Transforming branch staff with predictive analytics
In recent years, banks have been focused on driving costs out of the branch network with self-service technology, branch closures and staff reductions. Yet, there is a genuine risk that driving any more cost out of the branches with across-the-board staff cuts will drive customers out of the bank altogether.
“Workforce is the lifeblood of any organization,” according to Deloitte’s The Three-minute Guide to Workforce Analytics, “and when it’s operating at a high level, the likelihood of a company reaching its business goals is raised considerably.” Rather than treating the branch staff as a necessary expense, banks need to view their workforce as under-utilized assets and maximize their value.
Bankers intuitively know this but don’t know what to do about it. Workforce decisions based on intuition or outdated software solutions cannot keep up with the change of pace in retail banking. Analytics and modern workforce optimization solutions are needed to continuously align the branch staff position mix and selling capacity with market opportunity, as well as finding and deploying the talent to drive revenue and improve customer experience and operational efficiency.
Even as customer transactions migrate from branches to digital channels, branches remain critical to growing revenue. According to recent studies, over 75% of new accounts are still opened in branches. As branch staff interactions evolve from transaction handling to developing relationships and solving complex problems, so must the methods of recruiting, training and retaining talent with proper skills.
Why has the adoption of analytics for talent management been slow for banks? Workforce decisions always involve the Human Resources (HR) function and, unfortunately, HR ranks last among the business functions that use analytics. The result is that retail banking has high turnover and performance variability, a vicious cycle that keeps banks from achieving revenue targets.
Banks that view their branch workforce as an expense use one-size-fits-all staff reduction models or outdated workforce optimization software. Such models are unable to address the dynamics of changing consumer demand, branch attributes, market opportunity and platform workforce composition. These models produce unreliable and inconsistent recommendations that lead to over- or under-staffing in branches, causing poor operational efficiency. These models’ inability to align selling capacity with market opportunity limits revenue growth.
Given that the branch workforce is a critical success factor for customer experience and revenue growth, here are four recommendations for achieving those goals with analytics-based insights:
Acquire and retain top talent. In our recent survey of 37 banks, senior bank executives indicated that the top two challenges with their workforce were turnover and the quality of hires. HR needs to use predictive analytics to acquire and retain talented employees in the same way that marketing uses it for customer acquisition and customer retention.
Marketing uses analytics to score, rank, qualify, and nurture leads with the intent to convert to sales. HR personnel in banks must embrace their own data and analytics to do the same for acquiring top talent. Predictive analytics-driven assessments can help score and rank candidates who are most qualified for the position, represent a good fit for the bank’s culture and are most likely to stay on the job. Furthermore, predictive analytics can be used to assess employee attrition risk similar to the way marketing uses it to assess customer attrition risk.
Banks also need to focus on talent management initiatives such as learning and development, rewards and incentives. Because, more than half of the consumers in the U.S. use both digital and physical channels, educating branch staff about customer journeys and interactions in digital channels is important both for employee engagement and overall sales effectiveness. Other important initiatives are providing consultative sales training and aligning rewards and incentives with desired customer outcomes.
Align selling capacity with market opportunity. Most banks are either over-hiring, under-hiring, or not hiring the right skillsets. Distribution and workforce analytics models must be applied together to align the right selling capacity and position mix with the market opportunity. Such models need to take into account customer segmentation, arrival patterns, sales goals and the unique attributes of each branch in the network.
New workforce management software has the intelligence to avoid over-optimization by being focused exclusively on efficiency while ignoring customer experience and revenue targets. Customers will quickly see if their bank is focused exclusively on driving costs out of the branch. The perception created by the branch experience will impact where customers go when it’s time to get an auto loan, a new mortgage or a small business account. It’s already happening.
Optimize staff scheduling. Scheduling is a complex problem. In addition to their primary banking activities, branch managers need to plan for customer facing and non-customer facing activities and manage shift schedules, taking into account paid-time-off and sick time for full-time and part-time staff. Given recent branch transformation initiatives, scheduling has become even more complicated. Some banks are employing branch managers who manage more than one branch. Other banks are pooling staff members across multiple branches in close proximity.
Banks can improve their sales effectiveness by making it easy for branch managers to plan and schedule their staff. Optimized schedules can help banks put the right bankers in front of the customers at the right time and place.
Deploy universal bankers, but only when and where appropriate. The universal banker position is defined for multi-purpose bankers capable of performing personal banker, teller and customer service roles. Some banks re-train tellers to become universal bankers. Because universal bankers are not expected to perform as well as dedicated bankers, their sales performance can be significantly less. Other banks hire from outside the banking industry and struggle with identifying the right talent because the universal banker must be a whole new type of person with different skills and motivations than traditional bankers.
While universal banker deployment may be appropriate in certain branch formats or locations, it is not effective and efficient in all situations. Rather than deploying universal bankers with a one-size-fits all approach, bank managers should assess the optimal position mix for each branch utilizing insights from data and advanced analytics. Branch managers should also utilize proper forecasting and scheduling processes and tools to ensure that universal bankers are distributing their time appropriately between sales, service, transaction and channel migration activities.
The bottom line: the relevance of the branch workforce is significant for improving new customer acquisition and cross-sell. Banks can and should leverage workforce analytics to improve the quality of hires, enhance employee retention, optimize position mix, align selling capacity to market opportunity and optimize staff scheduling.