By James Maxfield, Chief Product Officer, Duco
I’ve talked to lots of firms across the capital markets space who have successfully delivered transformation projects. But the number of projects that succeed in the industry is dwarfed by the number that fail – often before they’ve even gotten off the ground.
Effecting change within a complex organisation is difficult, especially because the process for doing so tends to overlook a foundational pillar of change (data) and is at the mercy of an investment cycle that simply isn’t engineered to allow cross functional change.
For most investment cycles within capital markets firms, the process includes some fairly standard steps. Namely:
- Functions figure out their objectives (usually, but not always, aligned with company strategy). E.g. operations or risk departments work on objectives for the next year to support their own agenda.
- IT teams that support these functions then typically review these objectives and align their investment needs around supporting these outcomes (usually, but not always, the case…)
- The CFO or budget holder reviews all of the functional requests and challenges/approves the funding needed.
Now, this works fine where the outcome sought is internal to the function, such as more automation in the operations reconciliations process. But it’s less effective around cross-functional investment, like where a market change such as T+1 means there are end-to-end changes needed.
The optimum operating model for coping with shortened settlement windows requires a proactive approach to managing data, i.e. fixing the cause of errors rather than waiting around for the errors to appear and then addressing them. But while the solution is to head upstream, the way budgets are allocated don’t allow for this kind of journey.
Instead, the settlement platform owners, and the teams that work on them, end up in a situation where they have budget, but can’t use it to solution the whole problem, as this typically sits outside of their sphere of influence. And, typically, the other functions impacted are tied up with their own objectives.
Short term, the over-funded win as they spend the money on other things – (oh yes, you do) but longer term this ends up in a failed outcome.
Though meaningful transformation needs to be front to back, budgeting doesn’t work in that way. Which makes anything outside of small, functional change prone to fail…
“A successful transformation relies on close collaboration and coordination across the organization. However, many banks continue to operate in traditional functional or business silos, which leads to conflicting or misaligned priorities, lack of clarity, and a fragmented approach to execution.” McKinsey, 2023
The result of this internal fragmentation means big ticket objectives or agendas become very difficult to pursue – or at best get delegated to functions who usually lack empowerment or influence to really make them successful. And T+1 is just one of many examples where the investment cycle ties the hands of teams, and as an unintended consequence commits the organisation to another period of operational inefficiency.
Take the emergence of the chief data officer (CDO) as another example. It created some impetus to organisational change around the cost and complexity associated with poor data. But these roles became either ivory-towers or an internal think-tank that were all too easily ignored.
Which is problematic, because, when you get down to it, data becomes the key vehicle for most front to back transformation, as it creates a lot of internal inefficiency to manage it day to day. And unlike budgets, it does flow across organisational boundaries. Errors in one function can cause pain in others. Operations simply can’t get its house in order if the neighbours aren’t on board.
But there is organisational inertia around being able to think differently about it. And, whilst lack of data ownership internally is typically acknowledged as the challenge (who sources it, cleans it, distributes it), individual functional agendas usually can’t solve the problem.
So, although the appetite is there, the ability to organise around a data driven transformation agenda is not.
“While 91.9% of companies report that they have achieved some measurable value from their investments in data and analytics, just a dismal 23.9% say they have created a data-driven organization, and an even more paltry 20.6% of firms report having established a data culture.” HBR
So how do you solve it?
Investment spend ultimately has to be aligned with the outcomes sought by the C-suite to drive material, transformational outcomes. This has failed to deliver any meaningful change to the business models of capital markets firms over the last decade, making their economic fortunes heavily predicated on revenues and the fact they’re unable to shift their profitability (RoE for the whole banking sector has been persistently c9% for the last 15 years).
If you compare that with the level of transformation seen in other industries, who have embraced front to back thinking (such as those that have become obsessed with customer journey thinking), you can see how much opportunity has been left on the table. And also the impact technology has been able to have on their operating models.
As for what to do….
1. Budget centrally and align these to F2B outcomes that drive F2B value
This could be customer journeys, increasing trust in data, faster delivery of reporting, etc.
2. Allocate funding to initiatives that are aligned to these outcomes
Track against realistic outcomes that deliver value; reduced support cost, application retirement etc
3. Govern centrally, ensure oversight over the portfolio and release budget in increments.
Make sure funding is tied to value and measurable milestones (sprints, phases, sub-projects)
4. Encourage initiatives to test/validate assumptions or prototype ideas
These won’t all come off, but those that do show value and can support the hypothesis around the business outcome should be moved forward. This pragmatic approach to transformation avoids getting locked into endless iterations of ROI analysis, as it helps create the case for change.
5. Sponsor and lead
Functional heads need to visibly support the initiatives and sponsor shared outcomes (with shared incentives aligned with these). Encourage collaborative goals and objectives that supercede functional ones.
‘70 percent of digital transformations exceed their original budgets, and 7 percent end up costing more than double the initial projection.’
McKinsey
The old ways of sponsoring and driving change have failed consistently to deliver material outcomes, because business transformation has to be data (not functionally) driven. And this cost of failure is eye-watering – making for plenty of incentive to change…
Thankfully, changing the investment process to recognise that transformation, like data, naturally spans across multiple functions, is not a pipe dream. Firms like Santander are already doing it. This means they’re creating more agile, future-proofed businesses, that ultimately will keep them competitive.
