Companies must fix their unstable tech stacks to boost productivity

The UK has long struggled with a productivity puzzle. Before the 2008 financial crisis, the country managed to increase productivity by an average of 2% a year, but after the recession this rate of growth decelerated significantly and has failed to recover. In fact, recent statistics from the Office for National Statistics show that the UK is trailing behind other G7 countries – UK productivity is and is roughly 19% lower than the US.

This lack of productivity growth is even more puzzling given the record levels of business spending on IT and technology in the UK. According to a digital leadership survey from Nash Squared, tech spend in the UK in 2023 is set to grow at its third fastest rate in 15 years.

So what is causing this persistent gap between IT investment and national output? There are a few factors at play, including a persistent tech talent shortage, obstacles preventing employees from adopting technology such as knowledge and skill gaps, and the fact that a significant proportion of most technology budgets are spent sustaining legacy systems instead of on innovation – according to one statistic, companies spend $85 billion annually on fixing and maintain outdated technology, while Gartner predicts that 40% of IT budgets will be spent just on technical debt by 2025.

However, the fundamental problem facing companies of all sizes concerns the IT stack. For years, businesses have acquired various pieces of software to solve specific business challenges but have not done this strategically, failing to consider how these different technologies, tools and applications will fit together as part of a cohesive, efficient workflow. As a result, organizations have built unwieldy tech stacks based on disparate systems, which has led disconnected data, fragmented workflows, and poor user experiences.

The problems caused by a fragmented tech stack

For data to flow smoothly between different systems and applications, integration is vital. But fragmented tech stacks make this integration more complex and time-consuming. It results in data becoming splintered across multiple touch points or lost in data siloes, making it challenging to gain a full comprehensive view of the business.

This limited visibility prevents organizations from using this valuable information to generate the insights needed to power data-driven decision-making, and hamstrings innovation. One solution is to have employees manually correlating and keeping track of data, but these are mundane tasks that are not the most efficient use of an employee’s time.

Another issue caused by a fragmented tech stack is a lack of scalability, which restricts a business’s agility and growth. Every additional tool or piece of software requires management, oversight and maintenance, which drags on IT resources. Companies need to refine their tech stack, so that their tools are more integrated, easier to scale and adopt, and free employees from mundane tasks so they have more time to dedicate to innovation.

The value of combining automation with AI

According to The Future of Work 2023 Report from Infosys, digital automation tools and modernization are the top investment priorities for most executives in the year ahead. The survey of industry leaders from around the world found that 30% of organizations were investing in automation to help boost profits and productivity.

These tools can help organizations boost efficiency and reduce costs, as well as improve the user experience for customers and employees and achieve greater business agility. Combining automations with artificial intelligence (AI) can also provide businesses with real-time insights and enable faster innovations.

In fact, a recent report by Bain and Company highlighted just a few ways that AI and automation are helping companies to improve their business outcomes. Banks like HSBC are using the technology to fight money laundering and fraud, while delivery firm UPS uses AI to optimize delivery routes to save fuel and reduce carbon emissions. Meanwhile, consumer goods giant Procter & Gamble is saving around $60m a year by using AI and automation to more accurately model inventory levels. According to Bain and Company, around 40% of businesses are adopting or evaluating use cases for more advanced generative AI in their operations.

Further benefitting this trend is the rise of low-code/no-code technology, which addresses the skills gap by making AI and automation more accessible to workers, allowing businesses to implement them more quickly and at lower cost. The additional advantage of low-code/no-code automation platforms is that it empowers workers to make changes to any automations themselves, rather than relying on overstretched IT departments, especially as IT employees may be poorly suited to addressing these demands quickly over time or unaware of which AI workflow automations can benefit specific lines of business.

Given these trends, forward-thinking organisations across different sectors are looking to realise the benefits from both integration and automation. By integrating AI into everyday workflows, productivity and efficiency can significantly improve, as they help to democratize innovation, allowing anyone with the organisation the chance to test out their ideas on how to automate a task or business process. Integrating AI within your business’s automated workflows also offers the advantage of greater security and privacy, rather than using an external AI provider.

Adopting automation into the tech stack

We have seen businesses adopt a few different approaches to incorporating automation. A common approach is “hyper automation”, where enterprises attempt to automate as much as possible, as fast as possible – though this approach may not be appropriate to all businesses.

Successfully integrating automation and AI can not only resolve a fragmented tech stack but also increase an organization's operational efficiency, productivity and scalable growth. However, businesses do need to carefully consider how they will approach this integration process; in order to support large-scale digital transformation, companies must ensure their processes are democratic. They need to communicate with and engage teams across the business, and ensure the technology is available to multiple business operations including finance, HR, sales, marketing and customer support.

A key aspect of this integration process is to avoid forcing employees to create their own account with a separate AI platform they must learn to use. This will not only exasperate the fragmentation of the tech stack, but it may also introduce security risks for your business if sensitive data – such as financial statements or personal identifiable information – moves between different applications. Instead, look to bring the AI platform and its capabilities to the places where your employees already work from, such as your communications platform. Using a chatbot interface can guide your employees into making effective AI prompts and automations by providing advice, tips and tricks. This will help to ensure greater adoption among your workforce.

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