2019

How Emerging Technologies are Redefining the IT Service Provider Landscape

Technology is changing the way organizations do business across all major industries. New technologies (and new applications of existing technologies) are being developed all the time, and businesses are naturally looking for ways to incorporate emerging technologies into their operations.

As IT service providers, emerging technologies are constantly changing the way we operate and improving the level of service we’re able to offer customers. At a minimum, new technologies are:

  • Enabling new business models and revenue streams
  • Enhancing the customer journey
  • Improving the speed and quality of customer service
  • Facilitating huge efficiency gains in operational processes

With so many exciting new technologies coming to market, it can be hard for businesses to keep up. For example:

Robotic Process Automation (RPA) and Intelligent Automation can be used to automate business processes that are repetitive or time-consuming, e.g. an account opening process.

The Internet of Things (IoT) and Operational Technology (OT) help organizations collect and analyze data about critical systems and processes at an unprecedented scale.

Smart Analytics solutions help businesses organize massive quantities of operational data and use it to inform process improvements.

Artificial Intelligence (AI) can help improve the responsiveness and quality of customer service via automated solutions like chatbots.

Blockchain / Digital Ledger Technology (DLT) enables new business models across all industries, particularly those that rely on secure transfer of digital rights such as licensing of art, music, and software.

Before the end of 2019, we will definitely see even more newer technologies in development that will enable benefits to efficiency and customer experience.

Technology as an Enabler

As beneficial as technology undoubtedly is, it’s not the end result. Nobody adopts a new technology purely for the sake of novelty — it has to provide genuine business value.

At the same time, new technological advances are available to everyone. IT service providers can’t claim new technologies as a differentiator, because for the most part everybody in the marketplace has access to the same technological opportunities.

After all, we don’t talk about the competitive advantages of the telephone. Why? Because every business has them. The important thing is how businesses use the telephone to promote business objectives.

The situation is exactly the same with new technologies. It’s not about “what” technology you have access to, it’s about “how” you use that technology to produce the desired outcome.

CSS Corp starts reaping benefit of revamp kicked off 2 years ago

A complete organisational revamp initiated two years ago has helped the city-based CSS Corp, a technology company owned by Swiss PE firm Partners Group, to improve its performance. In the last one year, the quarterly run-rate has improved by about 25 per cent, said the company’s CEO, Manish Tandon.

“We are seeing results of the revamp with quarterly run-rate of about $40 million. Every quarter, we added 4-5 per cent sequentially. The growth was not sudden and attributed to one or two clients but was gradual over the last few quarters,” said Tandon who joined CSS three years ago after nearly 20 years at Infosys.

The company, which has around 4,000 employees in Chennai out of a total global workforce of around 7,100, has been witnessing 4-5 per cent revenue increase quarter-on-quarter, he told BusinessLine.

While growth for CSS was flat, Tandon said he had to rejuvenate the entire organisation and reposition the company. “Today, we are not an IT or BPO company but a new age IT service company. Give us any problem, we will lead with technology and people rather than the other way around. This was a big change for the company,” he said.

The entire sales and marketing organisation was revamped, and employee culture, mindset and training had to be worked on with technology changes. New revenue model was based on outcome. Most of the clients are now on annuity rather than time and material. This helps in a sustainable business. CSS mainly focuses on sectors like technology, media and telecom apart from digital business, he said.

Open to accquisition
Tandon said the company was open to acquisition to help growth, and is willing to shell out $20 million to $100 million. “We will look at a company that is into product development or testing. We have enough cash, and are fairly profitable. We are backed by the Partners Group, and if a need comes to inject equity, it can always be done,” he said.

For the year ending March 31, 2020, the company is likely to report revenue of nearly $160 million as against $139 million in the last year. “Organically, we will reach around $200 million in a couple of years. However, if an acquisition is done, achieving that will be much quicker,” he said.

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Upskilling Vs Onboarding: What Do Companies Prefer For Data Science Roles?

With technologies seeing newer dawn in Indian businesses, more companies are looking to adopt disruptive technologies such as analytics, data science, artificial intelligence in their working. To enable this, companies will have to look for a workforce that is skilled enough to adopt these tech innovations and bring newer competencies in the market.

This is where the need to reskill or replace comes into the picture. We have seen in the past how companies such as Cognizant and many other tech companies have laid off employees who were not able to keep up with the changing technologies and failed to upskill themselves in this highly tech-driven time. The world is changing at a fast pace and companies need to alter the ways they work by incorporating technology in their processes.

