1. Five Forecasting Fundamentals

2. Agenda Who are these jokers at the front of the room?
Communication with other Departments
Identify Forecasting Variables and Business Drivers
Data Analysis and Cleanup
Dealing with Special Forecasting Scenarios
Measuring Forecasting Accuracy

3. Presenter Highlights Debra Phillips - Verizon
- WFM IT System engineer for Verizon wire line business.
- Over 20 years of WFM experience
Shannon Knecht – Northwestern Mutual
WFM Assistant Director (for the last year)
10 years of Contact Center Management experience
New to the WFM role
Justin Zeigler - McKesson
WFM Manager
10+ years experience
Other departments can provide insight into business drivers as well as help determine cause of observed activity
It depends. Each business can be a little different but a good place to start would be the operations management group, marketing, and/or if in a BPO the group that manages the client relationship. (suggestions from group)
Anything that provides insight into the business that could impact forecasting (upcoming marketing events, known historical events, planned changes to how operations will handle calls, and many others)
Communication may be different by department or may be standardized. In some cases it could be as simple a report or more time consuming and intensive such as being added to a the team meeting or planning sessions for the other department.

4. Communication with other Departments
What good are other departments anyway?
Which departments do I work with?
What kind of information do we need?
What do we mean by communication?
Other departments can provide insight into business drivers as well as help determine cause of observed activity
It depends. Each business can be a little different but a good place to start would be the operations management group, marketing, and/or if in a BPO the group that manages the client relationship. (suggestions from group)
Anything that provides insight into the business that could impact forecasting (upcoming marketing events, known historical events, planned changes to how operations will handle calls, and many others)
Communication may be different by department or may be standardized. In some cases it could be as simple a report or more time consuming and intensive such as being added to a the team meeting or planning sessions for the other department.
Shannon’s comments
I can share the “Shared Services” model that my WFM team is in. For us, it’s very important to understand the different business areas we support
Importance of integrating the workforce staffing plan to the business area’s “business plan” so they are staffed appropriately to accomplish their goals for the year.

5. Communications

6. Forecasting Variables and Business Drivers
What are variables?
What are business drivers?
What do I do with these… things?
In our case variables are really just any component of the forecast that may change (handle time, call volume, service goal, caller tolerance (seen as abandon)
Business drivers are really just things that influence our variables to change (Time of Year, New Marketing Campaigns)
What does the group consider drivers
Variables and Drivers go hand in hand and to a large extent the terms could be used interchangeably. Out goal should be to use these items to help us arrive at a reasonable forecast.
After determining the most likely drivers you may have a better understanding of who you need to communicate with and what you need from them
Some drivers require external research and modeling (marketing campaign – you may need to determine historical impacts for marketing campaigns so you know how to incorporate a new one into your plan)
Some drivers may indicate a general direction your forecast may take (staged divestiture of products)

7. Forecasting Variables and Business Drivers
Call or Casework historical volumes
Average Handle Time (AHT)
Abandons (or Caller Tolerance)
Shrinkage (anything that pulls employees off the phones or out of production)
For the forecast, consider all planned shrinkage, as well as an average of the unplanned shrinkage that can typically be experienced
Vendor limitations
Weather Activity (can be both a variable or a business driver)
Business Drivers
Marketing Campaigns
Regulatory Changes
Sales competitions
Training initiatives that can drive up AHT or planned Shrinkage
New Self Service options (which can drive call or transactional volume down)
Union Agreements
Most of this information will come from your business partners in other departments. Very important to establish the relationship and create processes for “information sharing!”

