IT teams need to optimize and tackle tech debt before the economic downturn, analysts warn

IT teams are advised to focus on cost optimization and tackling tech debt ahead of a possible period of shrinking budgets and economic downturns.

Many company IT departments can expect a marked reduction in spending in the coming years and need to evaluate every investment in their tech stack to ensure it remains viable in the long term, according to Forrester researchers.

The shift in IT spending strategy is in contrast to the last major economic shift at the start of the COVID-19 pandemic.

In early 2020, the main focus for companies will be on spending heavily to ensure the digital infrastructure is in place to facilitate mass remote working.

“Responding to the current economic headwinds will require optimization and [portfolio] rationalization while maintaining resilient, modern environments – all without reducing the future tech strategy that fits the organization,” said Chris Gardner, VP, director of research at Forrester.

IT departments are advised to scrutinize every tool and process, looking for potential economic savings. However, some investments should be built and defended, as they can lead to significant long-term savings.

Investments in tools that optimize cloud costs, for example, are an area where IT teams can look to either increase or defend their investments, according to the analyst house.

Demand for compute and storage will only increase, it said, and the cloud will continue to be the primary deployment model. Since businesses already pay a premium for the flexibility and scalability offered by cloud computing, optimizing this cost will be important in mitigating economic headwinds.

A robust operational infrastructure is another area that can lead to long-term savings, both in terms of minimizing uptime and ensuring the smooth running of remote-working technology.

On the technical side, it is recommended that businesses identify declining, outdated, or risky investments, and phase out spending on them.

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

Non-intelligent and otherwise declining technologies in the operational space, such as alerting platforms, are becoming less popular. Integrated platforms such as Atlassian Jira Service and ServiceNow are increasingly favoring and replacing sub-optimal systems with a bring-your-own-device (BYOD) approach.

Forrester says that staff-related expenses should not be ignored either; it will always be the most expensive expense for a business, more than hardware and software expenditures combined. For this reason, companies may look to outsourcing as a cost-cutting measure because managing legacy applications drives up staffing costs, it said.

Defending investments in automation and cloud-native processes can also help mitigate this cost.

Emerging technologies are worth the gamble

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

Constantly experimenting with technologies, while optimizing costs in other areas, will allow organizations to withstand economic downturns and grow stronger because they will be competitively different when adopted these technologies.

Cloud-native computing and its accompanying elements 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 centers or public cloud environments.

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

AI-assisted code-writing tools can also help development teams develop and test new software. This can help speed up the development process by suggesting code refactoring and other changes that might take time without automation being deployed.

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