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The Deeper Problem Under HealthCare.gov's Rocky Start

Even as the federal government appears to have untangled the worst of HealthCare.gov's problems, the finger pointing and agonizing about what went wrong with the Affordable Care Act's centerpiece website are unlikely to die down any time soon.

The political dimensions aside, there's a persistent curiosity about how such a high-profile project could have failed so spectacularly. It was possibly the world's most important IT project of the moment, yet it performed as if it were rolled out the door without so much as a cursory kick of the tires.

That's because it probably was – and that's far from unusual.

A recent LinkedIn/Empirix survey found that at most companies and public agencies, pre-deployment testing is half-hearted at best and non-existent at worst. Public agencies and private companies alike have abysmal records for testing customer-facing IT projects, such as customer service and e-commerce portals.

This is despite the importance that most organizations place on creating a consistently positive customer experience; almost 60 percent of the contact center executives interviewed for Dimension Data's 2012 Contact Center Benchmarking Report named customer satisfaction as their most important metric.

It's not that IT doesn't test anything before they roll out a project. It's that they don't test the system the way customers will interact with it. They test the individual components — web interfaces, fulfillment systems, Interactive Voice Recognition systems (IVRs), call routing systems — but not the system as a whole under real-world loads. This almost guarantees that customers will encounter problems that will reflect on the company or agency.

Empirix and LinkedIn surveyed more than 1,000 executives and managers in a variety of industries. The survey asked how companies:

- tested new customer contact technology before it was implemented

- evaluated the voice quality of customer/service agent calls

- monitored overall contact center performance to maintain post-implementation quality

The results are a series of contradictions. While it appears from overall numbers that pre-deployment testing rates are high — 80 percent or better — the numbers are actually much less impressive than they appear.

In truth, the overall picture isn't good. More than 80 percent of respondents said their companies do not test contact center technology under real-world conditions before go-live. They do some form of testing, but it's not comprehensive enough to reveal all of the issues that can affect customer service.

They're a little bit better about testing upgrades to existing systems: 82 percent reported testing upgrades. There's grade inflation in this number, however. Sixty-two percent use comparatively inaccurate manual testing methods.

While better than not testing at all, manual testing does not accurately reflect real-world conditions. Manual tests usually occur during off-peak times, which do not accurately predict how systems will work at full capacity. Because manual testing is difficult to repeat, it is usually done only once or twice. That makes it harder to pinpoint problems — and ensure they are resolved — even if they are detected pre-deployment.

Another 20 percent don't test new technology at all; they just "pray that it works” (14 percent) or react to customer complaints (3 percent). The remaining 3 percent are included with the non-testers because they only test major upgrades. They're included with the non-testers because of the obvious flaw in their reasoning that only major upgrades are test-worthy. A small change can erode performance or cause a system crash just as easily as a major upgrade. In fact, small upgrades can create performance drags that are harder to pinpoint because unlike large upgrades, they do not have the IT organization's full attention.

Only about 18 percent of respondents said that their companies use automated testing for all contact center upgrades. That's the second-largest block of users after the manual testing group, but a low overall percentage of the total. These companies use testing software to evaluate the performance of new functionality, equipment, applications and system upgrades under realistic traffic conditions. This approach yields the most accurate results and rapid understanding of where and why problems are occurring.

The Spoken Afterthought

HealthCare.gov's problems highlighted shortcomings with web portal testing, but voice applications face similar neglect. Indeed, when the President advised people to use their phone to call and apply for healthcare, many of the call centers set up to field applicants also had trouble handling the spike in caller traffic.

Voice quality can be a significant drag on short- and long-term call center ROI. Contact center agents who must ask customers to repeat themselves because of poor voice connections — or worse, ask customers to hang up and call in again — are less productive than those who can hear customers clearly. In the long term, repetition and multiple calls erode customer satisfaction levels.

The vast majority of professionals who responded to the LinkedIn/Empirix survey — 68 percent reported that their companies never monitor contact center voice quality. Only 14 percent continuously monitor voice quality, while the remaining 17 percent periodically monitor on a daily, weekly or monthly basis.

This failure carries heavy risks. Globally, 79 percent of consumers replying to a Customer Experience Foundation survey said they experienced poor voice quality on contact center calls. Almost as many — 68 percent — said they will hang up if they experience poor voice quality. If they are calling about a new product or service, they will likely call a competing company instead.

Between misdirected efforts and testing rates like these, it's no wonder people aren't surprised when a major initiative like online healthcare enrollment goes off the rails, or customers calling a contact center get funneled down a blind alley in the IVR system. Customers who run into obstacles like those are on a fast track to becoming former customers.

Testing and performance monitoring can effectively stem those losses. Businesses that test and monitor customer service systems are better able to achieve maximum ROI on their customer service systems (CSS) by identifying and remediating problems quickly. An end-to-end monitoring solution provides organizations with deep visibility into complex customer service technology environments, enabling businesses to reduce the time it takes to understand the source of a problem — and fix it — before customers ever notice the glitch.

ABOUT Matthew Ainsworth

Matthew Ainsworth is Senior Vice President, Americas and Japan at Empirix. He has 15 years of experience in contact centers and unified communications solutions.