8. Data Analysis and Cleanup
What do we analyze?
What kind of analysis can we do?
What do we mean by cleanup?
Anything and everything that could add value (call arrivals, handle time, yearly patterns, center reactions to mailers / marketing events, and so on)
What Kind? (Ask group what they do)
Some analysis is simple and is quite possibly handled by your WFM system (intra-day, day of week, week of month, seasonality)
Some may be more complex (regression “type” analysis, holiday review and planning)
Cleanup in many cases relates to “normalization” removal or correction of anomalous data
You do not want to include one off or erroneous data in your forecast or modeling
Often it can be as simple as finding something that does not look normal, determining from business contacts if it was a one time event, and setting the value to something more in line with the norm (be careful as you may want to preserve the true value in case of audits)
Create information from your analysis (Holiday factors, Mailer/Marketing event impacts possibly multi week by volume)

9. Determining Data Outliers
Averages
Mean or Arithmetic mean - sum total of data values /number of elements
( ) / 6 = (42) /6 = 7
Median - a number in the middle of the set of numbers
Mode - most frequently occurring value in a range of data
6, 10, 5 and 3 of 7 = 7

10. Analyzing Data
Histograms or Scatter Graphs – plotting data values visually
Outliers

11. Actual to Forecast Loop
Review - Daily call arrival and call length patterns. If there were any unusual events for the day, the event should be logged for future reference. This should include weather impacts, power outages, press releases, etc.
Review –
Daily variance of calls by calculating calls offered divided by the calls forecasted. If the variance exceeds 4%. Review the prior 3 weeks, same day. If this is a trend, analyze root cause and adjust forecasts accordingly.
On a weekly basis, compare the weekly calls offered to the calls forecasted. If the variance exceeds 4% then review the past 3 weeks. If this is a trend, analyze root cause and adjust forecasts accordingly.
On a semi-monthly basis, compare the calls offered to the calls projected (use a mid-point for the projection). If the projection exceeds 4% then review the past 3 semi-monthly comparisons. If this is a trend, analyze for root cause and adjust forecasts accordingly.
Review - If there are a large number of abandoned calls, then it may be wise to reduce the number of calls offered by some amount to accommodate repeat dialers. The number of calls handled should not be used as measurement for forecast or projection accuracy because that number could reflect what staffing would support if there are a large number of abandoned calls and not what the true demand was.
Review - The number of busy signals offered at the network level should be closely monitored. This could be demand that is not being addressed.

12. Discovering Root Cause
To find the root cause of a variance in forecast, consider the following possible areas:
Growth rate
Usage rate
Seasonal fluctuation
Unplanned events (press releases, weather, marketing initiatives that were not published, manufacturing defects, etc.)
Planned events that did not materialize (marketing initiatives that are delayed or do not generate the anticipated response, delayed product releases, etc.)
Population size accurate
Call Arrival Distribution (day of week factors, etc.)

13. Special Forecasting Scenarios
Hey, can I use that stuff we did in analysis and cleanup?
What types of scenarios?
How do we bring it together?
Great question! Yes that is why we did it.
Scenario Types (We could get suggestions from the group)
New Product Launch
Loss of a product
Marketing event
Seasonal (re-enrollment or other types)
Organizational changes
Changes to Training or Hiring Strategy
Changes to Hours of Operation
Changes to Service Level
In some cases you can enter the adjustments into a WFM tool others you may need to maintain a plan externally to account for special events or scenarios? (What does the group deal with)

14. Measuring Accuracy Simple Formula (or similar):
(Actual-Forecast)/Forecast
So aside from the formula what should we consider?
How do you determine your accuracy objectives and the different thresholds it is measured?
The specific calculation could change depending on what you are trying to state (do you want to know error rate and direction , absolute error rate, Accuracy rate)?
What are you doing with the number? (Ask group their thoughts)
Accuracy testing at every level can be helpful (monthly, daily, intra-day) but they each tell you something different.
Monthly can tell your understanding of seasonality and trend are correct and have accounted for business drivers
Daily can tell you if you understand the normal day of week flow of your center and if you have address special days
Intra-day can tell you if you understand the best time of day to have plan for a resource
Measure the accuracy of all the variables you forecasted, not just volume.
Not always easy to determine why the accuracy is “off”. In these cases, important to talk with business partners to determine what might be impacting the variables we’re using.