We have published numerous studies and reports in the past which suggests that there are a lot of job openings in data science and AI field that currently needs to be filled up, which clearly indicates towards unavailability of talent that can be addressed either by reskilling or making new hirings.

But what do companies usually prefer — reskilling or hiring? Let us find out.

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Amplify Agents To Transform CX In Customer Service

Customer Support Representatives (CSR’s) are the bridge between customers and the company. When faced with product or service-related issues, customers instinctively reach out to the customer service department. In an industry report by Accenture, it was found that 89 per cent of customers get frustrated because they need to repeat their issues to multiple representatives.

In a customer service environment, there is a tendency to get carried away by modern technologies like AI or advanced analytics and set up complex systems to deliver “next-gen” support for customers. However, problems arise because agents are not able to leverage these technologies properly to come up with timely, meaningful solutions.

To find a quick resolution, CSR’s require comprehensive and contextual information about the customer and the issue. Organizations must understand that most customers today can use self-service tools to resolve basic issues, subsequently increasing their expectations for specialized agent support. While chatbots have caused a lot of buzz over the last couple of years, the industry has quickly realized that chatbot technology is not mature enough to handle non-standardized customer issues. The solution, therefore, lies in a holistic agent empowerment and amplification framework that enables agents to service customers seamlessly and effectively.

How Agent Amplification can drive customer experience

A customer service ecosystem consists of primarily 3 components:

  • Consumer experience
  • Technology-driven process automation
  • Agent experience

Out of the three, the agent experience is a crucial aspect, as it is the X-factor that drives the other two. As per the Aberdeen Group, companies who work to actively engage employees/agents have customer loyalty rates 233 per cent higher than those who don’t.

Therefore, an efficient contact center ecosystem should incorporate an agent-centric model that integrates technology seamlessly into the existing customer service ecology, while maintaining synergy with agent experience.

A holistic customer experience solution can be the answer
A digitally led customer experience management ecosystem can simplify complex customer service ecosystems. It can provide solutions that shift from reactive to pre-emptive engagement models, enabling agents to provide consistent support along the entire consumer journey. An effective support framework, depending upon whether it is in a B2C or B2B context, could have the following components:

A) Smart Case Routing
The genesis of most problems related to the call center environment, stem from the inability to map the right agent to the right customer issue. This creates frustration for customers as they are thrown from one agent to the other. However, with intelligent automation and smart case routing analytics, organizations can drive predictability and agility in customer service operations. Issue classification, routing and management is automated, so the agent with the right skill set and micro-attributes is holistically mapped to the right customer. This simplifies and reduces issue resolution time.

CSS Corp to expand facilities in India, add 1,000 positions over one year

Tech firm CSS Corp is looking at expanding its facilities in India, adding about 1,000 positions over the next year.

The company, which offers analytics, automation and cloud consulting services, currently has about 4,500 people in India across offices in Noida, Bengaluru, Chennai and Hyderabad.

“We have seen a strong growth in our business, we have grown 25 percent from a year back. We are looking at further strengthening our position here and expect to add about 1,000 people over the next one year,” CSS Corp CEO Manish Tandon told PTI.

In Noida, CSS Corp has about 100 people, which is expected to be doubled. Other centres like Hyderabad and Bengaluru would also see hiring taking place.

Globally, the company has about 7,000 people. It has centres in the US (Utah, Dallas, Milpitas and New Jersey), Poland, Mauritius, Costa Rica, China and the Philippines. Tandon said he expects the strong pace of growth to continue for the company.

“We expect to continue this growth momentum. There is a huge demand for automation and analytics solutions across sectors… Our digital-focused strategy and innovative network solutions have helped us to offer flexible and value-based services to our clientele, and fast-track their network transformation journeys,” he pointed out.

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HR voices: Analytics, AI and social will transform employee experience in 2019

The relationship between human resources (HR) and IT should focus on creating efficient processes for employees, say HR heads in India. 

While there have been fears of automation impacting traditional jobs, emerging technologies are also paving way for new job roles. In the fast-changing world of technology, it is not just the employees who need to be prepared.

The companies also need to learn and adapt to innovation so they can find and hire the most deserving candidates for any given job. To achieve this, the human resources department will need to work along with the IT team to develop strategies that leverage newer technologies.

Innovation to optimize HR processes

HR heads say the relationship between HR and IT should focus on creating efficient processes for employees. While HR processes may struggle to stay on top of technology, with collaboration and support from IT, HR can overcome those challenges. The collaboration will help develop best practices around technology for the entire organization.

