A flexible contact center model, like ShyftOff, allows companies to perfectly match agent availability to caller demand curves. Caller demand can fluctuate dramatically at each interval making it difficult and expensive to provide mid-tier service levels with a traditional call center model.

In this case study, we will examine how the ShyftOff model can supplement existing contact centers to improve service level performance and reduce overall cost compared to a traditional model. We will look at call performance, expenses, and productivity measures to determine the value and tradeoffs of each.

We will be using some terms that may be unclear, so before we go further, here are a few definitions to get us started:

Traditional Contact Center Model — is defined as a contact center that is staffed completely with full-time, W-2 employees. This is the standard model for operating contact centers today for both internal centers and BPO centers.

ShyftOff Model — is operated entirely with 1099 agents who have full autonomy over their time & productivity, similar to Uber. ShyftOff’s technology and processes ensure, despite lacking 8 hour schedules, there is optimal coverage at every interval.

80/30 Service Levels — our targeted service level for both models will be 80% of calls answered in 30 seconds or less, which we’ll refer to as an “80/30” service level.

In a previous article, we provide more background on the ShyftOff model by drawing parallels to Uber and the operational benefits of integrating a flexible staffing model.

The purpose of this exercise is to show, side-by-side, the difference in service level performance, productivity, and expenses between the two models. To make this more powerful, we will step through the process of forecasting and planning both models to show the assumptions we used.

Forecasting Contact Volume — we will briefly discuss the process and assumptions used to forecast contact volume, or demand, in this study. We want to highlight the types of assumptions businesses make to produce these forecasts and examine the likelihood for forecasting error as variables compound.

Staffing & Scheduling — we will walk through the assumptions we used to develop a simple schedule to cover forecasted call volume with an 80/30 service level. We did not use planning software for this exercise, just some excel skills. There may be opportunities to optimize further, but we believe it is effective for this analysis.

Service Levels & Financial Performance — most importantly, we will show the side-by-side view of our planning assumptions, productivity, and financial results.

Summary Findings:

Here are some of the highlights of our analysis in case you don’t have time to read through the more detailed assumptions later in the report. If you have any questions or comments, we would love to hear them at trevorclark@shyftoff.com. We’re also happy to provide free consultation to achieve similar results in your contact center.

1. Overstaffing is required to achieve 80/30 service level in traditional models - Case study reveals 31% unproductive time
2. ShyftOff’s model increases service level performance without adding unproductive costs
3. This case study shows 15% lower cost in the US by utilizing ShyftOff

Case Study Details

Forecasting Contact Center Volume

In our example, we have produced an offered call volume forecast for each 30 minute interval in a 4 week period. We modeled caller demand for a subscription-based business model, which required us to examine historical data and make predictions for product sales, subscriber churn, call in rates, and seasonality. We predicted calls by interval based on weekly patterns, day-of-week patterns, and intraday arrival patterns.

In a typical forecasting exercise, you may also account for any planned initiatives that will affect sales or subscriber growth, call in rates, and even weather factors.

Forecasts are based on many assumptions. As you combine assumptions and look further into the future, the error rate of your interval-level demand forecast is likely to increase. While we are not comparing our forecast to actuals in this study, this is another reason that flexibility to respond to changes in demand or supply is critical to your contact center’s success.

As you can see, contact demand has significant volatility across the month:

• Fluctuations week-over-week — weeks 2 and 3 are greater than weeks 1 and 4
• Daily fluctuations — peak days (Mondays) are nearly 2x greater than the peaks of other days (this contact center’s hours of operation is 8AM to 8PM everyday)

Before scheduling your contact center, we should run through a simple checklist:

• Do you know your forecasted demand and arrival patterns?
• Do you know what your targeted service level is?
• Do you know your hours of operation?

• Our forecasted demand is based on the forecasting exercise above: 297k offered calls in the month, 12.42 minutes handle time (including after call work), and for arrival patterns, see charts in the forecasting section
• We are targeting an 80/30 service level
• Hours of operation are 8AM — 8PM each day, including weekends

We estimate 407 FTE are required to support this contact center at our targeted service level, but there are more factors to consider before locking this number into your plan.

Traditional contact centers typically hire and schedule agents in a 40 hour work week, which is necessary to provide sufficient hours, stability and benefits to contact center teams. The challenge is that a typical 9–5:30 M-F schedule does not align to the arrival pattern of the calls.

Centers begin to break down the fabric of their centers and their internal cultures when they try to stretch these 40 hour schedules to match the demand.

• Policies that prevent days off on peak days
• Required overtime
• Nights & Weekend Scheduling
• High occupancy, leading to burnout

If we try to shape schedules more closely to the demand curve, we sacrifice stability and consistency for the agent, which should be avoided.

Staffing & Scheduling to 80/30 Service Level in a Traditional Model

The finding in this section is that traditional contact center models require overstaffing during non peak intervals to achieve targeted service level performance. And this overstaffing is directly proportional to the level of volatility in contact demand.

We are now going to be covering more tactical assumptions pertaining to this case study.

