how great contact center plans lead to a better...

How Great Contact Center Plans Lead to a Better

Operation

Ric Kosiba

Your Seminar Leader

Ric Kosiba is vice president and founder of the Decisions Group at Genesys. He founded the company, Bay Bridge, in 2000 that was acquired in August of 2012.

Ric has been involved in the call center industry 20+ years and enjoys working with contact center analysts and helping companies maximize profitability through math modeling. He holds a B.S.C.E., M.S.C.E., and Ph.D. in Operations Research and Engineering from Purdue University (go Boilers!).

Ric is responsible for the development and enhancement of our contact center capacity planning and analysis product line. He thoroughly enjoys working with our brilliant development and operations research team, which helped Decisions become the leading U.S. supplier of long-term forecasting and planning solutions.

Ric resides in Maryland with his wife and four children. Ric loves being a dad and enjoys coaching his kid’s football, basketball and lacrosse.

What we are discussing today

◦ Quick recap of the previous webinars

◦ The overall planning process, and how it really starts with variance analyses

◦ When should we reforecast?

◦ Some very powerful what-if analyses

◦ The very real and very big benefits of improving your planning process

Genesys confidential and proprietary information.

Unauthorized disclosure is prohibited. 3

Webinar 1: Why do we forecast?

◦ Forecasting is just one part of

the planning process

◦ We forecast to make resource

decisions!



ForecastStaff & Capacity

Plan OptimizationBudget

Requirements

Simulation

◦ What types of contacts to service?

◦ How do we best match channels to segments of customers?

◦ What standards are right for each contact types?

◦ Where (which centers and staff types) and when (which weeks) do we hire?

◦ Hiring versus overtime?

◦ How many centers are optimal?

◦ Budgets and budget priorities?

… and so much more

Webinar 1: How to automate your forecasts

We discussed:

◦ Purpose of forecasting (and which metrics are important to forecast)

◦ Humans versus (Learning) Machines

◦ A solid and standard forecasting process -- the math around:

• Spotting outliers

• Determining seasonality

• Choosing a method and automating it!

◦ New journey data – and forecasting of the future



Webinar 2: Math Modeling

We discussed:

◦ What is capacity planning?

◦ Types of models and what do they do (see next slides)

◦ How to judge whether models are good or not (it is important to validate!)

◦ Why it is important: what do we get if we have good models

• Consistent service delivery over time

• Lower costs. Always

◦ What happens to our operation when we automate our planning process

• The ability to quickly do great analytics!



Webinar 2: What are the steps to strategic planning?

Strategic planning systems work to take you from forecast to budget. They help to:



Requirements

Simulation

Predictive Model

“Predict the future”

(Covered in our last webinar)

Descriptive Model

“What happens to my operation in this scenario?”

Prescriptive Model

“Find me the best resource decision”

Variable Labor Model

“Cost it all out”

Webinar 3: Optimizing agent training

We (Huw Bristow) discussed:

◦ Three specific elements in getting the best from your employees:

• 1) Knowing the skills required to be a great employee;

• 2) Finding the skill gaps of each individual employee; and

• 3) Determining the best training schedule that addresses these gaps.



I (sort of) lied: Its not really linear – it is an ongoing process!



Requirements

Simulation

These are our modeling steps– but they are not the process steps to long term planning!

10

Cost Out The Plan

Plan For The

Future

The Standard Approach: How to Put Together a Plan

Predict The

Future

Tweak &

Analyze Plan

Argue About The Past

ForecastBudgeting

Capacity/Staff Plan

Sensitivity &

What-If Analysis

Variance Analysis

11

Variance Analysis

Note! Wages are growing relative to the forecast!

What can change?

◦ Call center/agent performance (AHT, sales per call, FMLA/absenteeism,…)

◦ Customer behavior (i.e. volumes, AHT, why they are calling, revenue potential per cal,…)

◦ Executive behaviors (center goals, center strategies, center configuration – number of centers, specialties of centers,… )


Unauthorized disclosure is prohibited. 12(A lot can change)

Variance analyses are our canary in the coalmine

Why is there variance?

1. The forecast may be off– a math or process error

2. Something external may have changed the mix of contacts or agent performance

3. Something internal may have changed the mix of contacts or agent performance

4. It could be a random occurrence (a blip)

A very appropriate role of your forecasting process is to be an early warning signal. And variance is often the impetus for many what-ifs!

Is it error or is it change?

Error

◦ Can I tweak my model to make it better?

◦ Hindsight: Was it my modeling choices

that made the difference in accuracy?

◦ Nobody understands what’s different this

month

Change

• Or do I have to throw away my

model for something radically

different?

• Hindsight: Did I have any way of

forecasting this right?

• We are hearing about the change

(from the agents, from the news,

etc…)

What many management teams view as error is really change! The best management teams view error as change!

