Today’s banks are challenged with meeting ever-increasing customer service and quality expectations, while managing internal pressure to lower costs and do more with less.

by Bryan Slepian, Sr. Manager, Labor Management Solutions

Today’s banks are challenged with meeting ever-increasing customer service and quality expectations, while managing internal pressure to lower costs and do more with less.  A common myth is that there is a trade-off between service, quality, and cost:
“If I focus on service, either my resource costs will increase or my quality will suffer.”
“If I cut costs by reducing headcount, I won’t be able to deliver on service or quality.”

The reality is that banks can achieve simultaneous improvements in service, cost, and quality by aligning their workforce capacity with customer demand.  In other words, ensuring the right number of people are scheduled in the right place at the right time.

What is capacity?
Capacity is the ability to process volume, or in this case customer demand.  It is not just about the number of resources, but also the time they are available and the productivity they can consistently achieve.  For example, If there are two resources available for eight hours each and can process 10 transactions per hour, then the capacity is 160 (2 * 8 * 10) – which is to say, the ability to process 160 transactions.

Businesses are always in one of three states of capacity, relative to customer demand – not enough, too much, or just the right amount.  When there is not enough, customers are waiting too long for service and employees are rushing (and often cutting corners) to serve them.  This results in poor quality and high costs – due to rework, the extra effort required to satisfy unhappy customers or to re-acquire lost ones. When there is too much capacity, employees are sitting idle or, most likely pacing themselves to appear busy, which also results in high costs and poor quality.  Intuitions have previously told us that when they have extra time to complete a transaction, they have extra time to ensure quality.  But in reality, too much time allows employees to become more easily distracted and causes them to lose focus on the task at hand, thus, resulting in poor quality.  Therefore, the main objective should be to plan for just the right amount of capacity to meet customer demand – all the time.  Remember, in a service industry, we don’t control our volume, we only control our capacity.

Productivity: The missing link of capacity.
When we are struggling to meet service levels, too often the answer is to incur overtime or ‘throw’ more people at the issue.  This solution, however, only considers part of the capacity equation and ignores the most important factor – productivity, which is defined as the number of transactions processed per hour per resource.  Productivity is a difficult measure to quantify for two main reasons: first, a majority of the tasks performed at a bank (both front and back office) are manual, and only a portion of the transaction is captured systematically, if captured at all.  Second, manual transactions are inherently highly variable due to the number of discrete processing steps and the overall duration of those steps. This proves to be a prohibitive factor when trying to analyze productivity and setting realistic targets.
Managers often rely on financial as well as time and attendance reports to calculate productivity.  This measure typically represents an aggregate number of total units per paid hour.  While this approach is relatively easy to generate, it fails to provide any visibility into the states of capacity or a true measure of achievable and sustainable productivity. If, during the reporting period, employees were sitting idle (too much capacity), then paid productivity would understate what actually can be achieved and sustained.  Conversely, if employees are swamped with work and miss service levels (not enough capacity), then paid productivity would overstate what can be sustained.  Although this latter measure would be a decent short-term indicator, it often doesn’t represent what can be consistently sustained over time.  The risk of using this number to set productivity targets would likely result in poor quality, higher absenteeism and higher employee turnover.

Establishing realistic and sustainable productivity targets requires a methodical approach to data collection and analysis.  It entails process observation and a combination of work sampling, stop-watch studies, and system reports – provided that they have a start time and end time for each transaction.  A few helpful hints:

  • Don’t treat all transactions the same. Segregate the transaction volume by function and complexity.
  • Gather enough samples to ensure statistical confidence and to incorporate variability within the process and between employees.
  • Avoid using straight averages. Averages do not provide incentives for poor performers to improve or top performers to maintain the productivity levels that they can achieve.

Customer Demand Pattern:  When does the volume arrive?
Once productivity targets have been established by function and work complexity, enabling us to calculate capacity, the next critical piece of information is the arrival of customer demand (volume).  Most operations managers understand their transaction volume by month or by week, but this only helps determine the gross resource requirements and doesn’t provide any insight as to when the resources need to be scheduled.  In banking there are predictable arrival patterns by days of the month, days of the week, and hours of the day.  For example, daily peaks in branch banking occur on Friday, the first Monday of the month, and Tuesday after a Monday holiday.  Intra-day peaks occur first thing in the morning, at lunch, and at the end of the day.  Now, we can take the monthly or weekly transaction volume forecast and distribute the work by day of the week and hour of the day using the customer demand pattern.  Visibility into the arrival time is essential for knowing how to adjust the staff schedule in order to consistently match capacity with demand.

Conclusion: Align capacity with customer demand.
In a service environment such as banking, we don’t control the arrival time or amount of volume we receive.  We do however, control our capacity (the number of resources and when they are scheduled) and the expected productivity (the number of transactions processed per hour).  Considerable up-front data collection and analysis is needed to establish productivity targets and determine demand patterns – but once this is validated, simple math (volume ÷ productivity) tells us what resources are required each day of the week and hour of the day.  Depending on the actual service level agreements, there are different strategies for generating staff schedules; however, the ultimate goal is to consistently align capacity with customer demand.  This creates a consistent pace and flow of operations – allowing workers to ‘lock-in’ to a nice rhythm and focus on the task at hand.  This improves quality, meets service levels, and controls costs – all at the same time.