sooner you can use the system, the sooner your business benefits from the financial investment you’ve made in it.

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There is a lot of excitement about technology’s potential to automate tasks making our lives easier and freeing us up to do more fun things.

ChatGPT is the latest in a long line of excited debates – with the CEO of OpenAI now suggesting that his ambition for the technology is for it to become a ‘reasoning engine’, so therefore not just a fact database. But the problem is (and this has been highlighted through various tests and articles) that implementing automation, never mind autonomy, is really quite hard.

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AI is changing the world. You have an infusion of AI at every step in the process, whether you talk about the first mile or the last mile. Whether you talk about AI being used to intelligently and automatically capture paper-based invoices or to enrich, augment, and predict incomplete data. But you can’t get results from AI if you have data silos. In fact, AI initiatives might fire back if you trained your models with the wrong data.

In today’s episode, our guest, Claus Jepsen, discusses why AI and ML solutions are less effective if businesses still have data siloed. He also discusses Unit4 stories and their unique approach to the cloud. Finally, he discusses issues with the first and last mile of AI and how they each offer unique challenges.

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An ERP system often underpins the core operations of your business, invariably affecting mission-critical functions. Poorly managed, an implementation project can spiral out of control, leading to business disruption, cost escalation and even damage to your reputation. However, when executed correctly, a well-implemented ERP solution presents an opportunity to enable true business transformation, increasing revenue, enhancing customer and employee experiences, helping your company adapt to change and even positively impacting brand equity.

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In a year marked by uncertainty, organizations are looking for ways to reduce operating costs and streamline processes. Efficiency is on the mind of every business leader. Deploying automation to reduce manual work will continue to be a top consideration to achieve this. Company leaders will also consider new ways to build and maintain software and accelerate digital transformation. They’ll also contemplate continuing to move more workloads off-premise and into the cloud — including Enterprise Resource Planning (ERP) functions.

But this will also be a year when businesses get back to basics. They’ll rethink decisions they’ve made in the past and add new talent to manage the growing complexity in their fields. Here are five predictions to watch for in 2023 and what they mean for CIOs and CTOs.

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Cloud computing can offer businesses fast deployment, scalability and reduced costs, but it can also be a surprising tool for reducing your carbon footprint. Today’s customers, stakeholders and employees are ecologically aware, making sustainability a top priority for keeping up in a rapidly changing world.

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Organizations use a variety of applications to handle business tasks, and at the center of many point solutions is the enterprise resource planning (ERP) system. In an ideal state, data from various solutions, such as the ecommerce system, CRM instance, collaboration tools, analytics solutions, payroll systems, etc., would flow seamlessly across the tech stack, with the ERP at the center.  In such an environment, Claus Jepsen, CTO at Unit4, discusses the value of having an integration-as-a-service approach.

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Modern people-centric organizations invest in critical integrations so they can use their ERP systems as a data hub but often lack the time or resources to work their way down the to-do list. Integration-as-a-service offers an opportunity to realize their ambitions of automation—and make time and cost savings as a result.

ERP systems have the potential to act as an organization’s data and transactional hub—but in my experience, this high level of integration is often just an ambition. As a result, I still see a lot of people exporting spreadsheets from one tool to another or using manual interfaces and rekeying data.

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