Questions we should ask before we reforecast

1. Is it error? If so, let’s fix it?

2. If it is change:

▪ When will we have enough data to reforecast?

▪ Do we understand what has changed –

can/should we fix it (change back)?

▪ If we do not have enough history, can we provide

sensitivity analyses to show the repercussions of

a high, medium, and low scenario?

▪ Let’s overcommunicate!

3. Is the variance significant? (meaning, will

it change our decisions??)



Is the variance significant? Vol Vs. SL/Staff Required



Sensitivity analysis is a quick way of determining the effects on service, staffing, and cost of variance

See webinar 2: having a validated contact center model makes sensitivity analyses possible.

Is the variance significant? AHT Vs. SL/Staff Required



See webinar 2: having a validated contact center model makes sensitivity analyses possible.

Varying handle times to determine the impact of variance on service levels and staff required

What do you do when there is variance?

Significant Variance

Controllable?

Yes

Yes

Yes

No

NoNo

Want to fix?

Fix Issue!

Ready to makeA decision?

Prepare for change!

Monitor Performance

What-Ifs!

Genesys confidential and proprietary information. Unauthorized disclosure is prohibited. 19

Cool What-Ifs: What service level goals should the business use?

At different times, under different economies of scale and revenues per call, different service goals are optimal!

Optimal service standards!

55% within 20 seconds

70% within 20 seconds

Should expected sales change your service goals?

Revenue/Sale: $400

Revenue/Sale: $250

Revenue/Sale: $50

Revenue/Sale: $100

Value per sale strongly influences service standard optimization: The most profitable ASA floats between 15 and 65

seconds given revenue/sale of $50 to $400 per hour: This implies service standards may vary (optimally) by season!

Sensitivity analysis helps answer

what-ifs, like “What service level

goal can we afford?”

Tip: Evaluate your

service standards

often– use sensitivity

analyses!

Cool What-Ifs: For service functions (not sales) this trade-off is very interesting!

What is my optimal staffing policy? (heard this one Monday at SWPP!)

Total Fixed and Variable Cost for a Sample Call Center

Given Different Staffing Strategies

5700000

5720000

5740000

5760000

5780000

5800000

5820000

5840000

5860000

5880000

5900000

40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90%

Hire to Percent Answered in 20 Seconds

Co

st

(Do

lla

rs) Staff to 40% Service Level

Overtime to Hit Goal

Staff to 70% Service Level



Undertime to Reduce Costs

During Slack Weeks


Undertime to Reduce Costs

During Slack Weeks



What-if: Have you ever tried to tame marketing?

◦ Marketing seems to be the operation’s

bane

• Uncoordinated mail drops

• Experimental offerings

• Catching the call center unaware with heavier volumes or more complex phone calls

◦ … and they never, ever call us first!

How Operations Views a Marketer

There are times to market, and times to not…

But, this is a terrific time for a marketing event!

Given seasonality, call center demand fluctuates. This is a terrible time for a marketing event

A little coordination goes a long way

This company involved, in their regular, monthly

(best practice) planning and decision making

meeting, marketing (also, best practice)

• The operation alerted marketing when they had little capacity for events

• They also alerted marketing when they had excess capacity to be used for marketing events

• AND, marketing used this venue to alert the operation to their plans

Marketer, after they call us

If we plan well, what happens?

◦ We have an easier workforce management process.

We have the right number of agents show up to

work Monday morning!

◦ Our service is more consistent, and our operation

smoother. We get fewer service hiccups

◦ Our costs are lower, and yet we still hit our service

goals (typically with a 5-8% improvement in

efficiency) (Precise, well run machine!)

The key to improving your planning is to improve your planning technology

Three criteria: Your planning process has to be fast, optimal, and accurate

Accurate:• You must be able to prove

(validate) that your planning models are accurate

• Hint: Erlang and occupancy forecast methodologies are typically not very accurate (they overstaff)

• Another hint: consider• Simulation is accurate if

validated

Optimal:• Your methodology has to

deliver just-in-time hiring plans

• Your methodology has to be able to find the optimal balance between overtime, undertime, and hiring, while meeting all your constraints

• Hint: You cannot do this by hand

• Another hint: optimization modeling, such as integer programming will save your company money!

Fast:• There is no reason a

planning scenario- from forecast to capacity plan to budget cannot be completed in 10 minutes

• Hint: Automate it all!

What is Decisions?

◦ Decisions is a long-term contact center strategic planning and what-if analysis system.

◦ Because it is fast and accurate:• Perform risk and sensitivity analysis of your contact center

• Evaluate center what-ifs: investments, consolidation, and growth opportunities

◦ Decisions complements traditional workforce management software by focusing on strategic decision making and long-term planning





Requirements

Simulation

Thank you!Ric Kosiba, Vice President, Genesys Decisions

[email protected]

317-957-1109 – office

410-224-9883 - mobile

mailto:[email protected]

how great contact center plans lead to a better...

Documents