Now is a Better Time Than Ever to Update from Manual to Automated Forecasting Models

Even in the best of times, determining the right staffing levels needed to keep a contact center operating efficiently while adequately meeting customer demand is a delicate balancing act. Staffing too many agents needlessly drives up costs: staffing too few at peak times causes service levels to suffer. The first step in making informed forecasting calculations is to accurately estimate the volume of calls coming into a business’s contact center. Of course, this is easier said than done, particularly in an environment where many organizations are experiencing dramatic call spikes driven by concerned and often panicked customers.

While there are many ways a company can try to figure out the number of calls coming into the contact center, the method will ultimately depend on which sources of information to which it has access. Obviously, the most effective way would be to obtain an accurate calls-per-day figure from an Automated Call Distribution (ACD) system. But even though these systems have proliferated over the years, far from every company that could benefit from such a solution has one in place. For many businesses that do not have an ACD or effective call logging solution, the option becomes simply asking staff to manually log the number of calls coming in.

Trying to match agent availability and skills with staffing needs while keeping track of work hour limits and labor costs is a daunting task, especially when done manually or with Excel spreadsheets. Some companies still employ downloadable templates to do their scheduling in Excel, often employing Erlang C formulas.

While using Excel can be a viable option for some smaller companies, it can turn into a tedious, time-consuming and inefficient process, particularly when there is a need to scale up rapidly. Making it all work is dependent on the contributions of a few lead users who have the requisite knowledge and system access. These lead users must frequently create new tables or worksheets …sometimes entire new files…to set up new staff groups, forecast time periods, call types, forecast variables, or forecast methodologies, These files then must be stored and linked together. If they include elements an entire team to needs to access, the files must be stored on network shared drives. In addition, spreadsheets tend to get progressively more complex, hard to maintain and error-prone

In an evolving period that calls for rapid response and flexibility, businesses are becoming increasingly frustrated with the limitations of Excel and are now seeking a simplified and more accurate planning process. Contact center managers and executives are seeking to find ways to connecting themselves with the tools that can take their WFM practice to the next level. Now they can take advantage of a focused educational presentation to help them expedite the timetable to understanding and implementing a more time-effective solution.

Genesys will present a complimentary tutorial “Best Forecasting Methods In the 21^st Century.” on CrmXchange. The webcast, scheduled for Thursday, May 28^th at 1:00pm ET. will be led by Shawn McCormick, Senior Solution Architect, Genesys. Shawn brings to the table more than two decades of experience supporting the Workforce Management/Workforce Engagement needs of companies of all sizes from just about every industry sector. He started his career as a manager doing scheduling on paper from a forecast sent down from corporate and thus respects the tradition while embracing the enhanced possibilities offered by WFM technology.

Among the topics he will delve into are a review of what is actually possible and how automated forecasting plays a role in preserving business continuity. This includes:

• Considerations for the manual planning processes and the perspective of faithful Excel users
• If automation is right for a specific company – what needs to be looked at to make the correct assessment
• How the use of AI enables businesses to perform the planning process more accurately and rapidly than ever.

Register now for this topical webcast: if you are unable to attend the live presentation, a link will be posted 24 hours later to allow you to access it.

 

 

 

 

4 Contact Center Tips for Forecasting and Analyzing Data

Picture this: there’s a sudden spike in call volume, but you don’t have enough agents to handle it. Wait times increase and customers become dissatisfied. You get on top of the problem as quickly as possible and scale your workforce up to handle the demand. Soon, call volume evens out again, and now you’re over-staffed and draining your budget.

Improving forecast accuracy can limit these scenarios. Data, history and experience, combined with your own judgement and common sense, make forecasting much more accurate and predictable. A quality system will combine historic data with real-time data for accurate forecasting.

Here’s how to improve your forecasting:

1. Choose quality forecasting software.

Your forecasting software should gather historical data from the past two years to show you daily, monthly and seasonal patterns and trends. It should then monitor performance, document results, and continue to measure and evaluate data on a recurring schedule. Most importantly, your software should repeat this process ­– the repetition is what makes the forecasting so accurate and dependable.

2. Look at both data overviews and specific segments.

Look at historical data, which will give you an overview of NCO and handle time. Also view data in hour, day and month formats. Continue to break data down to view it differently – turn monthly forecasts into daily forecasts, daily into hourly, and hourly into half hour views.

3. Compare one month to the same month last year.

Point estimates are too simplistic an approach when it comes to contact center forecasting. A point in the future won’t necessarily match the same point in the past, even if it’s the same hour, day and month of the year. You have to look closely to determine if any data is out of the ordinary, and a good start is to compare this year’s month to last year’s month (i.e. January 2018 to January 2017).

4. Don’t ignore aberrations.

Investigate data that’s exceptionally high or low to figure out if it was caused by a one-off event or if you should be prepared for a regular occurrence. Situations that affect call volume include:

• Billing cycles
• Business mergers
• Change in hours of operation
• Competitor activity
• Holidays
• Marketing campaigns
• New technology implementation
• Planned maintenance sessions
• Weather and natural disasters

Balance customer demand with staffing numbers to keep costs low while managing wait times and ensuring customers satisfaction.