“The HR function of businesses should leverage technological, analytical and intuitive tools to become more efficient in spotting and hiring the right resources. Innovative tools will continue to help employees in their up-skilling or reskilling initiatives in 2019,” mentions Visweswara Rao, senior vice president and chief HR officer, CSS Corp.

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Real digital transformation starts with staff for India Inc

Bengaluru/Kolkata: Employees are now front and centre when it comes to championing India Inc.’s digital transformation agenda. With technology increasingly becoming a core part of business, employees across companies such as Accenture, KPMG, ITC Infotech and RPG Group are playing a crucial role in steering this change in mind set.

Last year, RPG Group rolled out ‘digital academy,’ a programme to increase the tech quotient across its businesses. Company leaders have taken the course  and about 150 employees will participate in sessions and projects focused on analytics and smart products.

ITC Infotech started workshops to give employees practical experience in managing new technology. At ThoughtWorks, the focus is on employee communities who concentrate on technological trends and explore the intricacies of platforms powered by blockchain, machine learning and Internet of Things.

The emphasis is on ensuring the ability to constantly learn new technologies and solutions, HR experts said.

“Each month, we identify key focus areas and organise trainings on data management, develop related frameworks as well as cloud-based application development and environment management,” said Sanjay Kumar, VP of capability building and knowledge management at ITC Infotech.

Employees at CSS Corp get to test emerging technologies and develop new solutions at the company’s innovation labs. ThoughtWorks, a software company, operates a platform called ‘Insights’ that employees can tap for practical opinions and updates on aspects of digital transformation, product thinking and experience design.

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The mechanics of leveraging AI and ML to solve problems

Take a look around. Cars are driving themselves. Automation is everywhere. Even drones have become household toys.

These are clear signs that artificial intelligence (AI) and machine learning (ML) have become democratized.

As powerful as they are, using AI and ML to solve business problems is not a simple process. Many project teams do not fully understand how to work with these technologies.

Algorithm libraries are the smart choice 

There are more than 50 common ML algorithms, all with different applications.  It can be tempting for AI/ML adopters to develop their own in-house solutions. However, building new ML algorithms can be a huge challenge. Significant investments are required and it is difficult to compete with established players such as Amazon (AWS), Microsoft (Azure), and Google. A better alternative is to hire engineers who can work with existing ML libraries built into major cloud platforms.

Off-the-shelf ML algorithms are best suited for evolving markets that need rapid access to working solutions. Such pre-existing, bug-free algorithms are an important advantage as they speed up the development and deployment process.

Not all business problems can be solved using algorithm libraries. More complex problems will still need to be built from scratch by experienced R&D experts. This type of work requires a lot of creativity and human ingenuity.

Solving problems with AI and ML

AI/ML projects are often hindered by lack of understanding of the underlying dynamics, dependencies and data required to solve a problem.

Below are five steps engineers must take to successfully build AI and ML solutions.

1. Understand the problem: Before any development, engineers must have a thorough understanding of the problem. The team must identify the dynamics associated with the problem, a list of internal and external dependencies, and data attributes. The methods to achieve this include the ‘5 whys’, mind mapping, online analysis and domain SME discussion.

2. Understand data points: A thorough understanding of existing data is essential as engineers must be able to identify features that could influence the AI/ML model. Common tools and methods to help with this stage include data analysis, statistical methods, data interpolation and extrapolation, feature extraction methods and research.

3. Determine whether AI/ML is appropriate

This is perhaps the most important step in any project development to determine which technologies should be used to solve the problem. Many development teams opt to use AI and ML even when they are not the ideal choice.

Some good questions to ask before you start:

  • Can the problem be solved with rule-based-analysis?
  • Is the output strongly influenced by less than 1 to 4 metrics?
  • Are there any existing functions that can facilitate the desired output?
  • Is the problem computationally difficult but has a fixed outcome?
  • Is it simple to group the data or series of inputs?

If the answer to any of the questions above is a strong yes, the project may not be a good fit for AI and ML.

4. Spend time on feature engineering 

One of the most challenging tasks is establishing effective features that are dependable for ML classification. Based on the nature of a problem, features must be extracted from transformation. This requires significant expertise and application of data engineering concepts.

5. Apply ML algorithms contextually  

Selecting the correct ML algorithm for a problem requires analyzing and using KPIs such as accuracy, precision, recall, MCC (Matthews correlation coefficient), and F scores. There is no ‘minimum data’ formula, as it is highly driven by the complexity of the problem.

Selecting the right ML algorithm

As with the steps above, it is important to ensure the correct ML algorithm is selected for the success of the entire project. Once the problem, data attributes, and project objectives are thoroughly understood, an algorithm should be chosen.

