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Using Low Code to Overcome Day-to-Day Complexities

Anthony Abdulla
Pega

The last two years have accelerated massive changes in how we work, do business, and engage with customers. According to Pega research, nearly three out of four employees (71%) feel their job complexity continues to rise as customer demands increase, and employees at all levels feel overloaded with information, systems, and processes that make it difficult to adapt to these new challenges and meet their customers' growing needs.

Additionally, more than half (56%) of workers expect the pandemic to accelerate these complexities; however, nearly all (98%) believe that although technology contributes to job complexity, it is also important to their success, presenting a bit of a conundrum.

Despite the promises of digital transformation, many workers aren't experiencing the direct benefits. And with business complexity on the rise, organizations need to urgently address the increasingly complex intersection of technology and the workforce to ensure satisfaction and productivity for years to come. Before redefining a new strategy to reduce business complexity, leaders must first understand the key drivers that are rapidly increasing it. Here are a few areas where organizations can look to make improvements to help their workforce adapt and thrive in today's dynamic working environment.

Manage Information Overload

The volume of available data has outpaced workers' ability to process and use it efficiently. With data pouring in from multiple channels and systems, workers must spend more time pulling data from various sources, deciding the next steps, entering key information manually, and re-routing workflows. Workers spend more time on tedious, manual tasks instead of gaining insights and putting their data to work to build superior experiences for customers and employees. And with the increase of digital-first, remote work following the pandemic, more workers are struggling to find and access the data they need quickly to get their jobs done.

Organizations should be thinking about ways to increase access to information across their organizations and simplify the process of attaining it. Leaders should look to unify systems that triage information in a logical way so workers can tackle tasks efficiently. Layering in automation helps surface critical information across systems and silos that workers need to complete their jobs while providing assistance for lower-level issues. Technology like bots and artificial intelligence can handle lower-level tasks, giving workers more time to focus on higher-level issues that require human intervention and empathic thinking.

Adapt to Rapid Change with Automation and Low Code

With remote and hybrid work adding another level of complexity to the way we've traditionally worked, a host of new challenges have emerged. Workers now need to adapt to new digital tools to communicate and collaborate. This is another area where automation comes in. Coupling operations with technologies like machine learning, predictive and adaptive models, and natural language processing (NLP) to create intelligent workflows that bring together the people and information needed to get work done. They allow workers to tap into data, analyze current needs, provide the best responses at that moment, and self-optimize so you can adapt to unexpected situations with confidence.

Additionally, for firms blindsided by workplace changes triggered by the pandemic, struggling to keep pace with competitors, or feeling lost as to where to start — a collaborative, low-code platform provides excellent change management capabilities. Low code can help empower all of your stakeholders — from business users to citizen developers to pro developers — with tools to adapt workflows as needed and bring together the right people throughout the development process to break down silos and improve communication across teams and disciplines. This means faster innovation and better outcomes for both employees and customers.

Provide Resources to Get the Job Done

When workers can automate the mundane, day-to-day tasks that consume their time, they can shift their focus to more nuanced, innovative work that they were hired to do. However, workers want systems that integrate easily with other technologies, as well as access to better training and technology that's easier to use. In fact, more than a third of workers surveyed in the research above feel their company has increased job complexity compared to five years ago.

Instead of piecemealing projects implemented in isolation, businesses need to take a more unified approach to digital transformation. That means not only addressing complexity with the right tools and technologies but combining them with transparent communication of the organization's strategic business goals, as well as re-skilling and training workers to help them meet (and surpass) the expectations of their roles.

Empowering workers with the tools and training they need to perform their jobs effectively will, in turn, make it possible to supercharge workflows to improve customer and employee satisfaction as well as productivity. The companies that will remain competitive are the ones with the right architecture, approach, and understanding of what digital transformation means and communicate it across their organizations.

