During the initial years, outsourcing was only used for basic processes such as data entry and payroll processing. However, as connectivity expanded and the technological skills of BPO companies advanced, businesses started outsourcing more and more processes/services. Today, you can outsource many backend processes and financial/operation functions such as invoice management, accounts payable processing, survey reporting, and utility bill management to name a few.
This is most talked about business process outsourcing trend on the outsourcing horizon and yes, you’ve got it right! We are talking about cloud computing that will overhaul the traditional way of doing things.
Cloud computing is steadily digitizing businesses across the world. According to a recent study by Gartner, INC., the worldwide public cloud services market is expected to further expand by 17% in 2020 to $266.4 billion, up from $227.8 billion in 2019, is not it huge
A cloud is basically an interconnected network of internet servers that store, analyze, and process data in the virtual space. Cloud computing, then refers to a network that is used for the delivery of software services and data.
Cloud computing provides stability, security, and greater flexibility in outsourcing processes. A cloud-based platform works as a great collaborative platform for companies with locations in different countries as it allows data visualization that provides businesses with real-time data and information. It is further estimated that the next generation of business process outsourcing solutions will be all cloud-enhanced solutions
Cloud computing and business process outsourcing has evolved beyond an imaginable scale over the past decade. The Cloud, which was considered a mere concept not so long ago, is making waves in the industry today. Small businesses are the ones who have benefited the most, as they now have access to larger computing resources and high-performance infrastructure, which they could never dare to afford before. Since the high demand for the ‘cloud’ has led to numerous innovations, organizations, no matter what scale, are prioritizing to acquire superior cloud-based services and computing resources for increasing business process speed and efficiency.
Finding the right strategic fit has become an intimidating task, especially for entrepreneurial start-up ventures. Small-scale businesses usually lack market knowledge, skills, proper information and experience, which restricts them in finding a suitable computing service provider. As a rule of thumb, the better the service, the higher the expectations, the higher the results. This means that acquiring the right service is absolutely necessary if you expect to achieve significant results in terms of improved business processes and value chain engagement.
Attention! The fears were true; artificial intelligence is taking over the world and outsourcing is next!
Scared you pretty good, didn’t we? Well, jokes aside, it is a fact that artificial intelligence or AI is becoming an increasingly vital feature in every industry and the outsourcing business is no different.
AI is being increasingly employed to automate several data entry and processing functions including accounts payable processing, invoice management, and utility bill processing.
AI streamlines all these processes by identifying and segregating data and even automatically filling in missing details. As an example, let’s say you need to process a large number of invoices in every format ranging from physical documents to email attachments and digital invoices. Once the document conversion process is over, AI can automatically detect and fill in any missing information to complete the invoice document and increase the chances of swift approval and payment.
The applications of AI in business process outsourcing are endless and will revolutionize business process outsourcing solutions in the years to come.
Artificial Intelligence is fast invading various industries, so it is dictating upon business process outsourcing companies. To put it in a nutshell, Artificial Intelligence is transforming industries by researching in Big data and Cloud computing. As such, BPO is the one that is most affected as it is intimately related to both the former and the later. Moreover, it acts as an epicenter for numerous kinds of business process outsourcing companies. The centrality of the BPO industry also paves the way for meeting the growing customer expectations. Therefore, it would not be wrong to point out that a thriving BPO industry would flourish with AI intervention.
In the post-globalized world, businesses are eager to pile up their revenues. To make it happen, they want to cut down on unnecessary costs and further the scale of their operations especially in the untapped markets where favorable business conditions are present. Hence, they desire the outsourcing units to leverage the power of AI so that not only the subsidiary company is benefited but the parent company also becomes a partner in the road of rapid monetary progress.
BPO companies worldwide are now fast responding to this changing business climate. Using Big data and cloud computing they are mining large sets of data and generating a comprehensive graphical analysis from the raw and randomly stacked up data sets. These analytical data sets are not only useful for the scaling up of business operations in general but also tracking up customer satisfaction by review monitoring in particular.
Hence, when we are talking about the superposition principle in the case of AI and BPO, we are referring to the mutual benefits one can bring for the other. Put in simpler words, AI can make the BPO industry thrive in the form of revolutionizing the processes liked to the chatbot. On the other hand, the BPO industry can benefit AI by acting as a hotbed of research and a new genre for researchers interested in this field.
Outsourcing has moved beyond simple, repetitive, and basic tasks. Today, businesses are looking for smart solutions to their everyday problems that involve the perfect combination of human innovation, automated efficiency, and technical accuracy, i.e. people, process, and technology.
Outsourcing firms have risen splendidly to this challenge with a range of customized technological solutions. From custom-built automation bots to cloud-based collaboration platforms, the process of outsourcing has become a smart sourcing one.
By Reinvention and innovation, BPO doesn’t just hand you the same list of services with the same processing solution. BPO’s these days studies your business model and your current processes to identify the cogs in the wheel and then optimizes each step to create a flawless workflow with a customized solution that is tailored to your company’s specific needs.
BPO teams comprise college-educated, well-experienced members with analytical minds, and strong problem-solving skills. These skills translate into successful business solutions with the efficient employment of advanced automation and machine learning technologies.
BPO providers should look to build Omni channels as true “human services companies.” They have the data in place to do great analytics, but can’t always manage it from a technical and operational point of view.
One key issue is that improvements tend to be small, isolated, and almost exclusively under the umbrella of the English language. In a truly global market, BPO providers are missing out on key improvements that have the power to ensure clients maintain innovative practices and high-profit margins.
When BPO providers can nail areas like customer service, the benefits of new technology like AI and automation can be unlocked and services will be more affordable, which is of course the bottom line for customers.
Ultimately it all comes down to disrupting before you’re disrupted. It’s time for BPO providers to grab the opportunities to adapt, innovate, and reinvent successfully for the future.