Broadly, algorithms fall into four categories:

  • Supervised learning
  • Semi-supervised learning
  • Unsupervised learning
  • Reinforcement learning

When datasets are clear and consistent, supervised learning algorithms are a good choice. But, when data is complex or unclear, unsupervised learning algorithms are more appropriate.

It is important to remember that contextual application of ML algorithms is essential to project success.  Your choice of algorithm must be made objectively. Just because you have resources who specialize in an algorithm does not mean it is the best choice.

CSS Corp Addresses Commercial Challenges of Cognitive CX Transformation

One of the main challenges facing front-office automation projects is the adoption of commercial terms protecting the interests of both clients and CX services providers. In an industry dominated by traditional per FTE and per hour/minute pricing, to be successful, end-to-end digital transformation requires significant initial investments, new KPIs, a stake from the vendor, and a longer project horizon.

The cannibalization dilemma

Cost saving is a direct benefit of front-office automation, generated by deflecting traffic from live agents to self-service and improving productivity to enable reduction in required FTEs. Effective cognitive bots deployed in key customer journey stages or back-office workflow can eliminate the need for human intervention and decrease the volume handled, thus reducing vendors’ revenues.

So far, CX services providers have responded by absorbing the financial impact, hoping to protect their position from competitors, gain additional share of the client’s business down the road, or use it as a lever in the next renewal negotiation. However, this approach cannot be sustainable because cognitive CX is not an end solution but a continuous journey addressing customers’ increasing service expectations and growing acceptance of bots. Even in narrow-scope deployments, traditional performance metrics such as AHT lose their relevance when more complex and challenging interactions end up with human support.

Footing the robot bill

Clients commonly do not want to invest heavily upfront, especially when they do not know what outcomes to expect from CX automation. CSS Corp addresses this pain point with an upfront contract commitment to achieve cost out while backloading most of the investment and blending it in the rate. The company’s commitment stems from its significant experience with the specific client and vertical and from its cognitive IP. For example, its first large-scale CX automation project was with an existing home networking client, which CSS Corp has supported since 2005 and is now the sole supplier. The digital transformation with the client evolved from several joint RPA implementations and simplifications such as screen scraping in the past to 22% TCO reduction through automation. The vendor’s domain experience in home networking with multiple clients, accumulated customer data, and digital assets integration practice gives it confidence to accept the risk.

In another example, for a U.S. VoIP service provider, CSS Corp manages sales, customer care, technical support, and retention. It is responsible for increasing sales, reaching retention numbers, maintaining credit per line, and achieving customer satisfaction levels. CSS Corp charges on a ‘cents per active line per month’ basis. The provider owns the automation and tools but has agreed on a penalty matrix for FCR, CSAT, retention rates, etc.

Contracting with ‘unknowns’

In cases where the domain is less mature for the provider, or the client RFP does not give access to internal data, cases, or existing infrastructure, CSS Corp utilizes reference information and demands a clear view of the internal development roadmap. An example is a hardware storage manufacturer which CSS Corp supports in APAC, U.S., India, and Europe with 200 employees. The contract is based on flat per hour pricing with targets to reduce the headcount by year, 1, 2, and 3 with an increasing rate per hour.

A vital element here is the realistic assessment of meaningful results to justify the cost to the client. When these results do not bring savings, the company contracts against customer satisfaction improvements delivered through the CX automation. CSS Corp’s best practice is to employ a conservative calculation in generic cases. For example, it underwrites only 14-16% TCO over three years when the level of automation is limited by the product, languages, or degree of customer base exposure to chatbots.

Workforce model for bot-human support

With both established and prospective clients, CSS Corp applies a workforce model based on the number of eliminated contacts, volume of self-service, percentage handled by a chatbot or voice bot, and efficiency improvement for technology augmented live agents. It also includes the usual quality and SLA terms. If the automation benefits do not materialize, the provider accepts the need to overstaff. If the benefits exceed targets, CSS Corp gains from the additional savings. For ROI calculation to come through, the contract duration typically needs to be three or more years. Also, to win the buy-in from the organization, CSS Corp shares its calculations and research data, conducts onsite consultations, and organizes workshops.

The proper due diligence from CSS Corp requires sign-off on the client product release and IT update schedule. For these requirements it works with marketing, product development, IT, and operations in addition to customer service departments. The client’s IT approval is crucial to ensure an alignment of deployment dependencies and timelines. For example, in one instance, the client’s delayed telephony upgrade pushed the introduction of parts of the automation components back by six months. Here, the outcome-based pricing kicked in only after the infrastructure upgrade was complete.

