Cooperatives cooperating. Now there’s a big idea for 2016.
Well … yes, actually.
It’s not that credit unions don’t cooperate today, they do, and in many different, constructive ways. It’s that our movement faces new kinds of challenges that call for a new approach, a fresh paradigm that shifts scope, focus, nature, and priorities.
Traditional models of collaboration fall broadly into two categories. What I will label Collaboration 1.0 is the extension model, engaging a large cross-section of credit unions to extend the reach and capabilities of the credit union system as a whole. There are many such organizations including the leagues, Filene Research Institute, and many large CUSOs that come to mind as prime examples.
Collaboration 2.0 is driven by cost reduction and the need to aggregate sufficient scale and volume to support ancillary activities. There are myriad examples from core processors to specialists like myCUmortgage and back-room consolidators like S3, Shared Services Solutions.
Learn more about cooperative operating models in "Co-Sourcing: How 3 Credit Unions Collaborate On Back-Office Ops," "Survive Together Or Merge Alone," and "Partners In Progress."
Both approaches deliver efficiency, greater capacity and capability, more choice and flexibility for client credit unions, and good financial and functional ROI for member-owners. But too many CUSOs of both types seem to have a self-interested approach to competition that focuses on maximizing market share and income rather than service to clients, their member-owners, and the movement as a whole. This competition among collaborators threatens to undermine what should be the greatest differentiating strength of credit unions.
Theory And Practice
Harvard Business School professor Clayton Christensen identifies three different types of innovation. The baseline, Sustaining Innovation, is an organization’s steady development and delivery of new and extended capabilities to keep abreast — or even ahead — of the needs and expectations of its most valuable customers.
The best at this are market leaders whose ability to innovate is a significant competitive advantage. For most companies though, and virtually all credit unions, this is primarily a matter of not getting left behind. In this cause, our movement is well served by the existing collaboration paradigms.
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To move into Collaboration 3.0, we need to embrace what Christensen calls “Disruptive Innovation.” Not disruptive in the buzz wordy sense, but as Christensen defines it.
According to Christenson, Low-End Disruption is the delivery of a better value proposition to middle-market consumers who feel over-charged and ill-served by market leaders who always focus on their most demanding and profitable customers. Low-End Disruption means providing products and services that might not be at the top of the market but are good enough to meet the needs and expectations of most consumers — and to do so at an attractive price.
New Market Disruption occurs when the value proposition is improved so much that new consumer segments have access to products or services previously beyond their reach.
To move into Collaboration 3.0, we need to embrace Disruptive Innovation.
In both cases, it is the outcome that matters. New technology is not necessarily disruptive from a market perspective; it might not even be innovative from a market perspective. The same goes for a new business process or new business model. It is what you do with these innovations that determine their impact.
Those that have done the most — companies like Apple, Google, Facebook, and Amazon — have leveraged three closely related sets of innovative approaches alongside all their new technology: platform structures, the network effect, and advanced data analytics (“Big Data” for buzzword fans.).
Platform structures are open systems with clear, consistent standards for data and access to information sets that have traditionally been trade secrets. This attracts innovators who — assured of access to an open platform — invest in the creation of new tools and capabilities that integrate with the core platform in a modular fashion and provide users with more ability, flexibility, value, and control than traditional business structures. That is the network effect: the generation of a competitive business ecosystem capable of disrupting incumbent organizations.
Building this sort of framework should be easy for credit unions, but it won’t be. Existing credit union systems and data structures are highly differentiated and generally incompatible. Changing this will require those that control access to processes and data to transform their operating models, replace proprietary systems and restrictive business practices, and change their myopic competitive focus from beating one another to enabling their credit union clients to be more competitive with the fast growing array of for-profit financial services providers.
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The network effect also has the advantage of facilitating scale, both true scale and virtual scale aggregated across those involved in the network.
Scale drives down cost — a traditional CUSO attribute — and in a properly designed setting, scale can also drive up adaptability and quality of results, which are two crucial attributes when trying to drive innovation, particularly in the realms of technology and advanced data analytics.
In fact, scale might be the key success factor for advanced data analytics.
Advanced data analytics is still experimental. Logic, science, and the anecdotal success of early implementers all suggest that investing in it is smart, but the likelihood of success of any single or limited number of specific investments is uncertain. The cost-sharing that scale permits can make this more tolerable for credit unions that often seem hesitant to invest member resources in anything that isn’t wholly proven.
Another reason to seek scale is the basic nature of advanced data analytics itself. It offers a classic example of the multiplier effect of scale. The new array of data — not only traditional, structured data from our own back rooms and trusted partners and public sources, but also unstructured data from social media, shared application platforms, and the Internet of Things — is full of what the experts call “noise.”
The value of advanced data analytics comes from finding the signal in the noise — a concept introduced by statistician Nate Silver. The real competitive advantage of advanced data analytics comes from finding the faintest and most obscure of those signals. The more data, the easier it is to find them.
The Real Prize
Of course, there is risk in this notion of Collaboration 3.0. It means today’s proprietary-minded CUSOs and service providers must put themselves to a rigorous new competitive test because open systems free clients to pick up and go somewhere else if they aren’t satisfied. It also means managing things in an entirely new way, allowing for limited “loss” in traditional terms to make the ultimate outcomes better for everyone.
Today’s proprietary-minded CUSOs and service providers must put themselves to a rigorous new competitive test.
But that’s the real prize, eschewing competition among one another — and particularly among our CUSOs – and spreading the values of financial cooperatives to every American who can contribute to and benefit from our cooperative model.
Arguably, this is the approach Google, Apple, Facebook, and even Amazon have all taken, fostering a world where short-term cost or sacrifice fosters multiple winners who collaborate as they compete.
Can it work in financial services?
If anyone can make it work, it ought to be the credit union industry. But doing so will require significant strategic, cultural, and operational changes in the way we think and operate. It will require building Collaboration 3.0. If credit unions can do it, they can become the disruptors rather than the disrupted.