Robotic process automation or RPA refers to the application of specialized computer programs to automate secondary or repetitive tasks such as data entry or mining for higher accuracy and reduced operating costs
However, for a complete digital solution, you need a blended approach that uses artificial intelligence and machine learning with the right human intervention and supervision to create successful solutions.
The first step in the implementation of robotic process automation is a thorough analysis of the existing business process and the creation of an optimized solution to eliminate all errors. Once the new process has been defined, special software robots, i.e., bots are coded and assigned to the existing workstream wherein they start performing tasks with greater speed, accuracy, and precision.
The purpose of automation goes beyond just reducing costs, bots speed up your processing time drastically, while also delivering high-quality consistent data with greater accuracy.
The option of customized coding elevates robotic process automation over enterprise automation solutions as RPA offers more than just automation, it gives you a super-efficient work-stream, manages your workload effectively, and frees up your time and office resources so that you can focus on developing your core competencies and scaling your business.
Robotic process automation is set to revolutionize the outsourcing industry by transforming raw, unstructured data into measurable performance. Let’s keep a lookout for it, shall we?
Suggested Reading: Customer Service happens when the experience breaks down – Here’s How? AI for Contact Centers – What you should know?
Ironically, one of the biggest fears about outsourcing is also one of the biggest myths about outsourcing.
Cyberattacks are on the rise; as per RiskBased Security, data breaches exposed approx. 4.1 billion records in the first half of 2019 alone.
According to Fundera, around 43% of cyber attacks target small businesses. Statistics further indicate that healthcare, retail, and manufacturing are the most targeted industries for cyberattacks. This means that providing high-grade data security will one of the major business process outsourcing trends in 2020.
For any company, one of the primary outsourcing concerns while outsourcing data processing services is the fear of data theft and the negative impact it may have on their business. Their fear is entirely justifiable and that’s why outsourcing companies are paying greater attention to data security measures and protocols.
BPO should recognize that with data security, comes great responsibility.
They must be extremely particular about our clients’ data security and thus they should have their VPNs, SSLs, encryption protocols, HIPAA, PCI, GDPR compliances, and security protocols in place.
In addition to security compliances and protocols, they should be extremely careful about who they expose your data to. Access to sensitive data is strictly on a need-to-know basis, and they must have measures in place that ensure that your data cannot be moved, edited, or seen by all.
They should also take special care to hold sensitive data only for a strict time limit, once they are done with the data and have successfully delivered it, it should be disposed of it after the specified date. BPO clients trust them with sensitive data because they know that they can. They should also regularly review and update their security measures to manage the client’s documents and data entry securely.
There are some more trends going on for BPO companies, we will keep discussing them in our coming blogs, keep reading, stay tuned and more importantly fine-tuned
Sources: Gartner Forecasts Worldwide Public Cloud Revenue to Grow 17% in 2020
Customer experience and contact centers, in particular, are great starting points to implement artificial intelligence (AI) solutions since they are a large source of customer information, generating enormous quantities of data that is impossible to process manually. Here’s how AI can be used in contact centers:
Your customers may contact you for a multitude of reasons. Some of these reasons are fairly straightforward, others are intricate, yet, rarely are they entirely novel.
With the immense data that you are collecting with every recorded phone call, chat interaction, and email, you have a strategic asset that can be used to train machine learning models to understand customer intent within conversations.
Once you understand true customer motivations, you can then use AI to optimize interactions through:
Flagging interactions for fraud and compliance risk
Customer effort is one of the leading indicators of loyalty. Analyzing customer effort can guide companies in identifying emerging issues before they explode into major issues.
Traditionally, the effort has been quantified through structured questions on a survey. However, AI and machine learning techniques, combined with text analytics, can aid in evaluating the level of effort expressed in any piece of unstructured customer feedback.
AI can do this by interpreting word choice and sentence structure, as you can quickly understand which aspects of the customer experience cause friction in any feedback source – not just in surveys.
Before you deploy AI, it is worth considering that one of the biggest risk factors in any IT implementation, system upgrade, or system change is the human users of that system.
By failing to communicate in an open, honest, transparent way how this technology is going to benefit them, you will meet resistance.
If you simply say, we are rolling out this new robotic-led approach on Monday, your employees will inevitably be negative towards the technology and may even actively sabotage it.
Instead, you need to get people involved in the process. Ensure they can test out the technology in a safe environment and make sure they are comfortable with it before you even start rolling the technology out.
Any AI application will only ever be a good as the knowledge at its disposal. You need to ensure that when a question is answered in the contact center, that knowledge is captured and delivered into the knowledge management system (KMS), so that customers, bots, and advisors can feed off it.
After all, how can AI be used to make decisions when it does not actually know anything? It can learn but it needs relevant data to do that.
This is why it is so important to have processes and procedures in place that enable you to feed accurate data and intelligence into the KMS.
Many businesses are too reliant on their employees as a source of knowledge and therefore run the risk that if people leave the business, they take the knowledge and understanding that they have gained with them.
Any strategy that uses AI and machine learning should be considered within a broader customer experience AI strategy that considers how data will be leveraged across both the customer and employee journeys.
There are many opportunities to apply AI and machine learning across the customer engagement process.
For example, knowing the right moment to proactively engage with customers online, routing to the best agent based on the desired business outcome, and assisting them to accurately handle inquiries – AI and machine learning can help drive all of that.
However, AI applies to more than just customer journeys. It can also help identify why specific agents are better than others at certain contact or customer types, increase the speed and accuracy of workforce planning and scheduling and automate task completion post-contact.
SUGGESTED READINGS: Customer Service happens when the experience breaks down – Here’s How? TOP 6 Reasons to Invest More in Customer Experience