Co-innovation with pricing

CX automation programs require investments from the client and vendor, and advanced pricing models are a must to ensure ‘skin in the game’ from both sides. True co-innovation entails a more flexible commercial approach which translates into a next-level CX services partnership. One of the main challenges facing front-office automation projects is the adoption of commercial terms protecting the interests of both clients and CX services providers. In an industry dominated by traditional per FTE and per hour/minute pricing, to be successful, end-to-end digital transformation requires significant initial investments, new KPIs, a stake from the vendor, and a longer project horizon.

The cannibalization dilemma

Cost saving is a direct benefit of front-office automation, generated by deflecting traffic from live agents to self-service and improving productivity to enable reduction in required FTEs. Effective cognitive bots deployed in key customer journey stages or back-office workflow can eliminate the need for human intervention and decrease the volume handled, thus reducing vendors’ revenues.

So far, CX services providers have responded by absorbing the financial impact, hoping to protect their position from competitors, gain additional share of the client’s business down the road, or use it as a lever in the next renewal negotiation. However, this approach cannot be sustainable because cognitive CX is not an end solution but a continuous journey addressing customers’ increasing service expectations and growing acceptance of bots. Even in narrow-scope deployments, traditional performance metrics such as AHT lose their relevance when more complex and challenging interactions end up with human support.

Footing the robot bill

Clients commonly do not want to invest heavily upfront, especially when they do not know what outcomes to expect from CX automation. CSS Corp addresses this pain point with an upfront contract commitment to achieve cost out while backloading most of the investment and blending it in the rate. The company’s commitment stems from its significant experience with the specific client and vertical and from its cognitive IP. For example, its first large-scale CX automation project was with an existing home networking client, which CSS Corp has supported since 2005 and is now the sole supplier. The digital transformation with the client evolved from several joint RPA implementations and simplifications such as screen scraping in the past to 22% TCO reduction through automation. The vendor’s domain experience in home networking with multiple clients, accumulated customer data, and digital assets integration practice gives it confidence to accept the risk.

In another example, for a U.S. VoIP service provider, CSS Corp manages sales, customer care, technical support, and retention. It is responsible for increasing sales, reaching retention numbers, maintaining credit per line, and achieving customer satisfaction levels. CSS Corp charges on a ‘cents per active line per month’ basis. The provider owns the automation and tools but has agreed on a penalty matrix for FCR, CSAT, retention rates, etc.

Contracting with ‘unknowns’

In cases where the domain is less mature for the provider, or the client RFP does not give access to internal data, cases, or existing infrastructure, CSS Corp utilizes reference information and demands a clear view of the internal development roadmap. An example is a hardware storage manufacturer which CSS Corp supports in APAC, U.S., India, and Europe with 200 employees. The contract is based on flat per hour pricing with targets to reduce the headcount by year, 1, 2, and 3 with an increasing rate per hour.

A vital element here is the realistic assessment of meaningful results to justify the cost to the client. When these results do not bring savings, the company contracts against customer satisfaction improvements delivered through the CX automation. CSS Corp’s best practice is to employ a conservative calculation in generic cases. For example, it underwrites only 14-16% TCO over three years when the level of automation is limited by the product, languages, or degree of customer base exposure to chatbots.

Workforce model for bot-human support

With both established and prospective clients, CSS Corp applies a workforce model based on the number of eliminated contacts, volume of self-service, percentage handled by a chatbot or voice bot, and efficiency improvement for technology augmented live agents. It also includes the usual quality and SLA terms. If the automation benefits do not materialize, the provider accepts the need to overstaff. If the benefits exceed targets, CSS Corp gains from the additional savings. For ROI calculation to come through, the contract duration typically needs to be three or more years. Also, to win the buy-in from the organization, CSS Corp shares its calculations and research data, conducts onsite consultations, and organizes workshops.

The proper due diligence from CSS Corp requires sign-off on the client product release and IT update schedule. For these requirements it works with marketing, product development, IT, and operations in addition to customer service departments. The client’s IT approval is crucial to ensure an alignment of deployment dependencies and timelines. For example, in one instance, the client’s delayed telephony upgrade pushed the introduction of parts of the automation components back by six months. Here, the outcome-based pricing kicked in only after the infrastructure upgrade was complete.

Co-innovation with pricing

CX automation programs require investments from the client and vendor, and advanced pricing models are a must to ensure ‘skin in the game’ from both sides. True co-innovation entails a more flexible commercial approach which translates into a next-level CX services partnership.
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