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Don’t Let the “HOW” Stand in the Way of the “WHAT” in Strategic Planning

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3 minute read – We find that one of the pitfalls of the strategic planning process is that too much focus is placed on the “how” (implementation) before the “what” (strategy) has been decided. Often, decision-makers will gravitate toward the “how” because it feels more tangible but also because it seems to help determine the likelihood of success. This focus can limit a credit union’s strategy to what can we do today versus what should we do – even if we don’t know how to do it right now. The importance of not letting the “how” stand in the way of the “what” can’t be understated in light of the threats to credit unions’ relevancy and sustainability.

Take Apple’s iPhone and Quicken Loans’ Rocket Mortgage as examples. They both started with the “what.”

For Apple, the goal was to:

…develop a phone with an integrated music player, operated by a touch screen.” They’ve clearly accomplished that and more. However, consider the fact that nothing like this existed at the time. Most phones still had physical keypads and didn’t play music. The “how” was so extensive that “it involved rethinking every part of the phone from how to check voice mail to how to display a calendar.” (Apple Engineer Recalls the iPhone’s Birth, Wall Street Journal)

Rocket Mortgage likewise started with the “what” and then moved onto the “how:”

The goal was to allow a person to get a mortgage or refinance their home while standing in line for a cup of coffee.” Like the iPhone, it took Quicken years to figure out how to allow a person to apply and receive conditional approval in less than 10 minutes. Some of the “how” questions they had to answer were, “How do you pull income information…How do you pull asset information from sources that already exist? How do you pull property information? How do you give someone complete transparency into the interest rate and fees and how a person can adjust the interest rate and see what it does to the fees.” (This Could Be the Mortgage Industry’s iPhone Moment, Tech Crunch)

Apple and Quicken Loans faced a daunting amount of “how” questions but that didn’t deter them from landing on the “what” they felt was best for their company.

For credit unions, the message is clear – start with the “what.” Answer questions like:

  • What is happening in the environment around us?
  • What are potential threats, opportunities, etc. that could occur in the future that we want to test drive today?
  • What should our business model be (target market, value proposition, core purpose)?
  • What are our long-term decision filters and strategies for moving the organization forward?
  • What are our measures of success?

Once these questions have been answered and the “what” has been decided then shift to questions of “how,” such as:

  • How will we implement our strategy?
  • How will we improve our processes and manage our projects in order to implement our strategic planning initiatives?
  • How will our mindsets and talent need to evolve?

With the myriad of threats to relevancy and sustainability, it is critical for decision-makers to not let the “how” hinder the “what” that is best for the credit union’s future.

This post was originally published in May 2016, and has been republished due to its current relevancy. 

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What’s the Real Promise of Artificial Intelligence (AI)?

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In our blog of December 7, 2017, we asked the question, “How long do you believe it will be before AI will impact your business model and strategy?”  With options of less than 2 years, 2-5 years, 5-10 years, and greater than 10 years, the responses were heavily weighted toward the shorter end of around 2 years.  Also of interest were the comments, which touched on a range of topics, from the number of jobs that will be lost, to how far down the road it will be before we see artificial intelligence (AI) taking over high-level tasks.

What is the impact of artificial intelligence (AI) on a credit union's business model and strategy?

Some made the point that AI is already here, and we interact with it every day in the form of Apple’s Siri and Google Assistant.  Along those same lines, a credit union recently announced that its members will be the first to have the ability to converse with Alexa, Amazon’s voice-activated virtual assistant, to conduct their financial transactions (Source:  Alexa Becomes Enrichment FCU Members’ New Banking Buddy).

The reality is that AI is a broad term encompassing natural language processing (like Siri), the ability to see patterns and relationships in data and derive insights, and far beyond.  In fact, financial institutions are already using AI for fraud detection, investment robo-advisors, help with regulatory requirements, and more.  It holds great potential for lowering expenses, improving the member experience, and helping to create deeper “relationships” as the definition of relationships evolves in the digital world.

To get a better feel for what might be next, here are a few examples of what some large financial institutions have been up to recently in the AI arena:

COIN – In June of 2017, JP Morgan Chase introduced COIN, short for Contract Intelligence. Using machine learning technology, COIN has exponentially reduced the time it takes to review the 12,000 commercial-loan agreements the bank processes each year and resulted in fewer mistakes.

