IT teams need to optimise and tackle tech debt ahead of economic downturn, warn analysts

IT teams have been advised to focus on cost optimisation and tackling tech debt ahead of what is likely to be a period of shrinking budgets and economic downturn.

Many companies’ IT departments can expect a marked reduction in spending in the coming years and will have to scrutinise every investment in their tech stack to ensure it remains viable in the long term, according to researchers at Forrester.

The change in approach to IT spending will contrast with that of the last major economic shakeup at the start of the COVID-19 pandemic.

In early 2020, the main focus for companies was on spending big to ensure digital infrastructure was in place to facilitate widespread remote working.

“The response to the current economic headwinds will necessitate optimisation and [portfolio] rationalisation while maintaining resilient, modern environments - all without undercutting the organisation’s future fit tech strategy,” said Chris Gardner, VP, research director at Forrester.

IT departments are advised to scrutinise every tool and process, looking for potential economic savings. However, certain investments should be pitched and defended, since they may lead to large long-term savings.

Investments in tools that optimise cloud costs, for example, is one area in that IT teams may look to either increase or defend their investments, according to the analyst house.

Compute and storage demand is only going to increase, it said, and cloud will continue to be a key deployment model. Since businesses already pay a premium for the flexibility and scalability that cloud computing offers, optimising this cost will be crucial in mitigating economic headwinds.

Resilient operational infrastructure is another area that could lead to long-term savings, both in terms of minimising operational downtime and ensuring the smooth running of remote-working technology.

On the technical side, it's recommended that businesses identify declining, old, or risky investments, and phase out the spending on these.

Virtualisation environments can be replaced by cloud-native technology, for example, with containerised platforms and cloud development environments becoming the industry standard in this space.

Unintelligent and otherwise declining technologies in the operational space, such as alerting platforms, are becoming less popular. Integrated platforms like Atlassian Jira Service and ServiceNow are more in-favour and replace sub-optimal systems with bring your own device (BYOD) approaches.

Forrester said staff-related expenditure should also not be ignored; it will always be the most expensive outlay for a business, much more than hardware and software expenditure combined. For this reason, companies may look to outsourcing as a cost-cutting measure since managing legacy applications drives up staffing costs, it said.

Defending investments in automation and cloud-native processes could also go a long way in mitigating this cost.

Emerging technologies worth a gamble

Despite cost-cutting measures being inevitable, businesses are advised to continue experimenting with certain technologies so that business innovation and momentum remain uninterrupted.

Continuing to experiment with technologies, while optimising costs in other areas, will allow organisations to ride the economic downturn and emerge stronger since they will be competitively different having adopted these technologies.

Cloud-native computing and the elements it brings such as Kubernetes, microservices, and immutable infrastructure can be deployed in private, public, or hybrid environments and enable scalable business agility.

Investments in edge intelligence can redirect compute resources close to where the data is generated and away from data centres or public cloud environments.

Edge intelligence and analytics tools can especially help organisations that collect large amounts of unstructured data, Forrester said.

AI-assisted code-writing tools can also help development teams in building and testing new software. It can help speed up the development process by suggesting code refactoring and other changes that could otherwise take longer without automation deployed.