6 digital transformation trends for 2019

Business transformation will pick up speed in 2019 as enterprises make critical decisions about their digital strategy. Our six digital trends will guide those decisions.

1. Enterprises go after digital business moonshots

In 2019, more enterprises will make bet-the-company commitments to digital business. It’s a new kind of corporate race as companies adopt these moonshot goals. Expect to see a range of innovation: new business models, new technologies and even entire new businesses built from digital.
Enterprises will have to beat back resistance from those following hybrid traditional-digital strategies and internally competing business unit strategies — and unify the entire business around a common digital program. Concentrate your talent, funding, operating model and executive attention on this program. Having a unified digital strategy between the business and IT is the only way to unload the technical debt that is holding companies back from exploring moonshot digital initiatives.

2. Enterprises adopt next-generation IoT platforms

As enterprises map their physical world to an intelligence-rich one, smart “things” will become a driving force. Enterprises will start to implement next-generation platforms in 2019 that can analyze large quantities of industry-specific data streaming in from the internet of things (IoT) and use artificial intelligence (AI) and machine learning (ML) to find novel correlations between data previously thought to be independent.
For example, precision medicine integrates data from new sources (such as WiFi-connected heart monitors, fitness watches, location data or the human genome) with traditional sources (such as blood chemistry or dietary information). Working with these multiple data inputs and their correlations will result in more precise diagnoses and treatment plans.

3.  Action at the edge disrupts the cloud

In 2019 more apps and data will move to the edge, requiring enterprises to manage apps and data differently via what we call “the Matrix,” the pervasive, intelligent information services that go beyond cloud.
Data “gravity” becomes a primary design principle for multi-latency systems. Because data’s context is frequently local, the ability to maximize data’s value depends on local reaction time. Data gravity means data accumulates locally; the analytics needed to react move toward the data. This brings us back to the Matrix, which puts that intelligent interaction — and us — ever closer to the data.
Hence the shifts toward event-driven applications and serverless architectures that allow very small applications to run in lightweight environments as close as the device in your pocket, on your wrist, retrofitted to your desk or outside your house on a pylon. And yes, 5G wireless will change the data accumulation patterns in disruptive ways.

4.  Enterprises enter an age of Information Enlightenment

As enterprises shift to intelligent operations, they are challenged by increasing data arrival volume (digital trend 3) and data analytic complexity (digital trend 2).  The shift to intelligent operations means reacting faster becomes a competitive imperative.  Data value does decay quickly over time;  the value may be highest right when the data is created but much lower only seconds or minutes later.
So, in 2019, translating broad and deep information into actions will become a core competency. In this age of Information Enlightenment, companies will understand their information ecosystems better and know what to do to make better, faster, data-driven decisions. ML tools will be key for training systems and speeding response times. Enterprises will realize it’s sometimes better to take action based on a strong probability of being right (e.g., 70 percent) than hold out for being perfect (100 percent). That means paying attention to how ML rules are built.

5.  Enterprises redesign customer experiences amid stronger data privacy rules

In 2019, protecting customers’ personal data will force companies to rethink their digital strategy as the full effects of the General Data Protection Regulation(GDPR) set in. Failure to comply with GDPR will thwart an enterprise’s ability to conduct business globally. Innovative companies will see this digital trend as an opportunity to deliver better customer experiences and to build customer trust and loyalty.
Enterprises must have a clear strategy for managing customer data and processes. They will have to consider changes across their data landscape, especially in marketing databases, demand generation systems and customer relationship management systems.
Enterprises will also need to reimagine their information ecosystems with partners and suppliers, creating privacy-centric information ecosystems built on analytics and security, as they aim to deliver secure interactions and superior customer experiences.

6.  Enterprises begin closing their data centers

The enterprise data center is frequently “in the wrong place at the wrong time”. In 2019 we expect to see a noticeable shift of enterprise data center workloads to multi-tenant data centers in the public cloud. Information processing is becoming a utility, and customers (and their data) are widely distributed. Public cloud providers are providing massive bandwidth and strategically-placed data centers, and enterprises are shifting to them for efficiency and to maximize their data’s value.
In effect, enterprise data centers will become virtual compartments in multi-tenant public clouds and thus will be shut down except for their mainframe workloads. Mainframe workloads will migrate to specialized data centers until they, too, eventually go away. We will see a lot of “lift and shift” in 2019, but the trend will play out over the next 3 to 5 years, as cloud migration gives way to “built for cloud” replacements.
Taking these six digital trends into account will help to ensure that the enterprise’s digital transformation journey like Aloha Technology continues to be successful.




Read Original article on https://blogs.dxc.technology/2018/11/15/6-digital-transformation-trends-for-2019/

How AI is reinventing the mobile apps?

The word “Mobile App” is so familiar nowadays that there are thousands of applications for a newborn baby to 100 years old. There are almost 3.8 million Apps in the play store. Every day at least 10 applications are coded and uploaded into different play stores available in the market. Mobile app development became a passion for many as it is yielding impeccable benefits for everyone.


With Artificial intelligence in the market, Mobile Apps are taking its full advantage to make our day to day life simpler and automated. Even though there are millions of applications in the play store, only a few are successful. So it is very important to choose the best mobile application development company to stand out among your competitors.



What is artificial intelligence?

