What Happened to Quality?
Abstract
Greg and Fred discuss quality from engineering and quality points of view. Greg is developing AI engineering applications. Greg wants to build, ship, and monetize. Fred wants to build quality in. What do you think is the right way?
Key Points
Join Greg and Fred as they discuss what’s happened to quality from critical perspectives. Topics include:
- State of today’s quality profession
- ‘Show me the money’ approaches
- ‘Build quality and reliability from the get go’ approach
Enjoy an episode of Speaking of Reliability as sparks fly. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
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Show Notes
Achieving the right balance between qc & productivity will involve setting clear standards, empowering staff & optimizing processes regularly . Leveraging technology for automation and data analysis will streamline quality checks while boosting productivity concurrently for the business.
When I say “metrics” what’s the first thing that comes to mind? If your answer is spreadsheets and dashboards packed with tons and tons of analytics, you’re probably not alone. And while many of these metrics have their purpose, when it comes to agent performance, there are really two types of metrics that matter. The first is a productivity metric and the second a quality metric.
There’s something critical to note about these two metrics. Neither metric is mutually exclusive, requiring the right balance between the two to achieve the positive results you’re looking for in your contact center. In cases where quality and productivity are out of balance, negative consequences are likely to follow. Before we talk about the ideal balance, let’s first define these metrics and discuss some of the consequences that can result if one is valued more than the other.
Imagine that your company was just featured on a popular television show and overnight your email backlog jumped from 100 to 20,000. You instruct your staff of 10 agents to get through that backlog by the end of the week. I did a little math, and that’s like 400 emails per day. If that’s the requirement, what kind of quality do you think you’ll see? Probably not great, right?
Your agents will likely begin creating canned responses and sending them as quickly as possible with little to no personalization. This increases the likelihood that customers receive replies that only partially address the issue, resulting in a dive in customer satisfaction and increased follow up emails from customers. This is a great way to keep that backlog from never disappearing.
Now imagine you’re looking at productivity for your phone team and discover that one of your agents handles calls two minutes faster than the rest of the team and takes significantly more calls than everyone else. You might be tempted to call them a rockstar until you discover that they’re disconnecting customers before they’ve fully resolved the issue all in the name of efficiency and productivity.
While these two scenarios may seem far fetched, I can assure you that they’re both based on true stories. Clearly, a singular focus on productivity has some serious flaws.
References:
https://www.icmi.com/resources/2019/quality-productivity-and-striking-the-right-balance
https://www.linkedin.com/advice/0/what-best-ways-balance-quality-control-productivity-ptamf#:~:text=Achieving%20the%20right%20balance%20between,productivity%20concurrently%20for%20the%20business.
Hi Carl:
Good morning. Very thoughtful response. I hope I can add some context.
The science of personal productivity and metrics have been around since Taylor. The challenge is that the concepts have been used to dehumanize work.
Now, we have AI agents that can provide autonomous decision making, emphathy, and inspection. If the AI agents can respond to teh backlog by discerning patterns of similarity then, the work can be automated with seemingly human ‘caring. Several reference:
Attended AI conference this weekend. Results:
“a research paper published by Google researchers in January, a Large Language Model (LLM) based AI system optimised for diagnostic dialogue in the medical field outperformed doctors on 28 out of 32 evaluation axes related to conversation quality, diagnoses, and management plans.Mar 4, 2024′”
And
“Google’s healthcare AI ranked higher than human physicians across 24 of 26 conversational axes, according to the patient actors in the study, who reported that AMIE outperformed across areas like politeness, coming across as honest, explaining the condition and treatment, and expressing care and commitment.”
https://www.pymnts.com/artificial-intelligence-2/2024/google-claims-healthcare-ai-more-empathetic-accurate-than-real-life-doctors/#:~:text=Google's%20healthcare%20AI%20ranked%20higher,and%20expressing%20care%20and%20commitment.
In other words, AI demonstrated more ‘humanness’ than a human doctor. Much in the same way, QC tasks can be automated.
This future is definitely interesting. Dystopian? Or freed and fulfilling? We’ll soon see.
Thanks for your deep thoughts. Very much appreciated.
Hi Greg,
Loved the conversation between you and Fred. I have been studying Quality, in different shapes and forms and talked to people from different departments, different shapes and forms, at work, and during my research.
I think we need more conversations on Quality and what you and Fred have been talking about. I liked your controversial style, it was refreshing – as opposed to all the time people agreeing and taking the safe path out of a conversation.
Apart from my work, research and study on quality, which has been mainly looking at the human side of quality, the psychology of empowerment and self-empowerment and how it has an impact on quality, I have recently co-authored a paper, and raised this question:
“Is quality management dead? How can Deming’s 14 points be a vital resuscitator for quality management in the era of AI?” In my humble way, trying to approach this from the human side of quality.
It seems that quality is more human than we think it is, hmm.. maybe?
Kind regards.
Hi Rozana:
Good day. Thanks much for your kind words. It’s good to hear from you.
Many professions are being disrupted. Check out today’s Financial Times article: Banks and Account Firms Should Brace for Cost of AI JoB Losses: Unions Warn”
Also check out: FutureofProfessions.com. A few years ago, Taylor/Francis out of the UK and our company tried to monetize teh disruption. We found it more difficult that we imagined.
When I read your piece, I thought you’d written ‘conversational.’ Now, I see it is controversial. Yes, you’re right. Folks don’t want to read or listen to “same same.’ A little spice makes it interesting.
Many of our talks focus on the rules of engagement between ‘human and machine.’ This involves trust. Much in the same way, quality has lost its way due to trust or the lack there of. We think you’re onto something.
Talk soon. Greg