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These days, there’s an acronym for everything
Explore our outsourcing glossary to find a definition for those pesky industry terms.
The outsourcing industry has entered 2024 during a period of significant growth and change, one that is being shaped by economic trends, technology advancements, and shifting customer expectations.
To understand the impact of the shifting business landscape, SupportNinja partnered with CMSWire and conducted a survey of 488 leaders to understand how these forces are shaping outsourcing decisions, vendor selection, and value measurement.
The results reveal five major storylines that are shaping the state of outsourcing. The full whitepaper will be released later this month, but in the meantime, here’s a sneak peek at five key insights.
There’s no industry that exists outside of the larger economic environment, and as it evolves, so too do the organizational priorities that receive the most focus. The current overall slowdown in the rate of global economic growth has made a value-conscious approach to operations a priority in most organizations.
In light of this, we were not surprised to learn that 78% of respondents said the current economic environment has at least some impact on their decision to outsource (47% reported a minor impact; 31% a major one).
Well-deployed outsourcing has long been a powerful tool for savvy organizations that want to maintain flexibility through changing times, but what might have been considered a fringe approach five years ago has become best practice today.
That evolution is present in the data: 63% of respondents reported an increase in their outsourcing budget over the past year. The range of options for outsourcing is bigger than ever, rising to meet the continuous growth in demand.
In fact, that connects directly with the next major trend we see in the data.
Consider these two outsourcing statistics side-by-side: 93% of our respondent organizations are at least somewhat satisfied with the level of service they receive from their outsourcing partners, but 63% are either actively considering or willing to consider a change to a new provider. What can we distill from these data points?
To us, they tell a clear story about what matters most to organizations, and that story is about value. Loyalty to a specific vendor seems to be less important to companies that utilize outsourcing than the quality of the solution that’s offered.
Our data about priorities ranks cost savings and service quality as nearly neck-and-neck. What does it all mean?
In 2024, companies are open to the possibility of something better.
Rapid innovation in the outsourcing industry means that when a contract is up, there may be an objectively better option out there, and value-conscious decision makers are willing to make the switch as often as is necessary to get the best balance of service and cost.
Finding new ways to scale fast is part of the tech industry’s DNA, so it should be no surprise that 65% of SaaS / tech companies say they have several outsourcing partners who fulfill critical business processes, as compared to 28% of respondents from other industries. For tech companies, outsourcing partners that are built directly into core functions have become the norm, because they grant access to both niche subject matter expertise and the ability to scale up teams quickly in response to rapid growth.
There’s also a strong affinity between the types of services most effectively outsourced today and the areas that tech companies often feel the most pressure to scale — things like customer and tech support, software development, and cybersecurity services. The high value placed on CX in most technology organizations that rely on continuously growing their MRR also means they’re more willing to invest in delivering the best support possible.
The best outsourcing vendors fit together with their tech clients seamlessly, like a jigsaw puzzle, enabling them to focus on growth without compromising their operations.
AI isn’t just a “nice to have” anymore — it’s a key part of the decision-making process when companies select an outsourcing partner. 73% of respondents deemed AI capabilities as either "moderately important" or "very important" when choosing an outsourcing partner. And expectations around how outsourcing partners leverage AI to create real value are rising quickly.
Basic AI capabilities aren’t always enough to differentiate from other providers, especially as AI continues to develop. Most respondents say their outsourcing vendor(s) have basic (41%) or advanced (37%) AI capabilities. This makes sense, because working with an AI-enabled partner is a step toward future-proofing a business or outsourced program. But what matters more and more is how well is AI actually used to deliver outcomes.
We see this trend as a mirror image of data we’ve gathered related to the biggest challenges in outsourcing. When comparing outsourcing options, beware of these common concerns:
This data challenges some assumptions about the outsourcing industry and reinforces others.
Companies continue to see the value of outsourcing, especially amid economic uncertainty.
Value, represented by the balance between cost and quality, is a top priority for many companies.
Most would be willing to switch outsourcing providers under the right circumstances, and many are actively looking to switch in pursuit of greater value.
The tech industry is ahead of the curve when it comes to leveraging outsourcing, but the same growth-focused values that have made tech such a good fit are becoming more commonplace across all industries.
AI is on the rise, no longer a “nice to have” buzzword for an outsourcing partnership, but rather a key differentiator — companies are increasingly scrutinizing how outsourcing providers use AI to create value.
At SupportNinja, we’re excited to be in a space that we believe the data shows is rapidly evolving to favor the type of service and experience we deliver to our clients.
Discourse around artificial intelligence (AI) spans industries and applications, and customer experience (CX) is no exception. Some say AI will take over CX jobs entirely, while others say it shouldn’t be used in customer interactions because it will never be able to fully replicate humans.
At SupportNinja, we have a more nuanced view: we firmly believe that human CX teams and AI both have their respective strengths and weaknesses, and that they’re better together.
Keeping a human in the loop is a great way to optimize human-AI collaboration. But what does a human-in-the-loop AI strategy look like, and how can it improve CX?
Table of Contents
Human in the loop (HITL) is based on the premise that even with current advancements in AI, humans still need to supervise machine learning (ML).
ML systems like generative AI don’t have beliefs, opinions, or knowledge beyond the extent of their datasets. Their entire “being” is dependent on processing factual information provided by humans. Because of that, humans are needed to train, test, and supervise how an AI is using the data.
By working together, humans and AI can confidently and efficiently complete a wide range of tasks, from identifying objects in images to responding to customer inquiries. Common applications for HITL include text generation, image labeling, audio transcription, content moderation, natural language processing (NLP), and more.
In HITL models, humans and AI work together. In some instances, humans monitor AI outputs, performing quality assurance (QA) and validations, and making corrections when needed. In other instances, humans perform the main actions with assistance from AI surfacing relevant information or parsing through data quickly to form the best response.
This layered system doesn’t just fill gaps in the AI’s knowledge and improve its accuracy over time — it also keeps humans from getting bogged down in repetitive tasks, so they have time to work on more complex problems.
Particularly in the context of CX, AI algorithms are generally built within a closed system. This means that the AI is trained using specifically selected, human-approved content and / or data, and doesn’t have access to any external materials.
Throughout the training process, humans provide feedback on the AI’s responses to ensure they meet the required standards. As the AI becomes more proficient, it can eventually perform its own QA, with humans stepping in to double-check responses as needed. This iterative process continuously trains the algorithm, enhancing its performance over time.
Humans outperform AI whenever it comes to complex problem-solving, empathy, and creativity, but AI enables scaling instantly. To provide the highest level of service, the best solution is to combine the power of humans and AI via HITL.
In CX, the HITL approach is particularly helpful for:
Implementing HITL is not without its challenges. It’s important that your CX team truly understands how to use AI to improve CX the right way.
Some concerns you might face include:
At SupportNinja, we leverage NinjaBot — our own AI solution for improving CX — to deliver fast, accurate responses, automate routine queries, and ensure our agents have all the information they need at their fingertips.
We also offer bespoke builds to align with your needs. Our team of HITL experts will work with you to ensure your AI tools integrate seamlessly into your tech stack and are set up using only the data you want to include.
Interested in learning more about how SupportNinja can empower your CX team with faster resolutions and smoother customer journeys? Get in touch with us.
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