Chatbots – Also called virtual assistants, chatbots are designed to use artificial intelligence to enable customers to interact via natural language (voice or text).  Bank of America’s erica is one example.  Erica will be incorporated into the mobile app, allowing customers to conduct routine transactions as well as providing financial guidance in the form of smart recommendations.

RPA Bots – Robotic Process Automation (RPA) bots are software applications that utilize artificial intelligence, and are programmed to automate tasks that are typically performed by staff but are repetitive in nature.  RPA technology mimics a human worker, logging into existing applications, entering data, completing tasks, and logging out.  It is designed to eliminate the need to reprogram underlying systems for speedy implementation.  Bank of NY Mellon Corporation has been using this technology to improve efficiency and reduce costs (Source:  BNY Mellon’s Automation Efforts Draw Industry Accolades).

Artificial intelligence can clearly improve efficiencies, but holds real promise in making it possible to know members better.  It can process vast amounts of data from multiple sources, and make connections with the end goal of better understanding members.  There’s a good chance that back when your credit union was founded, staff knew every member personally.  Those days are gone for most, but AI could make it possible to “know” members like that again.

For many credit unions, the member relationship is part of the differentiator that drives their business models.  Having deep, individual knowledge of members available to the front line and in marketing could propel relationship-building to new levels.

For now, just like other developing technologies, it’s best to keep artificial intelligence on your radar screen.  Spend some time imagining how various applications of AI might change your credit union, and continue to broaden your thinking on what it could mean for your membership going forward.

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Sharing Economy Ripe For Disruption By Blockchain Technology

It turns out that the internet is a great matchmaker—even beyond dating sites.  eBay matches buyers to sellers, Airbnb matches rentals to renters, and LendingClub matches borrowers to lenders.  Now, these stars of the sharing economy, many of whom were disruptors, are ripe for disruption themselves.

A definition of sharing economy

These businesses still have a lot in common with traditional business models.  The platform owner ensures that business is conducted as agreed, provides a level of safety, and takes a (sometimes hefty) cut as profit.  This is where the use of blockchain technology has the potential to foster enormous change.

A definition of block chain technology

Take ridesharing as an example, and imagine drivers and riders connecting directly via an app.  They are negotiating their own transactions without a middleman like Uber or Lyft.  (There are already startups doing this.)  Some view this as a more authentic sharing economy where individuals are not beholden to big corporate entities.  Blockchain makes this possible through its ability to provide things like digital identities linked to a publicly available reputation system and cryptocurrency payments—with no intermediary.

While the financial services industry has so far survived the “LendingClubs” of the world, the emergence of blockchain could change the game for better or worse.  Blockchains don’t have to be public.  There is a lot of investment and development underway on permissioned blockchains that can be utilized privately by a financial institution.  These could be used to make the infrastructure far less expensive, create efficient and secure ways to automate contractual agreements, track financial transactions, log asset ownership, etc.

And for once, regulation might be a good thing.  The highly regulated nature of the industry makes it more complicated, time-consuming and expensive for new entrants to carve out niches in this space, especially using new underlying technology.

These are just a few examples of how blockchain could disrupt the sharing economy and financial services.  The possibilities are endless.  It’s like going back to the 1990s and asking what we would be able to do with the internet—even though most of the answers hadn’t even been thought of yet.

*Definitions sourced from Oxford Dictionaries.

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Optimize Your Budget Business Intelligence

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Given all of the time and rigor that typically go into the annual budget process, it makes sense to consider how that process might be improved and generate greater business intelligence for decision-makers.  Beyond creating a base budget, following these 6 steps can help take the budgeting process to the next level and provide leaders a significantly better understanding of potential outcomes.

Diagram showing steps for optimizing your budget business intelligence

1)  Begin with the Baseline Budget
The baseline budget should provide a solid foundation for understanding how the primary strategy is likely to impact financial results.  Building upon the credit union’s strategic directions, the budget assesses the impacts of expected new business goals, deposit generation, investment strategies, non-interest income, and operating expenses.  The budget establishes the fundamental expectations for the core strategy and how it will impact the financial measures for success such as return on assets (ROA) and net worth ratio.

