VIEWPOINT: Capping the cost of change
For a finance provider, the decision on whether to embark on a major technology transformation marks a critical juncture.
The implications of legacy technology for an asset finance business are well known; it can be a millstone around the neck that hinders growth and efficiency. Legacy systems struggle to keep pace with the drive for digitalization, and the AI boom has emphasized these weaknesses.
That much is understood, but the situation can become clouded by an organization’s collective experience. Scars from past implementations - often long-running or over-budget - make for useful learnings, but can obscure the cost of doing nothing.
This article explores practical approaches to controlling transformation costs that can help you manage cost and risk - rather than avoid the challenge altogether.
"Scars from past implementations can obscure the cost of doing nothing."
Make scope a project cornerstone.
When looking to manage the risk and cost associated with a technology project, scope control is the first port of call. This needs to go beyond a statement of intent, set at project inception and quickly forgotten. It should be your project manifesto, clearly aligned with the approved business case and underpinning a broader set of day-to-day governance routines and structures.
This doesn’t mean rigidity - scope can and will change. But ensuring it does so in line with a clearly outlined change control approach is critical to the assurance that all options have been weighed fairly, especially in light of cost and impact on the overall program.
"Scope should be the project manifesto, aligning with the business case and underpinning daily governance routines."
Involve the right resources at the right time.
Ensuring the right SMEs from the business and technology are engaged in the project from day one is critical. They are ultimately responsible for the day-to-day direction of the project: requirements, decision-making, change control assessments, and coordination with the rest of the organization. Leaders should avoid asking those resources to perform multiple roles at once, as doing so can result in bottlenecks and subsequent delays - ultimately increasing long-term cost.
However, to achieve the velocity required to deliver the project while balancing the opportunity cost on operations, in-house SMEs can be bolstered with both vendor and system integrator (SI) resources. Selecting vendors with delivery experience, a strong track record, and a clear cultural fit will pay dividends down the road.
The mix of customer and vendor resources is ultimately a balance that can vary by project, depending on factors such as scope and complexity. This balance may not be struck immediately, and may change as the project progresses. A strong governance structure is the answer, flagging resourcing challenges to leadership quickly so they can pivot accordingly.
"The mix of customer and vendor resources can vary as a project progresses. Strong governance can flag challenges with leadership so they can pivot accordingly."
Gravitate towards predictable outcomes.
Like any task involving people and technology, a complex technology transformation can be unpredictable. However, not every group or platform exhibits the same level of unpredictability, and project leadership should look to maximize the number of predictable outcomes.
One example of this is platform hosting. Historically, finance providers would need to find a way of hosting a vendor platform, which involved establishing teams, infrastructure and tools to support the most basic function: keeping the system on. But vendor-hosted solutions now offer low-risk, high-quality solutions with clear costs that evolve and strengthen over time.
Equally important is core platform selection. Choosing a vendor with appreciable experience implementing in your industry and a keen understanding of the challenges - whether those are scale, compliance complexity, or automation requirements - is a vital step towards a predictable outcome.
Similarly, some vendors offer preconfigured versions of their software platform, based on established industry best practice. Because they’re configured in advance, these offerings are comparatively quick and cost-effective, delivering considerable gains in predictable outcomes.
"Project leadership should look to maximize the number of predictable outcomes by choosing experienced vendors."
Keep an eye on long-term sustainability.
Implementation costs are often the focus when tracking against budgets. But new long-term costs associated with a modern technology platform should be assessed with the same diligence.
One of the most common pitfalls is a lack of ‘application ownership’ (the ability for a business to take control of its software platform, usually through configuration), often resulting in a long-standing dependency on vendor services.
Avoiding this problem starts with the vendor. Their offering must be highly configurable and backed by comprehensive documentation. Custom code should be avoided because, although it may provide a quick win, it can complicate future upgrade paths. It’s wise to embrace this approach by establishing your required long-term resource structure and investing in knowledge transfer accordingly.
In turn, this eases scope control. Knowing that changes can be made easily and efficiently after going live can help win hearts and minds on controlling scope. This also simplifies platform upgrades, enabling new features to be implemented and the platform's real benefits to be realized.
"Ensuring high levels of configurability, establishing your required resource structure, and investing in knowledge transfer can help avoid a costly long-term dependency on vendor services."
Incorporate the latest and greatest technology.
Technology transformation often requires a large amount of manual effort, much of which is ripe for disruption by the latest AI tools.
For example, technology transformation often requires substantial up-front analysis: what does the landscape look like today, and what does that mean for tomorrow? Translating old documentation, disparate data sources, and legacy code into understandable requirements is a task that AI can and should support, without requiring extensive specialized resources.
This can also apply to system testing. Deploying AI-driven tools to perform as much automated testing as possible is a key driver of platform success, reducing the need for an army of test resources and paving the way for the rapid implementation of upgrades and new features.
"Translating old documentation, disparate data sources, and legacy code into understandable requirements is a task that AI can and should support."
Talk to Alfa.
At Alfa, we’ve been delivering complex implementations for more than 35 years, and these are just some of the lessons we’ve learned along the way.
We’ve invested continuously in our delivery capability during this time, drawing on learnings from a wide range of customer business models. This investment can take the form of tooling that simplifies day-to-day implementation tasks; establishing a low-cost, customer-owned data migration tool; or developing a specialized methodology that delivers our best-in-class software at entry-level cost.
Our solution to this challenge is the market-leading Alfa Start - preconfigured SaaS, tailored to your market - which enables customers to go live in as little as 24 weeks.
We take the best-in-class Alfa Systems software platform, preconfigure it with industry best practice, and deliver affordable efficiency into your business - in a timeframe that works for you.