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Organizations, big and small alike, draw strategies and build cultures that seek to fulfill customer requirements. Talent management is the preferred and exploited tool used to drive organizational health and customer satisfaction. However, what most companies overlook in the rush to gain a competitive edge and stay relevant in a digital age is their human capital. Interestingly an organization’s satisfied staff is likely to outperform the competition by 20%; so says a SnackNation article.

Employees who feel satisfied with their jobs, the parameters of job satisfaction still remain respectful treatment, compensation, benefits, and job security; are 12% more productive. Of course, the dearth of the right talent at the right place is making CEOs press organizational issues. Instead of only chasing new target markets, employers need to focus on retaining and nurturing their current talent pool.

 

In a dynamic business environment, talent can be turned into a competitive advantage for businesses if paired with strategic workforce planning, states a McKinsey article. By leveraging workforce planning, organizations validate their capability and capacity to drive home the planned business strategy.

 

Filling In The Gaps

According to an Accenture research, 61% of employees feel under-skilled to transition into a digital business. This shows that companies will have to invest the time and effort to train their staff better to allow for business strategies to be translated into business operations. Breaking away from the stringent silos and blurring the boundaries of responsibilities and making your workforce acquire multiple skills are the ways to overcome this hurdle. Think of the financial crisis that led banks to lay off their front-office jobs and gave rise to a need for regulatory staff.

 

Businesses need to provide agility to their teams for them to be able to transition from one role to another, without their business outcomes taking a hit.

 

Rewarding Change

Nine out of ten companies still depend upon the performance of an employee to evaluate their appraisals. According to a McKinsey article, companies such as Microsoft and GE are giving these dated methods of performance evaluation a miss as they lack a process that allows regular feedback and the necessary training.

Companies are implementing performance management software that helps profile separate individuals, instead of deciding according to the average employee performance. By using better data, some companies are severing the ties between performances and compensations entirely.

 

Changing leadership profiles

Strategic quality monitoring looks to revamp the entire organizations and not just the lower tiers of the structure. Leaders too need to rise to the occasion in order to drive the changes they envision. 

According to a McKinsey article, in order to coach people to be different, the coaching to has to undergo change. Leverage performance management software and include these practices that are likely to deliver the desired results –

  • Change the way in which feedback is provided
  • Back feedback by actual instances
  • Discuss scope of improvement

Implement a talent strategy that drives in-house growth to experience actual business efficiencies. As Accenture pointed out, people and not just technologies will drive growth in the age to come.

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Leveraging Natural Language Processing To Its Fullest

Twenty years ago or even ten, if we were seen talking to our laptops and smartphones, we would have gained the stare from quite a few people around us, not anymore. Devices these days especially smartphones come equipped with technology that allows us to voice our demands and generate the necessary results. So, asking Siri, Cortana, Alexa, or even Google Now the best route to get to work in a jiffy and make a coffee stop while at it is a cakewalk.


Most tech enthusiasts will say that with the use of natural language processing that the aforementioned technologies use, technology has come of age. But, has it? Well, to be honest not quite. Though, natural language processing has a very promising future, with a McKinsey report claiming that 80% of technology could be automated through the use of natural language processing; its current state presents an opportunity for vast improvement.  This is especially true, for call center software that relies on natural language processing.


It is a scientifically established fact that our voices are as unique, if not more, than our fingerprints. The number of spoken languages in the world keeps growing year-on-year, with the current number of spoken languages in the world is being capped at 6909. The most advanced technologies such as Google are investing more and more resources to enhance their natural language understanding capabilities.

With more and more customers relying on self-service and automation such as quality management, meeting customer expectations is the only edge that contact centers can have. There are three common mistakes that most businesses are making when relying on software that offers natural language processing. Let’s analyze what these mistakes are.

 

Three Missed Opportunities For Businesses

1. Treating language as data

Though data is the basis of analytics that can help businesses understand their customers better, when it comes to natural language processing, this is not the case. Each data string needs to be treated individually instead of clubbing it together. Like each voice is unique, each request is unique, so should its results. Computational statistics and pattern recognition is not the best approach when it comes to artificial intelligence that uses natural language understanding. Simply transforming language into data and not understanding the context is a flaw that will need to be addressed.

2. Not a set formula

The context of a language is integral to its meaning. Language cannot be compartmentalized to a fixed set of formula. What most artificial intelligence models are missing out on is understanding the context in which the search request is being made. With customers having little patience to voice their concerns and even little time to repeat themselves, contact center software has to have the ability to understand the context of the query to completely and correctly address it.

3. The rationale behind language

The ‘customer is king’ is still the ruling phrase of the contact center industry and will be for a long time to come. The AI model that a contact center relies on should be facilitated with the ability to rationale a request. Our voices represent a myriad of emotions and often we forget that we are talking to a machine instead to a fellow human. To start with, a query can be resolved better if factors such as the time and location of the person making the request can be taken into consideration. Building trust and ensuring that eventually, the customer becomes dependent on the assistant should be the long term goal of any business.

 

Being At Par With Customer Expectations

Though technology is advancing at a rapid pace, growing customer expectations are matching their speed. Natural language processing has to understand all the nuances that language presents. Artificial intelligence models will need to be empowered in a way so as to understand not just the words being spoken but also the emotions represented by them.

Businesses can either blame movies such as the Star Wars and Iron Man series or actually use them as benchmarks that they need to achieve and even surpass. Research and development with the adoption of every achievement are necessary when it comes to the evolution of technology. Results that are effective, accurate, and efficient in the eyes of the customer need to be commonly achieved by all businesses.

 

A Promising Future

Natural language processing has the power that will enable our customers to directly interact with machines the way they do with fellow humans. Machines will need to evolve training and skills that will help them cater to the request of a baby boomer and a millennial differently.

The interactions between machines and humans are only likely to strengthen efficiencies of all parties involved. A McKinsey report clearly spells out a bright future by saying, ‘rethink how workers engage with their jobs and how digital labor platforms can better connect individuals, teams, and projects’ through natural language processing.