Related Links:

www.empirix.com

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The Deeper Problem Under HealthCare.gov's Rocky Start

Even as the federal government appears to have untangled the worst of HealthCare.gov's problems, the finger pointing and agonizing about what went wrong with the Affordable Care Act's centerpiece website are unlikely to die down any time soon.

The political dimensions aside, there's a persistent curiosity about how such a high-profile project could have failed so spectacularly. It was possibly the world's most important IT project of the moment, yet it performed as if it were rolled out the door without so much as a cursory kick of the tires.

That's because it probably was – and that's far from unusual.

A recent LinkedIn/Empirix survey found that at most companies and public agencies, pre-deployment testing is half-hearted at best and non-existent at worst. Public agencies and private companies alike have abysmal records for testing customer-facing IT projects, such as customer service and e-commerce portals.

This is despite the importance that most organizations place on creating a consistently positive customer experience; almost 60 percent of the contact center executives interviewed for Dimension Data's 2012 Contact Center Benchmarking Report named customer satisfaction as their most important metric.

It's not that IT doesn't test anything before they roll out a project. It's that they don't test the system the way customers will interact with it. They test the individual components — web interfaces, fulfillment systems, Interactive Voice Recognition systems (IVRs), call routing systems — but not the system as a whole under real-world loads. This almost guarantees that customers will encounter problems that will reflect on the company or agency.

Empirix and LinkedIn surveyed more than 1,000 executives and managers in a variety of industries. The survey asked how companies:

- tested new customer contact technology before it was implemented

- evaluated the voice quality of customer/service agent calls

- monitored overall contact center performance to maintain post-implementation quality

The results are a series of contradictions. While it appears from overall numbers that pre-deployment testing rates are high — 80 percent or better — the numbers are actually much less impressive than they appear.

In truth, the overall picture isn't good. More than 80 percent of respondents said their companies do not test contact center technology under real-world conditions before go-live. They do some form of testing, but it's not comprehensive enough to reveal all of the issues that can affect customer service.

They're a little bit better about testing upgrades to existing systems: 82 percent reported testing upgrades. There's grade inflation in this number, however. Sixty-two percent use comparatively inaccurate manual testing methods.

While better than not testing at all, manual testing does not accurately reflect real-world conditions. Manual tests usually occur during off-peak times, which do not accurately predict how systems will work at full capacity. Because manual testing is difficult to repeat, it is usually done only once or twice. That makes it harder to pinpoint problems — and ensure they are resolved — even if they are detected pre-deployment.

Another 20 percent don't test new technology at all; they just "pray that it works” (14 percent) or react to customer complaints (3 percent). The remaining 3 percent are included with the non-testers because they only test major upgrades. They're included with the non-testers because of the obvious flaw in their reasoning that only major upgrades are test-worthy. A small change can erode performance or cause a system crash just as easily as a major upgrade. In fact, small upgrades can create performance drags that are harder to pinpoint because unlike large upgrades, they do not have the IT organization's full attention.

Only about 18 percent of respondents said that their companies use automated testing for all contact center upgrades. That's the second-largest block of users after the manual testing group, but a low overall percentage of the total. These companies use testing software to evaluate the performance of new functionality, equipment, applications and system upgrades under realistic traffic conditions. This approach yields the most accurate results and rapid understanding of where and why problems are occurring.

The Spoken Afterthought

HealthCare.gov's problems highlighted shortcomings with web portal testing, but voice applications face similar neglect. Indeed, when the President advised people to use their phone to call and apply for healthcare, many of the call centers set up to field applicants also had trouble handling the spike in caller traffic.

Voice quality can be a significant drag on short- and long-term call center ROI. Contact center agents who must ask customers to repeat themselves because of poor voice connections — or worse, ask customers to hang up and call in again — are less productive than those who can hear customers clearly. In the long term, repetition and multiple calls erode customer satisfaction levels.

The vast majority of professionals who responded to the LinkedIn/Empirix survey — 68 percent reported that their companies never monitor contact center voice quality. Only 14 percent continuously monitor voice quality, while the remaining 17 percent periodically monitor on a daily, weekly or monthly basis.

This failure carries heavy risks. Globally, 79 percent of consumers replying to a Customer Experience Foundation survey said they experienced poor voice quality on contact center calls. Almost as many — 68 percent — said they will hang up if they experience poor voice quality. If they are calling about a new product or service, they will likely call a competing company instead.

Between misdirected efforts and testing rates like these, it's no wonder people aren't surprised when a major initiative like online healthcare enrollment goes off the rails, or customers calling a contact center get funneled down a blind alley in the IVR system. Customers who run into obstacles like those are on a fast track to becoming former customers.

Testing and performance monitoring can effectively stem those losses. Businesses that test and monitor customer service systems are better able to achieve maximum ROI on their customer service systems (CSS) by identifying and remediating problems quickly. An end-to-end monitoring solution provides organizations with deep visibility into complex customer service technology environments, enabling businesses to reduce the time it takes to understand the source of a problem — and fix it — before customers ever notice the glitch.

ABOUT Matthew Ainsworth

Matthew Ainsworth is Senior Vice President, Americas and Japan at Empirix. He has 15 years of experience in contact centers and unified communications solutions.

Related Links:

www.empirix.com

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...