Anthony Abdulla is Senior Director of Product Marketing at Pega

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Using Low Code to Overcome Day-to-Day Complexities

Anthony Abdulla
Pega

The last two years have accelerated massive changes in how we work, do business, and engage with customers. According to Pega research, nearly three out of four employees (71%) feel their job complexity continues to rise as customer demands increase, and employees at all levels feel overloaded with information, systems, and processes that make it difficult to adapt to these new challenges and meet their customers' growing needs.

Additionally, more than half (56%) of workers expect the pandemic to accelerate these complexities; however, nearly all (98%) believe that although technology contributes to job complexity, it is also important to their success, presenting a bit of a conundrum.

Despite the promises of digital transformation, many workers aren't experiencing the direct benefits. And with business complexity on the rise, organizations need to urgently address the increasingly complex intersection of technology and the workforce to ensure satisfaction and productivity for years to come. Before redefining a new strategy to reduce business complexity, leaders must first understand the key drivers that are rapidly increasing it. Here are a few areas where organizations can look to make improvements to help their workforce adapt and thrive in today's dynamic working environment.

Manage Information Overload

The volume of available data has outpaced workers' ability to process and use it efficiently. With data pouring in from multiple channels and systems, workers must spend more time pulling data from various sources, deciding the next steps, entering key information manually, and re-routing workflows. Workers spend more time on tedious, manual tasks instead of gaining insights and putting their data to work to build superior experiences for customers and employees. And with the increase of digital-first, remote work following the pandemic, more workers are struggling to find and access the data they need quickly to get their jobs done.

Organizations should be thinking about ways to increase access to information across their organizations and simplify the process of attaining it. Leaders should look to unify systems that triage information in a logical way so workers can tackle tasks efficiently. Layering in automation helps surface critical information across systems and silos that workers need to complete their jobs while providing assistance for lower-level issues. Technology like bots and artificial intelligence can handle lower-level tasks, giving workers more time to focus on higher-level issues that require human intervention and empathic thinking.

Adapt to Rapid Change with Automation and Low Code

With remote and hybrid work adding another level of complexity to the way we've traditionally worked, a host of new challenges have emerged. Workers now need to adapt to new digital tools to communicate and collaborate. This is another area where automation comes in. Coupling operations with technologies like machine learning, predictive and adaptive models, and natural language processing (NLP) to create intelligent workflows that bring together the people and information needed to get work done. They allow workers to tap into data, analyze current needs, provide the best responses at that moment, and self-optimize so you can adapt to unexpected situations with confidence.

Additionally, for firms blindsided by workplace changes triggered by the pandemic, struggling to keep pace with competitors, or feeling lost as to where to start — a collaborative, low-code platform provides excellent change management capabilities. Low code can help empower all of your stakeholders — from business users to citizen developers to pro developers — with tools to adapt workflows as needed and bring together the right people throughout the development process to break down silos and improve communication across teams and disciplines. This means faster innovation and better outcomes for both employees and customers.

Provide Resources to Get the Job Done

When workers can automate the mundane, day-to-day tasks that consume their time, they can shift their focus to more nuanced, innovative work that they were hired to do. However, workers want systems that integrate easily with other technologies, as well as access to better training and technology that's easier to use. In fact, more than a third of workers surveyed in the research above feel their company has increased job complexity compared to five years ago.

Instead of piecemealing projects implemented in isolation, businesses need to take a more unified approach to digital transformation. That means not only addressing complexity with the right tools and technologies but combining them with transparent communication of the organization's strategic business goals, as well as re-skilling and training workers to help them meet (and surpass) the expectations of their roles.

Empowering workers with the tools and training they need to perform their jobs effectively will, in turn, make it possible to supercharge workflows to improve customer and employee satisfaction as well as productivity. The companies that will remain competitive are the ones with the right architecture, approach, and understanding of what digital transformation means and communicate it across their organizations.

Anthony Abdulla is Senior Director of Product Marketing at Pega

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...