When was the last time you went into a branch (even pre-COVID)? Or the last time you paid for something in cash?
Financial services have been gradually digitizing for years. It started with digital distribution of existing services. And then the services and service providers started to change. Who still uses their high street bank for FX payments or for buying stocks?
We’re now moving into a new phase where, now digitized, financial products are going to be more and more embedded into other services – either tightly, like payments within the Uber app, or just bundled together for convenience like in super apps.
But while the industry is undergoing this paradigm shift, the way we evaluate the enterprise software on which it runs remains unchanged.
At best, the conventional analysis is becoming increasingly irrelevant but, at worse, it is steering decision makers towards systems that are not fit to address their changing needs.
So we’ve decided to shake things up. We’ve written a report explaining in detail how wealth management is changing as a result of digitization and, as part of the report, we launch The Market Map, a new criteria for evaluating software solutions in the digital age.
Here’s why we think enterprise software analysis is broken and a look at how a new approach would produce radically better results.
From supply to demand
When we talk about digitization, we invariably focus on technology itself, specifically how far it has advanced. But its more significant — and often overlooked — consequence is that business models are also changing.
If the industrial revolution solved the problem of supply and made economies of scale possible, the digital revolution is turning the supply-demand equation on its head.
Supply is no longer an issue because, most of the time, sourcing, distribution, or both can be digitized. Even where creating economies of scale isn’t feasible, the proliferation of as-a-service tools means you can borrow them at a reasonable cost.
Instead, it’s now demand — or, more specifically, customers’ attention span — that’s in short supply.
This shift from supply-side to demand-side economies of scale has far-reaching implications. Mass consumerism is falling out of favour because, with supply abundant, customers don’t have to settle for a limited selection of highly standardized products or services in exchange for affordability.
On the contrary, they now expect to be treated as individuals, and will vote with their feet if their needs aren’t met.
A vicious cycle
If individual consumers are embracing their newfound power and demanding more tailored experiences, enterprise clients — particularly in the financial services space — are yet to smell the (small batch roast) coffee.
Digital transformation has been one of the financial services industry’s top priorities for several years. And Covid-19 has only made the need for it more pressing. But the business models underpinning most firms have remained largely unchanged, in that they’re still predicated on mass production.
The result is that firms tend to approach vendor selection in an anachronistic way. And the system is self-perpetuating.
Procurement teams’ requirements are rooted in supply-side economies of scale. At the same time, the businesses who evaluate enterprise software need to appeal to the enterprise buyer. So, their reports give importance to the criteria procurement teams look for, even though these aren’t necessarily the criteria that matter.
And the cycle continues.
Size doesn’t always matter
The way enterprise software analysis is currently done has two major flaws.
For starters, many reports are directly or indirectly pay to play. Right off the bat, this creates an economic barrier for smaller vendors.
More significantly, even where the economic hurdle can be overcome, vendors may still be let down by the methodology. This is because reports tend to rank on criteria that make sense from a supply side perspective rather than the demand side.
Consider size.
On paper, staff numbers, office locations, and annual revenue are important, because they’re the mark of a financially viable, trustworthy company. In a tightly regulated industry where the stakes are sky high, it’s understandable that firms would prefer an established firm over an untested upstart.
But when it comes to the actual job of launching a new business model, do these numbers matter?
Probably not.
Take revenue. In an on-premises or single instance scenario, whether a vendor makes $5 million or $500 million a year has little significance aside from, possibly, indicating they have more resources to put into R&D.
But bigger R&D budgets and capabilities aren’t as beneficial as you might think. On-premises and single instance upgrades are time-consuming, expensive, and, as a result, infrequent. And in an era where APIs make integrating highly specialized tools quick and easy, it may actually be a disadvantage for software to have a wide breadth of functionality.
If anything, with 80% of digital transformation projects doomed to fail, the bigger risk is investing time and money and undergoing a disruptive implementation phase only to find out your chosen software isn’t fit for purpose.
Of course, this is not to say size never matters. Having a large number of clients is extremely important where a vendor is able to leverage this customer base to externalize network effects by, say, training a common AI model or aggregating services that are useful to the network.
But to deliver these kind of demand-side economies of scale requires a modern technology architecture, which can orchestrate interactions across a network. A lot of older vendors, with higher revenues and more employees, don’t have this.
From one-stop-shop to best of breed
When packaged software became commercially available, it was a vast improvement on what banks were working with.
Before there was an IT industry, banks wrote their own apps in-house at considerable expense. In comparison, packaged software met most of their functional needs and ran on cheaper hardware.
Better still, changes could be applied easily, so the ongoing run-the-bank costs were lower, while it was possible to launch new products much more quickly than in the past.
But, the move to SaaS has changed the landscape entirely.
SaaS is more than just a new delivery model. It has changed the plane of competition. When integration was hard, having monolithic systems with broad functionality was a competitive advantage. Now that integration is less of a concern, the focus has changed to software architecture and the quality of both (narrower) functionality and the user experience.
There are many second-order effects. One is the possibility to circumvent the enterprise buyer to sell simpler and better solutions bottom-up directly to the end user. But another is the move to best-of-breed.
If integration is easier, why would an enterprise buyer not want to source the best functionality, rather than take it all from a single application? This again can make breadth of functionality actually a disadvantage, rather than advantage.
The logical play for incumbent software solutions is to become the bridge to these best-in-class applications, but many applications don’t have the capability or the vendors fear the risk of cannibalization. Either way, this is not something that most software evaluations even consider.
New business models
In the same way as vendors need to start thinking about changing their business models, so do financial services providers.
They similarly need to think about demand aggregation, supply aggregation (becoming a platform) or focusing on the plethora of underserved or overserved customer demographics that can now be reached directly through digital channels.
However, to be able to do, requires them to have different technology solutions. For example, they might need to aggregate multiple (non-financial) data sets or deliver services over third-party distribution channels. But, again, these are not criteria in most evaluation reports.
Introducing the Market Map
So, we have launched a new methodology for evaluating software solutions. It starts from the assumption that, now or in the future, financial firms will need to do more than routine innovation. That is to say, to survive and thrive, they will need to move beyond just distributing existing solutions to existing customers over new channels.
Financial firms will need to undertake non-routine innovation.
Since non-routine innovation is a function of capacity for technology innovation and capacity for business model innovation (and normally both), these are the key criteria we use in our evaluation methodology.
Better outcomes
The way enterprise software is analyzed and evaluated is bad for everyone.
Vendors with exciting products are missing out on growth opportunities. Enterprise customers are missing out on potentially transformative technologies. And analysts are spending time putting together reports that are out of sync with their clients’ needs and, so, ever more valueless.
Clearly, enterprise software analysis is broken. Our bet is that changing the methodology will encourage the industry to embrace tools that, though not fitting the traditional mold, unlock more value at lower cost and allow them to get better at what really matters in the digital age: delivering better services at greater scale.
