Many articles and case studies are published about the benefits of a sound Workforce Management solution in all contact center types, including outbound contact centers and with the improvements in technology and the shift from ‘calls’ to ‘interactions’, this has made it easier for systems to adapt and easily classify the contact/lead on the dialer as an interaction, which allows the WFM software to forecast for it.

New technology is great and I welcome it, however, I also believe that without a deep understanding of Workforce Management, many contact centers aren’t able to get the best out of the software they choose. I did a case study back in 2016 for an outbound sales contact center without any WFM software, about how WFM can work and improve their outputs and the method I used, is what I want to share.

To start off, lets understand why a sales contact center environment is so complex: It is due to the close relationship that Sales and Marketing share, therefore many businesses would want to track the effectiveness of each marketing campaign based on the sales that were made, to understand the cost and returns of that type of campaign (TV, Radio, Internet, etc.) and viability of running that type of campaign. This fact makes WFM forecasting and planning become very complicated and in my experience, there is often a misguided approach of trying to implement WFM based on an ‘inbound template’, by simply stating outbound calls as ‘incoming workload’ and trying to forecast in this manner.

The reality is, the outbound call volumes are only a reflection of agent behavior – it is a view of what they actually did and by using this as the baseline for the forecast together with a ‘total average handle time’, staffing figures are skewed, workload volumes don’t match and schedules are not aligned – staff then reject the WFM plan and the implementation fails.

To overcome these challenges, the WFM team must understand that each campaign, each channel, each product type must be treated as its own with its own unique workload and its own handle times and find the best way possible to improve the productivity of the contact center which does not necessarily mean ‘provide schedules’.

First, understand the business – create a map of each department, the campaigns they work on, their product and their customer type (target market).

Second, understand the call flow – conduct time studies to segment each step of the call, how long it takes for the agent to navigate the system based on the product they are selling and any wrap up or admin work required afterward.

Third, understand the campaign/marketing plan – get sight of the marketing strategies, campaign rules (how many times are contacts/leads recycled etc.), campaign lifecycle, business sales targets and the average revenue per closed sale.

Fourth, analyze the current workforce stats – the total talk time, calls per agent, conversions and closings, time usage and management, productivity, occupancy and utilization stats.

By understanding the various product and customer types, we can apply a specific handle time to specific teams in the outbound contact center, an example: selling an ‘add-on’ benefit to existing customers. These calls will be shorter than those of the actual product being sold so taking an AHT for the entire department may not work, instead, it will have to be broken down by team or ‘product type’. Another example is the customer type, if your target market are individuals above the age of 60, chances are, they will spend more time on the phone as they feel more comfortable ‘speaking to a human’ compared to the younger generation that prefers online and electronic interaction.

The time studies point out some very important factors, the most important one being that you absolutely cannot use a total AHT when calculating staffing. Whether its cold data or hot data, an outbound agent’s AHT will not be accurate as some customers would want a call back at a different time, are driving at that moment or get halfway through the call and realize they don’t have all the information available to complete the sale. To determine the correct staffing, each segment of the call should be categorized and matched back to the performance of the type of campaign being run – therefore it is vital to understand the marketing plan.

Knowing exactly how the department is setup will reveal overflow or multi-skilling opportunities between the teams. It will reveal if a ring-fenced team is actually causing your business harm by being either over or under staffed and depending on the ‘best time to sell’ data, you can use your resources on multiple campaigns throughout the day.

Putting all these together, highlighted two very important statistics for me: 1) The percentage gap between how many sales can be produced and how many are actually produced, 2) Why there is a gap and what can I focus on to close that gap.

In my case study, I found the overall opportunity to increase performance was 12% which then increased the potential number of sales by 9% – an additional 38 sales per day! The increase in performance was an amount of ‘workable time’ that was being lost due to a number of things, like processes, structure, design of the department, lack of skilling options etc. which all came to light while doing the analysis after collecting all the data. Each identified problem had an impact on ‘workable time’ and by resolving the ones we could, it increased the ‘workable time’ which increased Productivity as well as help put an accurate staffing cost to each campaign – business now had sight of the cost of generating the contact/lead and the amount of time spent working that lead, related back to a staffing cost.

For me, WFM in an outbound contact center is focused around WFM Analytics – knowing the true output capacity of the contact center with the performance of the campaigns being run and being able to match the two in a way that focuses on the business goals.

This method has proven to work in various other outbound departments that I have worked on and I am sure there are other methods and if a something else worked for you, or you have any comments, please share them with me.