2)  Use a Long-term View
Looking beyond the next fiscal year acknowledges that the budget is not a destination, but a path to the future.  It can be useful to see the longer trending impacts of decisions made today, even while recognizing that uncertainty increases when projecting further into the future.  Our clients tell us they find long-term financial forecasts showing impacts over the coming 3-5 years provide valuable information and an early warning while not wading too far into the uncertain future.

3)  Understand the Impacts of Changing Rate Environments
Asset/liability management (A/LM) should be an integral part of the budgeting process.  After understanding the baseline budget, assess the sensitivity of the budget to interest rate risk (IRR).

This process begins with choosing the market rate assumptions in the baseline budget.  We recommend credit unions develop baseline budgets assuming market rates remain at current levels.  By so doing, the impacts of the strategic assumptions can be isolated from the potential benefit or detriment of changing market rates.  Otherwise, the market rate changes may hide risks and opportunities driven by the core strategic assumptions.

Once the baseline budget impacts are understood in the current rate environment, play through a variety of likely and potential market rate changes, with rates increasing and decreasing, and where short- and long-term market rates move independently (i.e., twisted yield curves).  How sensitive is the structure to those changes in rates?  And what other decisions might be made today that remain consistent with the overall strategy but may reduce potential net income volatility in changing rate environments?

4)  How is the Credit Union Positioned for IRR if the Budget is Successful?
Regardless of how far forecasts look into the future, targets are typically established for the coming fiscal year for measures such as growth in members/assets/deposits, ROA, net worth, etc.  While assessing the impact of changing rate environments along the way, how well-positioned is the credit union for future IRR in 1 or 2 years if the budget is achieved?

Using the target financial structure implied by the budget, how would the A/LM modeling assess IRR at that point in the future?  Is the credit union better prepared for market rate volatility, or did the credit union increase its risks?  Are IRR policy limits and guidelines still being met?  If not, understanding those risks today and weighing options with the board and management could be critical.

5)  Consider Alternative Scenarios beyond the Base Budget
Most would agree that having a clear picture of the future would be a welcome gift, especially during budget season.  Unfortunately, predicting that future can be a tricky business.  Instead, we often look to recent trends to inform us of likely market directions and pressures.

When trends appear likely to impact the credit union’s business model or strategy, it can be valuable to consider the extent of those impacts and likely responses the credit union may take.  Ask how trends might impact the business model, and develop what-if scenarios to understand the potential financial implications while also testing mitigating strategies.

For example, what if the trend data suggested mortgage volumes may slow, and a growing opportunity for more home equity loans?  What challenges or opportunities might that present?  Similarly, what if some regulators warned about the risks of low-cost funding sources going away, and at a time when long-term assets in the industry have been increasing?  What if funding costs increased more rapidly than anticipated?  If concerns exist for the credit union with regard to long-term assets, what options might exist today (i.e., before more of the industry might face similar pressures) to mitigate the risk in some way?

Considering alternative scenarios can better prepare management and boards for potential impacts, and create more informed strategic dialogues.  Modeling such scenarios early can better prepare the credit union to pivot from current strategies should those trends continue by creating awareness and understanding.

6)  Effectively Summarize the Results
The value and power of this additional business intelligence can be lost if buried in an array of detailed reports.  However, by being clear on the critical measures to evaluate, we have found that the results can be typically summarized in a 1- or 2-page document.  Using a brief description of the budget and what-if options, the measures can be included in table form.  This allows decision-makers to quickly assess the different outcomes of each of the various options and how they compare.

For many credit unions, the investment in the annual budget is significant.  Perhaps because the effort can be monumental, many do not focus on generating the additional value that can come from these steps.  However, with the powerful tools available to credit unions today in budgeting and A/LM software, steps 2-6 should require a fraction of the typical budgeting time while delivering exponentially greater business intelligence to decision-makers.  Tools today can allow for fast-paced what-if scenarios, building on and creating more value from the baseline budget.  Using these tools, credit unions can do more to rehearse many possible tomorrows today.