Role of Machine Learning on Business Process Outsourcing

Machine learning refers to programmed detection or recognition of a significant pattern in data. In the past few years, it has become a popular tool in almost any task that requires extraction of information from sets of extensive data. In today’s world, we are surrounded by a Machine learning technology like cars are equipped with accident prevention system that is assembled using machine learning technology, digital cameras learn to detect faces, smartphone application learns to recognize voice commands and so on. Anti-spam software’s filter emails and credit card transactions are secured by software that determines how to detect fraud or scam.

Advantages and Risk of BPO

Assigning function of business to a third party provider is known as Business Process Outsource (BPO). The services include in BPO are accounting, customer call center relations, data entry, accounting, etc. This is also known as information technology enabled services (ITES). BPO services enhanced the speed and efficiency of the business process; expenditures are not required, not required for an organization to invest additional business assets and to improve value chain engagement. As far as advantages, risks include to the BPO are underestimated running costs, dependence on the service provider, a breach in data privacy, etc.

Impact of Machine Learning on BPO Industry

Machine learning or automation is expected to sweep across industries, and the global BPO sector is also under its effects with the rise in machine learning, artificial intelligence, and automated services. The emergence of extensive data, machine learning cloud computing and artificial intelligence are optimizing and spreading business process at a rapid pace. By controlling technology, firms and companies can gain a competitive edge and plan for the future. Also, it has improved efficiency in the BPO industry as well as leading to an immense productivity workforce growing at a dramatic rate. All of this offering BPO’s a chance to upgrade their processes at a low cost. By incorporating machine learning tools, BPO’s can differentiate themselves by offering automation services.

How BPO Industry badly affecting by the Machine Learning

The significant side effect of adopting machine learning and automation tools is the chance of going declines in the BPO industry workforce. The low skill routine jobs are getting increasingly impacted, and it is expected that it will affect more in the upcoming years. Moreover, machine learning destroys many low-skilled jobs; the main focus will shift to higher skilled and more professional jobs. As this technology becomes older, ubiquitous jobs related to BPO will be particularly at risk. Currently, machine learning still developing and its infancy complements existing human skills in the BPO industry, allowing workers to become more productive and efficient and less in number while completing the same amount of work. As technology is developing continuously and its implementation expands, it is expecting that more than one million jobs are at risk in developed countries.

How Machine Learning Can Optimize BPO

Most of the service companies spend a lot of their expenses on customer support. Management of these organizations seeks to reduce this cost without compromising on standards and quality. Machine Learning plays a significant role in the BPO arena. The technology automates the process of identifying problems and recommending fixes which boost problem resolution, reduce expenses, and improve the satisfaction of customers. Recently, Machine Learning systems use pattern algorithms and recognition to learn from and make predictions on data. In the past few years, Machine learning solutions have surpassed high concept to become a near-term reality across BPO, and other multiple industries.

Here some of the critical things BPO providers must do to survive better in the future.

  1. Invest in other areas of Business

Spend and empower in that area of business which helps differentiate your organization from others in terms of skill, innovation, impact, and speed.

  1. Lead the way

Build deep technology capabilities and show your organization can deliver technology-led innovation on a current and ongoing basis which helps to overcome this technology.

  1. Go Deep

To stay in the game work and effort on acquiring a deep awareness of specific industry domains, so your customers know you completely understand their business and worth in their business transformation.

  1. Focus on skill and proficiency

Appoint re-skilled and train your employees so the workforce can move up the value chain to a position such as a mathematician, data scientist, an actuary, so your company can offer existing and potential clients high order capabilities.

 

 

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