What's Wrong With How We're Counting 'Service Level' in Our Call Centres and How To Fix It! This slidedeck will de-fine, de-mystify and de-tangle call centre Service Level.
Customer Service Call Center Benchmark StudyChris Scafario
This presentation highlights some best practice players in the world of customer service and call center management; from first time resolution to order up sells. It also goes on to perform a rather organizationally specific gap analysis complete with actions steps designed to support a journey of continuous improvement.
Customer Service Call Center Benchmark StudyChris Scafario
This presentation highlights some best practice players in the world of customer service and call center management; from first time resolution to order up sells. It also goes on to perform a rather organizationally specific gap analysis complete with actions steps designed to support a journey of continuous improvement.
7 concrete ways to cut costs without cutting quality in your contact centreHilario Fiandeiro
Under pressure to…
• Serve more customers BUT with less cost
• Do service faster AND with better quality
• Handle more complexity BUT with lower AHT!
Operating a contact centre that delivers consistent success, is not easy.
View my latest SlideShare for concrete ideas on how to cut costs without cutting quality in your contact centre and beyond…
#BeContactCentreSmart
FUSION14 Session 302 | Optimizing the Tradeoff: Cost vs. Quality in IT SupportMetricNet
Cost vs. quality: It’s a perennial issue in technical service and support. Drive your costs too low, and you risk sacrificing the quality of service. Conversely, if you push quality too high (yes, that’s possible!), then you drive your costs through the roof. Understanding the cost/quality tradeoff is the most critical step toward optimizing your support model. Using data from more than 300 benchmarks worldwide, Jeff Rumburg will illustrate how top-performing service and support organizations strike an appropriate balance between the cost of service delivery and the quality of support provided. He’ll share simple yet powerful techniques that will enable organizations to pinpoint their position on the cost vs. quality curve, determine if higher (or lower) quality is justified, reduce costs without sacrificing quality, and improve quality without increasing costs. Finally, he’ll share an interactive scorecard that organizations can use to determine whether service and support has been optimized, and, if it hasn’t, to identify the tangible steps needed to achieve an optimized support model.
Call Center Statistics or Performance Metricsguest14c061
An article on the differences between call center statistics and call center performance metrics. Which of these should a call/ contact center use? Which is better?
5-minute Practical Streaming Techniques that can Save You MillionsHostedbyConfluent
"Companies are looking for ways to reduce streaming infrastructure costs in the current macroeconomic environment. However, this is a difficult task for two reasons. First, cutting costs without sacrificing latency or correctness requires deep knowledge of engine implementation details and a keen eye to identify opportunities. Second, optimization techniques are less accessible when working with high-level language abstraction, such as SQL. These techniques often involve engine query planning, requiring even deeper expertise. Many Data Engineers and Data Scientists prefer not to deal with Intermediate Representations (IR) and optimization rules. They also may not care too deeply about the details of applying streaming watermarks to reduce the runtime complexity for Point-In-Time-Correct join queries.
In this talk, I will share some simple optimization techniques you can apply with streaming SQL in just a few minutes that can cut costs by 10x or even 100x. Then, we’ll gradually dive deeper into some novel optimization techniques that can be applied across your distributed storage and compute stacks.
By the end of this talk, if you are a Data Engineer or a Data Scientist who is looking to build real-time streaming workloads but have concerns about cost, I hope you’ll be able to walk away with some tricks so you can check that box on your product ROI OKR :) If you are a platform engineer, I hope you will learn how to apply optimization abstractions across various compute and storage engines in your platform."
Managing a workforce is hard. Thankfully, Workforce Management (WFM) tools can help you automate, optimize and manage scheduling in your contact center. Follow the slides to learn the top 6 workforce management challenges with solutions to overcome each.
Hotel management system, a type of management information system. This concept will enable you to get full understanding of the information system and how it works.
The Light Bulb Moment – Learning to-identify-robotic-automation-opportunitiesOpenSpan
The “Light Bulb Moment” is the point when you realize how Robotic Automation and Robotic Desktop Automation could help you boost productivity and drive superior results in the process-centric parts of the enterprise.
7 concrete ways to cut costs without cutting quality in your contact centreHilario Fiandeiro
Under pressure to…
• Serve more customers BUT with less cost
• Do service faster AND with better quality
• Handle more complexity BUT with lower AHT!
Operating a contact centre that delivers consistent success, is not easy.
