The Decision Maker

Amazon vs Borders: A Lesson for Credit Unions

Posted by Paul Ablack on Dec 6, 2013 6:17:05 PM

 

In the book Competing On Analytics by Davenport and Harris, Amazon is featured as an “Analytic Competitor”. Amazon was a new entrant to a very mature market and within 10 years became a leader in a market that saw the demise and eventual bankruptcy of a formidable competitor. Why is this story relevant to credit union leaders?

I am an enthusiastic supporter of a flourishing Credit Union movement. Since 2009, the industry has experienced growth in membership, net assets, ROA, and capital. From a business strategy perspective these are noteworthy achievements. Yet, there is an absence of a true “leapfrog” strategy to move credit unions to the next level of competitive advantage. When I look at the changing competitive landscape of today’s credit unions, I think that much can be learned from the recent history of Border Books and Amazon.

Borders was once firmly established in the retail book market. They had a large customer base and over 500 brick and mortar locations where customers could enjoy the Borders experience. When Amazon entered the market, they had no customers and no locations. All they had was a commitment to use data to run every aspect of their operations and a vision to be an “Analytic Competitor” (Competing On Analytics). How was it possible for Amazon to take down an established and well-liked retailer? The chief reason is Borders chose to compete on more traditional retail tactics and ignored the data.

Once a common site in most major metropolitan areas, Borders book stores were founded in 1971 and evolved into an international retailer with hundreds of stores spread across many countries. Founded in 1994 by Jeff Bezos, Amazon sold its first book on-line in 1995. The concept of online retailing was at first considered to be a fringe market at best. Critics doubted books could be sold on a large scale in such a manner. How could a “virtual” Amazon compete without a geographically dispersed network of locations? Few predicted this fledgling online retailer, a survivor of the dotcom crash, would sell more online than its 12th largest competitor and produce a return to shareholders of over 12,000%!

In 1995, Borders clearly had the upper hand. They had hundreds of locations (think branches) across the world where customers could come in and browse books and make purchases. Their customers stayed loyal for a number of years after Amazon first appeared. Eventually, however, they started to migrate away as Amazon enticed visitors with helpful reviews and suggestions on what others like them were purchasing. Unlike Borders, the Amazon management team invested heavily in data analytics technology. This made it possible to create an intimate relationship with the customer base that strengthened with each visit to the site. Borders on the other hand, saddled with a heavy investment in real estate, chose to stay with what worked in the past, the traditional retail model. They failed to embrace the “online” strategy and actually outsourced that portion of their business to Amazon.

In February of 2011, Borders books declared bankruptcy and liquidated their stores. Today Borders remains only a brand name.

In 2008, at a business school reunion, I chatted with a classmate who worked for Amazon. I was curious about his employer’s winning strategy. He attributed their success to an obsession with analytics. Amazon had committed to a vision to become an “Analytic Competitor”.

Amazon built their business around a core data strategy that would integrate all of their business processes into a single repository and then churn out analytics to drive efficiency and effectiveness across the enterprise. On the customer facing side of their business, data on every click and transaction made on their site was collected and stored in their data warehouse. From these data, valuable analytics were applied, allowing them to create an intimate “relationship” with customers. For all of us who have experienced Amazon, we’ve become dependent on the reviews and suggestions when making a purchase decision. This is all driven by analytics, the engine that drives Amazon. So what does this mean to the credit unions (and small to mid-sized retail banks)?

Unlike Borders, credit unions are very aware of the aging membership base and the changing role of the branch. They are investing heavily in mobile technology to allow members to interact virtually. However, while these changes are necessary and important to the future of these credit unions, they will not provide the kind of leapfrog effect that will be required to stake a leadership position in this industry. Credit unions today sit on a mountain of data that gives them a unique advantage over any looming competitors. Unfortunately, less that 5% of the credit union industry has embraced data and analytics as a core foundational element of their growth strategy.

In the last two years, new competitors like PayPal and Google have entered the retail financial space. These are large companies with well-known brands that aspire to become the virtual bank for the younger generations of members who are very comfortable with mobile devices. What these upstarts lack, however, is experience, infrastructure and the data accumulated over years of member transactions. Today, credit unions have a distinct advantage in the volumes of data that they collect about their members and the way they spend and save their money.

This is a gold mine of data that could be integrated and turned into valuable information to be used to build relationships with the entire member base. More importantly, it will become a key factor in the ability of credit unions to attract and retain younger members.

Imagine a credit union mobile application that would allow members to set a reserve in their accounts and give daily updates on their balance remaining until the next paycheck deposit. Before making a purchase decision at a store, a member could consult with their credit union application and see impact of their purchase decision on their average daily allowance for the rest of the month. Imagine the ability to “push” information to the front line staff that allows them to recommend the next best product to members based on “basket” analysis that identifies complementary products. Imagine being able to quickly track and trend information about what products members are using while also monitoring check account penetration for new members. The possibilities are endless when all of your member transaction data is integrated into a single repository.

This type of innovative application is driven by data warehousing and analytics. Unfortunately, there has been a lack of attention to this area at credit unions. Data warehousing and analytics today is perceived as an expensive technology investment that is beyond the budget and expertise of most credit unions. Unlike Amazon, data warehouse/analytics is relegated to the status of another “project” to be prioritized. Suppose someone had presented the Borders leadership team with a proposal to invest in a strategy to become an analytic competitor? In 1995, they probably could have not justified the ROI and rejected the idea.

There are some credit unions that have built their own data warehouse/analytics infrastructure. Unfortunately, this is a mere handful of the credit union industry. The reality is that over 95% of credit unions today use Excel as their primary reporting tool.

The idea of becoming an “Analytical Competitor” is only now being discovered by a small number of forward thinking credit union CEOs. For the rest, they rely on a mixed bag of Excel, MCIF, and CRM systems to churn out metrics that have not changed in 10 years.

To be sure, the cost of building a traditional data warehouse and maintaining it is beyond the reach of the majority of credit unions. Some have tried to save money by doing it on their own. However, the quality of many I have encountered are a shadow of what an industrial-strength data warehouse/analytics platform should be.

While technology is a core foundational element of the strategy to become an “Analytical Competitor”, there are other organizational aspects that must be considered. Below is a list of four strategies to move forward:

  1. It starts with culture. Become a data driven and performance driven company. This does not just focus on the financial aspects of the credit union, but all aspects including member services.
  2. Use data to drive transparency and accountability.
  3. Use data and analytics to provide managers greater visibility into their own performance.
  4. Do what everybody else is not doing.

Take your choice: Amazon or Borders? In the credit union of the future, which model do you think will thrive? Think data and analytics if you aim to build toward future success in the credit union world.

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Topics: Data Analytics