Using data and analytics to scale banking revenue

Current market dynamics undoubtedly have created a new set of obstacles for financial institutions in meeting or surpassing commercial revenue targets. Banks are challenged by selling into an economy plagued with deteriorated industries and sub-segments that are experiencing financial difficulty. In addition, with banks repurposing relationship managers (RMs) and diverting their efforts to primarily portfolio management during the COVID-19 pandemic, frontline sales resources have become not only constrained but truly consumed in servicing and monitoring activities. These two issues have challenged banks to capitalize on any sales momentum and create real sales inertia.  

As we look ahead to a post-pandemic landscape, many banks are finding even greater challenges. In addition to deteriorated industry segments and constrained sales resources, other obstacles are preventing growth: the impersonal and remote sales process currently being delivered through video conferencing, compounded by a noticeable lack of standardized sales methodologies to guide teams. Most critically, the absence of data and analytics (DnA) to support the banks’ sales program has hampered sales teams in meeting or exceeding growth goals. 

Even with an effective sales methodology and highly trained team in place, banks will struggle to scale sales methodology and grow revenue without data and analytics. Put another way, while banks might experience short-term growth, they will struggle to find long-term success given the absence of a focused, cost-effective, and scalable process aimed at the ideal, targeted customer.

Where historical, data-less methods miss the mark 

Historical methods for selling are largely ineffective in today’s environment. Commercial banking sales have historically been rooted in selling through relationships and networking with Centers of influence (e.g., accountants or attorneys, etc.). In today’s climate, this is challenging because there is often not a methodical plan to expand, repopulate, curate, and filter the network on an ongoing basis to insure ample and effective referrals.  In fact, the somewhat “randomness” in which bankers attack this aspect of business development is a major issue hindering growth and opportunity identification. The financial results prove this out with historically low win rates, sporadic cross-sale success, and in many cases heightened levels of sales personnel attrition. 

Without a standardized methodology, banks are generally unable to unlock the magnitude of their organization. Without a methodology, sales efforts are not repeatable and must be reinvented with each new sale, proving both costly and ineffective in business development. Without scalability, as banks grow inorganically, these challenges become compounded and further complicate growth. 

Banks have historically failed to leverage their disparate data sources—even when owned by the bank—to drive the methodology and optimize execution of sales plans. With data typically stored in disparate data houses in multiple non-integrated systems, it has become nearly impossible for bankers to identify and prioritize relationships in a meaningful way. 

Because of the lack of coordination around data, banks typically fail to effectively, easily, and accurately align product revenue, whether interest or fee income, to an individual borrower or relationship. Without a clear understanding of the 360-degree profitability view, it becomes challenging to plan and segment holistic, high opportunity sales calls through proper segmentation and targeted sales activities.

Why is this important? Now more than ever, a new scalable method is required to effectively identify, pursue, and sell to targeted existing and new prospective clients that offer high levels of probability for new opportunities within optimal, performing industry segments.

Banks are slowly embracing the concept that not all customers are created equal and that they have varying degrees of future value (e.g., new sales opportunities), predictable with data already owned by the bank.

Investing in scalable sales strategies, driven and supported by data and analytics, is one path to accurate and higher probability sales opportunities followed by an accelerated sales cycle, and ultimately a higher win rate with more business on the books.

Questions when considering your bank’s scalability

West Monroe’s perspective is that scalability is a sought-after state of operations and provides the foundation for rapid, cost-effective growth. At the core of scalability is repeatability and the ease with which results may be reproduced as bank operations change and adapt to varying conditions. Scalability is often made possible through technology enablement while leveraging automation.

While banks have explored scalability through technology and tools such as loan origination systems, base level CRM systems, and integrated third-party tools to automate the credit underwriting and scoring processes, this alone does not create scalability. Scalability is also built upon standardization, streamlined policies and procedures, and is evident through repeatability made possible by simplicity.

Organizations that are scalable benefit from economies of scale and process greater volumes with fewer resources. This increases net profits as the direct result of top line revenue growth while reducing operating expenses.

How scalable is your sales organization? Ask these questions:

• If sales goals for commercial banking relationship managers increased meaningfully over last year (call it 30%), would your bankers know where and how to begin looking for that extra growth in the market?

• Are your relationship managers able to consistently and repeatably enter new markets, whether geo-based or industry-based, and are they able to create new opportunities at a pace above market averages?
• Does your sales methodology automate opportunity identification for a customer or prospect based on a commonly recurring set of opportunities repeatable within a certain market or industry?

Embed data and analytics within sales effectiveness

A bank’s DnA must be embedded within sales effectives to drive support and insight through the intersection of sales methodology and technology, all of which leads to greater scalability and accelerated growth

In our view, banks should operate through a delivery model that leverages data and analytics, provides scalability, and identifies the following: advanced customer segmentation, early-stage opportunity identification, early detection of significant cross sell opportunities, and pre-defined sales targets supported by actionable and tactical workplans.

With the right tool, banks also can unify the RM sales management process and drive user adoption and experience to accelerate success and drive both sales accountability and transparency through customized automated dashboards and reporting.

This also allows for the automation and generation of critical, tactical sales tasks built around an effective sales cadence, and automation and integration of data throughout the entire sales journey. With this approach, banks can begin managing RM sales activity in ways that create scalable, sustainable sales success and ultimately achieve higher than market growth rates.

Transformation considerations

Utopia is often achieved through transformation as opposed to the flip of a switch when considering sales effectiveness. This transformation is possible if banks first evaluate the sales methodology being deployed across the enterprise.

While scalability, sales methodology, and DnA considerations reside at the onset of the transformation, multiple elements must also be addressed along the implementation. For example, once DnA becomes integrated, key performance indicators should be revised to measure desired, targeted leading sales behaviors of RMs. It’s no longer about how many sales calls were made per defined time period. Instead, the KPIs are likely to become based on:

• How many calls were made on highest opportunity clients and prospects?
• How many high opportunity sales calls actually advanced an opportunity sales stage?
• Was the opportunity converted to closed faster than regional or national average closing rates?

Leading KPIs must then be converted into lagging outcomes, aggregated, and rolled into new financial performance budgets. There’s likely also an opportunity to revisit short-term incentive plans (STIPs), with the intention of realigning to new, accelerated levels of sales performance.

Sales transformation affects more than just front office sales activity. Banks must also evaluate the organization’s ability to support the rapid, resultant sales growth. In fact, it becomes equally critical to develop an assessment plan for the middle and back-office functions to ensure ample capacity and throughput are available to support the growth. Without proper sales support, the organization will struggle to deliver and realize the full potential of a sales transformation.

Sales organizations whose methodology is infused with data and analytics stand to drive more focused teams and scale their growth. The banks that we have helped most successfully transform follow these steps to get started:

1. Evaluate the current effectiveness and usage of the bank’s sales methodology based on upon enterprise-wide and individual banker sales results
2. Determine the general scalability for the bank’s sales program to assess the organization’s ability to create rapid growth
3. Consider improving the effectiveness of the sales methodology by integrating DnA across the entire sales process
4. Assess if known DnA gaps are due to:
   1. Lack of data or data quality
   2. Lack of data integration and digital tool
   3. Lack of a standardized methodology
5. Prioritize the areas of greatest benefit from DnA integration and scalability improvement
6. Identify key points in the sales process that generate significant and short-term benefit derived from scalability and begin the journey with DnA as the new foundation to your sales success