View my latest SlideShare for concrete ideas on how to cut costs without cutting quality in your contact centre and beyond…
#BeContactCentreSmart
FUSION14 Session 302 | Optimizing the Tradeoff: Cost vs. Quality in IT SupportMetricNet
Cost vs. quality: It’s a perennial issue in technical service and support. Drive your costs too low, and you risk sacrificing the quality of service. Conversely, if you push quality too high (yes, that’s possible!), then you drive your costs through the roof. Understanding the cost/quality tradeoff is the most critical step toward optimizing your support model. Using data from more than 300 benchmarks worldwide, Jeff Rumburg will illustrate how top-performing service and support organizations strike an appropriate balance between the cost of service delivery and the quality of support provided. He’ll share simple yet powerful techniques that will enable organizations to pinpoint their position on the cost vs. quality curve, determine if higher (or lower) quality is justified, reduce costs without sacrificing quality, and improve quality without increasing costs. Finally, he’ll share an interactive scorecard that organizations can use to determine whether service and support has been optimized, and, if it hasn’t, to identify the tangible steps needed to achieve an optimized support model.
Call Center Statistics or Performance Metricsguest14c061
An article on the differences between call center statistics and call center performance metrics. Which of these should a call/ contact center use? Which is better?
5-minute Practical Streaming Techniques that can Save You MillionsHostedbyConfluent
"Companies are looking for ways to reduce streaming infrastructure costs in the current macroeconomic environment. However, this is a difficult task for two reasons. First, cutting costs without sacrificing latency or correctness requires deep knowledge of engine implementation details and a keen eye to identify opportunities. Second, optimization techniques are less accessible when working with high-level language abstraction, such as SQL. These techniques often involve engine query planning, requiring even deeper expertise. Many Data Engineers and Data Scientists prefer not to deal with Intermediate Representations (IR) and optimization rules. They also may not care too deeply about the details of applying streaming watermarks to reduce the runtime complexity for Point-In-Time-Correct join queries.
In this talk, I will share some simple optimization techniques you can apply with streaming SQL in just a few minutes that can cut costs by 10x or even 100x. Then, we’ll gradually dive deeper into some novel optimization techniques that can be applied across your distributed storage and compute stacks.
By the end of this talk, if you are a Data Engineer or a Data Scientist who is looking to build real-time streaming workloads but have concerns about cost, I hope you’ll be able to walk away with some tricks so you can check that box on your product ROI OKR :) If you are a platform engineer, I hope you will learn how to apply optimization abstractions across various compute and storage engines in your platform."
Managing a workforce is hard. Thankfully, Workforce Management (WFM) tools can help you automate, optimize and manage scheduling in your contact center. Follow the slides to learn the top 6 workforce management challenges with solutions to overcome each.
Hotel management system, a type of management information system. This concept will enable you to get full understanding of the information system and how it works.
The Light Bulb Moment – Learning to-identify-robotic-automation-opportunitiesOpenSpan
The “Light Bulb Moment” is the point when you realize how Robotic Automation and Robotic Desktop Automation could help you boost productivity and drive superior results in the process-centric parts of the enterprise.
Why Contact Centres are Costing More than They Should & How to Fix This!Hilario Fiandeiro
I share SIX insights on why contact centres are costing more than they should.
1. We're not embracing self-service automation to the max.
Often, it's because we think customers prefer to speak to a human. As it turns out, most customers actually prefer interacting with well-designed self-service systems.
2. We're dealing with too many repeat + transferred + escalated contacts.
Research shows that nothing erodes customer loyalty more than instances where customers have to make 'more than one contact' to resolve an issue.
3. Most of our 'first-time' contacts could be prevented in the first place.
We're getting good at reacting to service failures. We need to get much better at preventing service failures from happening in the first place.
4. Our contact centre group structures are unnecessarily specialised.
We tend to split our contact centres into smaller agent groups not because we should, but because we can. This means we're not benefiting, as much as we should, from 'economies of scale'.
5. Our 'slim-fit' AHT's (Average Handle Times) aren't as healthy as they appear to be.
We tend to look at AHT purely as a number that needs to be met, not as a behaviour that needs to be managed.
6. Our people aren't as productive as they should be.
We tend to rely too much on 'offering juicier carrots' or threatening with 'bigger sticks' to improve performance. Our focus needs to shift towards creating a culture that is intrinsically motivating.
Now here's the thing…
Not only do the above factors cost more they also more likely to damage customer loyalty.
So this has a 'double-negative' impact on an organisation's bottom line.
Counting what Counts in Contact Centres - A Course IntroductionHilario Fiandeiro
Managing a contact centre can be difficult when you find yourself paddling through an endless sea of data and performance measures.
That's why I've designed this course...to help contact centre professionals keep their 'heads above water'.
By understanding and applying the right metrics, you can make a hugely positive impact on your contact center, your customers, and your entire organisation.
Counting What Counts in Contact Centers - Call Quality MonitoringHilario Fiandeiro
With ‘Call Quality Monitoring (CQM)’, we need to be spending much MORE time obsessing about how we can improve each customer conversation and much LESS time haggling about the validity and fairness of CQM scores.
