Would you pay $15 to see 10 minutes of a movie? Of course not; you want the whole story. Why should quality assurance be any different? On average, companies spend more than $2,300 per agent each year for call recordings and agent scoring. With that investment, they get a yes/no checklist and solid details on a smattering of compliance behaviors. Both are important – but are they enough? Depends how you measure success.
If you’re primarily concerned with regulation and policy adherence, stick with the tried and true approach to monitoring. But if you’re under pressure to impact business performance and customer relationships, it’s past time to shift gears. In our experience, very few companies have given concentrated attention to truly re-aligning the monitoring function. Other than moving resources offshore, we haven’t seen any major trends in the last 15 years. While it’s important to lower cost and be conscious of every dollar, it’s even more important to take actions based on data-driven intelligence.
What Leaders Have in Common
Companies that have exponentially increased the effectiveness of their quality program, and enjoyed huge financial returns as a result, have three things in common:
1) Use a Wider Lens: The smartest companies are enhancing quality functions by listening more broadly. They apply sound research principals and an outside-in approach to re-create quality as a business strategy. Instead of one-and-done approaches managed within process siloes, they’ve figured out that integration of all listening posts into a single information hub is where it’s at. So what kinds of data go into an information hub? In short, everything. Call observations, quality scores, survey data, call recordings, agent mouse-clicks, financials . . . everything counts. The trick to turning this “big data” into something usable is ensuring you have representation from three primary areas:
- • Critical to the Customer: Expanded data and statistically significant sample sizes provide robust analytics including agent performance and customer expectations. Things like customer effort, agent empathy and channel of choice fall into this bucket.
- • Critical to the Operation: Multiple data sources are leveraged to drill deep into the experience, identifying root causes of operational inefficiencies and customer pain points. Measures like operational efficiency, self-service success and upstream impacts are captured here.
- • Critical to Compliance: Expanded metrics on process adherence, regulation enforcement and security procedures are important as well. Things like adherence and compliance are assessed.
2) Get to the ‘How’ Behind the ‘What’
Modern advances in speech analytics have allowed businesses to reliably recognize even iterative phrases during conversations, a significant advancement in assessing agent compliance. This level of specificity and reliability is crucial for accurately measuring agent performance and can paint a very different picture from what the company gets using traditional quota methods. And by increasing the volume of observations to every call, not just a random subset, agents and their team leads are more likely to act on findings rather than debate their validity.
The biggest gain in ROI using speech technology has been its success understanding customer sentiment. By tracking sentiment and implementing real-time monitoring, companies can be alerted of potential detractors and defectors – without waiting for survey results. Retention teams are parachuted in even while the customer is on the first call. Supervisors and the agents themselves are notified for real-time agent performance intervention.
3) Focus on Business Impact: The few that have made a sea change and turned their quality programs into a strategic imperative are committed to:
- • Following the Money: These teams understand which call drivers are most costly to the business and/or painful for customers, and they focus observations on changing these outcomes . . . not just on meeting agent quotas.
- • Creating Smart(er) Data: Innovative firms leverage technology and data science to link quality observations to operational and financial data sources, ensuring more robust and insightful analytic modeling.
- • Expanding the Sphere of Influence: Leaders that are super heroes to the c-suite engage their peers in cross-functional planning to resolve upstream issues. They leverage more than pain point insights and one-off solutions; instead, they work to develop objective business cases for change with rank-ordered options and statistically valid tradeoffs.
Proof It Works
When companies implement the above, they’ve experienced multiple benefits like right-sized observations (and investment), more engaged agents, richer quality insights and truly transformational results. As an example, one satellite provider adopted these principals and in less than a year shed 15% of their total call volume by truly understanding the root cause of contacts and fixing upstream drivers of the calls themselves. Root causes spanned the gamut – from quick wins like making it easier for customers to login to self-service diagnostic tools, to more strategic changes like redesigning the promotion strategy. The payback? More than $24M in less than one year.
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