A detailed look at our schedule assumptions:

The required FTE for this forecasted demand is ~407, however our schedules require ~580 headcount to achieve an 80/30 service level. Here are the assumptions:

• All schedules are 40 hours per week, 8 hours per day
• All schedules include two 15-minute breaks and a 30-minute lunch
• There are 2 groupings of schedules: “Mon — Fri” and “Sat — Wed”
• Staggered shift starts every 30 mins beginning at 8am until 11am each day

We believe these assumptions represent a basic scheduling approach that encapsulates the required headcount to staff this contact center forecast. More advanced software and use of part time employees may produce a more optimal staffing plan than our model assumptions.

80/30 Service Level Contains 31% Unproductive Time & Cost

When we look at the interval level forecast for required FTE vs. Scheduled FTE, we can see a significant mismatch between the two lines. (see below)

Where “FCST_Staff” exceeds “Req_FTE” the contact center has a surplus of staff and significant unproductive time. When we quantify the amount of time that the “FCST_Staff” exceeds “Req_FTE” it is 31% of the total time and cost of running the center.

Our takeaway here is that there is extreme cost associated with delivering mid-tier service levels in a traditional contact center model. It is especially costly when the volume is volatile.

In order to deliver targeted service levels, contact centers must staff close to their peaks, which requires holding more headcount than is required for the inbound demand for the majority of the week.

Staggered schedule starts and varying the days of week for your team can help reduce the number of staff scheduled on a given day, but costly imbalance remains.

Many teams use surplus time to run training, team meetings, and other supportive activities to make use of the time, however 31% is typically a lot more surplus time than you need to run your center effectively.

Worth noting — this scheduling and volatility dilemma occurs in centers both onshore and offshore. While it is cheaper to send calls offshore in the traditional model, would it be worthwhile to bring that work back to the US with ShyftOff for a comparable price? We will explore the concept of using ShyftOff to support reshoring efforts in subsequent articles.

Staffing & Scheduling to 80/30 Service Level with ShyftOff

ShyftOff’s model operates without schedules and demonstrates exceptional flexibility to meet changing contact demand. Our technology and processes allow us to perfectly fit the supply to demand in a way that is advantageous to the agents and our clients.

Our agents are a diverse group of talented people based in the US. Some are full time contact center professionals (trainers, coaches, etc.) and work with ShyftOff to earn extra income. Some are college students, full time parents, entrepreneurs, etc.

Our agents have full autonomy to work when they like, and despite a different approach to sourcing a contact center, there is high confidence before go-live that ShyftOff will have the right agents in place to deliver your targeted service levels (80/30 in this example) while greatly reducing the unproductive time.

Internal schedules with the ShyftOff Model

In this case study, we are going to assume our client maintains a base of 50 agents internally. These staff can also be through an outsource partner — we are assuming the cost structure is the same.

We believe it is advantageous to prioritize our client’s internal schedules and overflow the volatility to the ShyftOff model. This adds another perk for full time agents to gain autonomy over their schedules and a material improvement in agent attrition.

• Reducing all schedules to M-F
• Limited staggered schedules in this example

Internal Planned FTE vs. Required FTE

At every interval, the client is staffed below the required FTE number, meaning unproductive time is completely under control.

Where “Req_FTE” exceeds “Planned_FTE”, volume will overflow to ShyftOff.

Overflow contact volume to ShyftOff

Below is a visualization of the required FTE volume that would be sent to ShyftOff. It is very volatile, and requires a different approach to cover it effectively.

Similar to our traditional model, we need to review our checklist:

• Do you know your forecasted demand and arrival patterns?
• Do you know what your targeted service level is?
• Do you know your hours of operation?

The answers will be exactly the same in the previous example because these core requirements remain an important part of ShyftOff’s planning and implementation.

Instead of defining schedules to match this demand, ShyftOff will look at the arrival patterns and determine a range of volume to be prepared for each day.

ShyftOff is able to deliver service levels with a flexible workforce by providing favorable financial and behavioral economics that are aligned to the interest of our agents.

The result is highly skilled and highly responsive flexible agents available at each interval to match demand.

The image below shows the comparison in coverage between the two models. ShyftOff has almost completely eliminated the surplus and unproductive time in the traditional model, which is where the majority of savings is realized.

‍Call Performance & Financial Results

When we compare the financials of operating a traditional contact center compared to ShyftOff’s flexible contact center the case study reveals 15% savings in total cost to deliver the same or better service level performance as a traditional model.

We are using the exact same assumptions of forecasted contacts, AHT, and arrival patterns while delivering identical service levels.

We are assuming the cost of the Traditional Center is $.63 per productive or available minute, which is on the low end of the range for US onshore contact center pricing. For the sake of this study, we will assume the cost of operating internally or with an outsourcing partner is identical.

Final thoughts

This case study compares these models in the planning stage of operating a contact center. Demand and scheduling forecasts typically contain many variables and assumptions.

This means the actual call volume may differ considerably at each interval, and actual staff may differ too. This is another reason that flexibility in contact center operations is critical, yet we are not measuring the difference between planned and actual results at this time.

Ultimately, we advocate for a blended model to bolster service level performance, reduce unproductive cost, and improve work-life balance and morale for traditional agents. While we have not yet examined additional benefits from lower attrition for our clients, we believe this is a natural byproduct of implementing ShyftOff.

We look forward to hearing from you! Please visit www.shyftoff.com and email trevorclark@shyftoff.com for more information.