This slide deck highlights what's wrong with CQM in our call centres and suggests how to fix It!
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Show drafts
volume_up
Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Counting What Counts in Contact Centers - Service Level
1. Brought to you by…
ContactCentreSmart
Dismantling Frustration. Engineering Happiness
Counting what counts in
contact centres...
Image credit: sxc.hu/profile/onetwo
Service
Level
17. Defining, demystifying and detangling…
Service Level (SL)
What
count
What
count
What exactly is SL?What exactly is SL?
Why
count
Why
count
When
count
When
count
How
count
How
count
Counting
cousins
Counting
cousins
Why is SL a BIG deal?Why is SL a BIG deal?
When should we use SL?When should we use SL?
How do we measure SL?How do we measure SL?
How does SL relate or impact other metrics?How does SL relate or impact other metrics?
Counting
benchmark
Counting
benchmark
Counting
calamity
Counting
calamity
What are the benchmarks for SL?What are the benchmarks for SL?
What can go wrong with SL?What can go wrong with SL?
17
27. 27
SL is central to call centre planning and staffing
1 Choose
SL Target
2 Collect
Data
3 Forecast
Call Load
4 Calculate
Base Staff
5 Calculate
Shrinkage6 Calculate
Actual Staff
7 Organise
Schedules
8 Determine
Budget required
9 Optimise to
get best SL-
Budget Fit
Planning
Process
Start here…
29. 29
Use Service Level when…
Contacts have to be handled when
they arrive
Use Response Time when…
Contacts don’thave to be handled
when they arrive
30. 30
Contact Type Service Level Response Time
Inbound phone calls
Outbound phone calls
Web chat
SMS
Email transactions
Faxes / Post-mail
Walk in customers
Web call me now
Web call me later
35. 35
270
Here’s an Example
How many staff is
required to achieve SL?
Number of Phone Calls in an Half-hour
Average Handling Time (in seconds) 200
Required Service Level (x % in y sec’s) 80/20
36.
37. 270 # of phone calls
x 200 AHT seconds___
54,000 seconds
÷ 1,800 seconds (in ½ hour)
30 Agents needed!
38.
39. 39
Contact Type Service Level Response Time
Inbound phone calls
Outbound phone calls
Web chat
SMS
Email transactions
Faxes / Post-mail
Walk in customers
Web call me now
Web call me later
For these weFor these we
need to use
this…
45. 45
Contact Type Service Level Response Time
Inbound phone calls
Outbound phone calls
Web chat
SMS
Email transactions
Faxes / Post-mail
Walk in customers
Web call me now
Web call me later
For these
use this…
For these
it’s OK to
use this…
46. 270 # of emails
x 200 AHT seconds___
54,000 seconds
÷ 1,800 seconds (in ½ hour)
30 Agents needed!
47. Basic Response Time
Formula…
Agents = Volume
(RT ÷ AHT)
Volume = Number of contacts to be handled
RT = Response time (in min)
AHT = Average Handle Time (in min)
48. 48
60
Here’s an Example
How many staff is
required to achieve RT?
Number of outbound calls to be made
Average Handling Time (in min’s) 4
Required Response Time (in min’s) 120
79. SL Suitability Test
Q1: Meet customers' needs and expectations
Q2: Keep abandonment at acceptable levels
.
Disagree Neutral Agree
ContactCentreSmart
Dismantling Frustration. Engineering Happiness
Does your SL…
Q3: Minimise expenses AND maximise revenue
Q4: Minimise agent burnout and errors
.
Q5: Support the organisation's mission and brand
119. hilario@ContactCentreSmart.com
www.ContactCentreSmart.com
Connect
Find this useful? Follow me on LinkedIn
to get more of this type of stuff…
‘What's Wrong With How We're
Counting 'SL' & How To Fix It!’ Read it…
Read
Need the full ‘Count what Counts in
Contact Centres’ workshop? Find out…
Find Out
Need me to deliver a customised a SL
workshop? Enquire here…
Enquire
Need help with a question relating to
SL? Ask here…
Ask
120. About the author...Hilario Fiandeiro
Hi! I’m Hilario is the owner of ContactCentreSmart, an
independent consulting practice, specialising in ‘dismantling
frustration and engineering happiness™’ in customer-facing
environments.
I have more than fifteen years experience, as an operations
manager, facilitator and management consultant, across
various industries, in the customer experience and contact
centre space.
As a professional consultant operating from Johannesburg,
South Africa, I focus exclusively on making customer-serving
professionals more successful and customer interaction
experiences more rewarding.
For more information…
Contact me on:
hilario@ContactCentreSmart.com
www.ContactCentreSmart.com