Skip to main content

Agile Procurement in Financial Services

Ben Henshall
Red Hat

In today's ever-changing business landscape, more and more companies are operating like software companies. Through the adoption of agile technologies, financial firms can begin to use software to both operate more effectively and be faster to market with improvements for customer experiences. Making sure there is the necessary software in place to give customers frictionless everyday activities, like remote deposits, business overdraft services and wealth management, is key for a positive customer experience.

It has long been established that procurement is an important stage in the adoption of technology to drive innovative investments in the financial services industry. And just as the business looks to be more agile in the use of technology, the technology supplied need to be available to the business quickly. This gives way to the notion of agile procurement.

Agile procurement is the idea that the supply of technologies and the associated services can also be acquired in a flexible, agile manner. Agile procurement follows a similar principal as agile development and operations (DevOps) practices in that it introduces new policies and ways of working and can become a better means of accelerating procurement of next-gen applications. Agile procurement processes work to improve technology adoption to be more timely and in step with business and development teams. Indeed, improving collaboration across teams and improving technology vetting processes, policies and organizational barriers in this redefinition of procurement procedures.

In today's business landscape, it is important that companies work quickly and are not bogged down by long lead times and requirements gathering, slow feedback cycles, multi-tier governance and approval policies. And when these detriments to speed to market are combined, they can stymie company goals leaving customer needs unfilled. Agile procurement is focused on the longer term success and adoption of technology, focusing the results that can be gleaned from applying new, innovative technology in practice, rather than in concept. Starting with business and technology teams agreeing on a specific minimally viable product (MVP) necessary to reach the desired business outcomes, a portion of the procurement budget is used to acquire only the necessary technology to use in the pilot.

This more inclusive decision-making replaces process, focused on business outcomes counters traditional, central planning approaches and by default, makes processes more agile given all parties needs are included from the start. The focus is then able to turn to delivering code and features into a production-ready application within tight timeframes. During this process, development, testing and ops, in addition to an assessment of a technology's impact on policy, processes and people are considered, so that the impact of the application and associated technology adoption become integral to the pilot process. This in turn, alleviates the traditional after-thought of technology acquisition, namely adoption.

In order to have agile procurement, financial services first must ensure they have agile development in place — in fact the two, hand-in-hand makes it easier to be able to keep up with changing market factors and business requirements.

One of the main outcomes of agile procurement is that compared to traditional procurement methods, it results in lower procurement and production costs. It costs far less to make changes to MVP deployment done in a short production window (especially with a microservices approach) than one done over a longer period of time, using processes that don't account for micro-adjustments. This is partly because when agile procurement is in place, the organization can more quickly develop and deliver code, and the quicker code is delivered, the longer the company has to cross-sell and pursue other revenue-generating options.

Agile procurement can lead to positive business outcomes, and the culture and road to get there is quickly realized with the use of enterprise open source. Secured by design for organizations, enterprise open source is a path to new, innovative technologies. Organizations that have agile procurement in place can more quickly adapt to business change, solve shared problems faster and use open source standards to preserve business agility while cutting down costs and providing new innovations that can keep up with business needs and customer demands.

Ben Henshall is Senior Director, Financial Services, at Red Hat

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

Agile Procurement in Financial Services

Ben Henshall
Red Hat

In today's ever-changing business landscape, more and more companies are operating like software companies. Through the adoption of agile technologies, financial firms can begin to use software to both operate more effectively and be faster to market with improvements for customer experiences. Making sure there is the necessary software in place to give customers frictionless everyday activities, like remote deposits, business overdraft services and wealth management, is key for a positive customer experience.

It has long been established that procurement is an important stage in the adoption of technology to drive innovative investments in the financial services industry. And just as the business looks to be more agile in the use of technology, the technology supplied need to be available to the business quickly. This gives way to the notion of agile procurement.

Agile procurement is the idea that the supply of technologies and the associated services can also be acquired in a flexible, agile manner. Agile procurement follows a similar principal as agile development and operations (DevOps) practices in that it introduces new policies and ways of working and can become a better means of accelerating procurement of next-gen applications. Agile procurement processes work to improve technology adoption to be more timely and in step with business and development teams. Indeed, improving collaboration across teams and improving technology vetting processes, policies and organizational barriers in this redefinition of procurement procedures.

In today's business landscape, it is important that companies work quickly and are not bogged down by long lead times and requirements gathering, slow feedback cycles, multi-tier governance and approval policies. And when these detriments to speed to market are combined, they can stymie company goals leaving customer needs unfilled. Agile procurement is focused on the longer term success and adoption of technology, focusing the results that can be gleaned from applying new, innovative technology in practice, rather than in concept. Starting with business and technology teams agreeing on a specific minimally viable product (MVP) necessary to reach the desired business outcomes, a portion of the procurement budget is used to acquire only the necessary technology to use in the pilot.

This more inclusive decision-making replaces process, focused on business outcomes counters traditional, central planning approaches and by default, makes processes more agile given all parties needs are included from the start. The focus is then able to turn to delivering code and features into a production-ready application within tight timeframes. During this process, development, testing and ops, in addition to an assessment of a technology's impact on policy, processes and people are considered, so that the impact of the application and associated technology adoption become integral to the pilot process. This in turn, alleviates the traditional after-thought of technology acquisition, namely adoption.

In order to have agile procurement, financial services first must ensure they have agile development in place — in fact the two, hand-in-hand makes it easier to be able to keep up with changing market factors and business requirements.

One of the main outcomes of agile procurement is that compared to traditional procurement methods, it results in lower procurement and production costs. It costs far less to make changes to MVP deployment done in a short production window (especially with a microservices approach) than one done over a longer period of time, using processes that don't account for micro-adjustments. This is partly because when agile procurement is in place, the organization can more quickly develop and deliver code, and the quicker code is delivered, the longer the company has to cross-sell and pursue other revenue-generating options.

Agile procurement can lead to positive business outcomes, and the culture and road to get there is quickly realized with the use of enterprise open source. Secured by design for organizations, enterprise open source is a path to new, innovative technologies. Organizations that have agile procurement in place can more quickly adapt to business change, solve shared problems faster and use open source standards to preserve business agility while cutting down costs and providing new innovations that can keep up with business needs and customer demands.

Ben Henshall is Senior Director, Financial Services, at Red Hat

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...