In a simple phrase, we can describe Artificial intelligence as “Intelligence beyond Humans”. We have been listening to the phrase “Robots will replace humans very shortly”. But have you ever thought how it would be possible?

Artificial Intelligence is a computer science engineering subject. In this field, we study how to make robots think intelligently. So that they perform all the tasks that a human can do. AI is everywhere and vast in use from health care to technology. The concept behind automatic cars or trains is Artificial intelligence.

How Artificial intelligence can work with mobile apps?

If you are up to date with the Amazon products or technology, then you must have known about the Amazon product Alexa. It works on your voice commands when connected to your households. If not electronics, have you heard about the driverless car apps?

These both work on artificial technology. Both artificial intelligence and mobile app reduce our work thereby our efforts. So mobile app development with artificial intelligence will lay roads to our future.

Benefits of mobile apps with AI

As said AI reduces human effort by maximizing the computerized technology. There are a lot of benefits by using AI with mobile Apps, some of them are

• Chatbots (instant reply)
• Big data analytics
• Online reviews
• More revenue
• Voice assistants (Siri)

Conclusion:

Artificial intelligence is our future. If you want to be a successful person in the era of technology, then choosing the best mobile application development and artificial intelligence services is the first step to your success. Visit the news about Aloha Technology which Helps Global Companies Race to the Top With Artificial Intelligence and Machine Learning.

Big Data & its Revolutionary Impact on Analytics

Organizations across the world have only recently come to realize how much of an essential asset database is. It is highly valuable for digital transformation as well as business development. It aids the smooth functioning of machines and systems that carry out important tasks like production, logistics, transformation as well as personnel management.

It is also highly vital for being familiar with the preferences and tastes of the consumer in a dynamic market. Big Data has been a unique phenomenon that forced organizations to develop analytical and processing tools that could be capable of processing a massive volume of data, which is unstructured, complex and being generated at a phenomenal pace.

Big Data has had a revolutionary impact on business analytics. It has enabled organizations to make credible, data-driven decisions. It has also paved the way for technological innovation by being a significant precursor to technologies like the Internet of Things (IoT) and Machine Learning (ML). Let us look at some of the factors behind the immense impact of the Big Data revolution.

The Foundation for Digital Transformation

For technologies like Machine Learning, which involves recognizing patterns and trends within a stipulated set of data, the emergence of Big Data has essentially been a foundational element, bringing about a massive scope for further innovation.

Machine Learning technology relies heavily on historical datasets. Larger the volume of the data, more accurate is the system’s suggestions. Thus, IT professionals have been able to use Big Data to their advantage for exploring the potential of many such technological tools like Artificial Intelligence (again, a historic-data reliant technology) as well as the Internet of Things.
Innovation in the field of cloud computing and storage has been propelled to a great extent. Big Data is also proving to be responsible for introducing a culture of developing insight-driven systems and machines. Big Data has led to the development of analytical and processing tools that are able to crunch scores of data in a very short amount of time.

Companies like Aloha Technology offers many such unique IT services that can pave the way for digital transformation in an enterprise. And it can be said that Big Data has been the cornerstone for most of the contemporary disruptive technologies.

Smarter Business Processes

Business development, strategizing and business expansion involves a lot of crucial decision-making. Leaders across the globe have recognized the value that Big Data provides in this process. Big Data renders a complete 360-degree view of the consumers of a particular product or service.
In an ever-changing market, business leaders know how vital this information is. For analytics, Big Data provides a considerable quantity of database. In terms of the quality, this data is not only diverse but also emerges from a varied source. This helps practices like pattern-finding for strategizing for the future.

Decisions relating to investments, insurance and capital generation can be made easily by relying on Big Data accumulated by the organization. Aloha Technology offers varied services related to Big Data Analytics and Processing as well, which can help your organization make your business processes smarter!

The Impact of Big Data

Looking at the two broad areas mentioned above, it is certain that the impact of the Big Data Revolution is far-reaching. It has touched upon every aspect of business as well as technological evolution. We can now say that we have been ushered into a new era of data-analytics with the advent of The Big Data Revolution.

Website: http://www.alohatechnology.com
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AI in the Context of Digital Transformation

In the enterprise, no buzzword is as buzzy as the term “digital transformation”. If you spend any amount of time reading whitepapers, analyst research, or attending webinars you’ll see the term digital transformation used in conjunction with a wide range of enterprise-focused technologies ranging from data centers to application development, to enterprise architecture and AI and blockchain. But what does digital transformation even mean? And how does AI fit into the picture of how enterprises are thinking about AI and related cognitive technologies?

What is Digital Transformation?

Many industry pundits and authorities like to talk about the subject of digital transformation, but the concept boils down to the key idea that technology, and in particular digital technology (computers, networks, data, embedded systems, and the like), lead companies to transform the way they work to take advantage of the more efficient and advanced ways of working. You can think of digital transformation as the after effect of applying digital technology, perspectives, and methods to traditional problems.
In essence, digital transformation is key for organizations who want to remain relevant as technology continues its relentless advance. Organizations who remain bound to old and outdated paper-based processes, human labor-intensive activities, who operate with low information visibility and usage, and with low-skilled labor forces face a future where they could be rendered obsolete by organizations that dominate with the power of a business transformed by the use of digital technology like adapted by Aloha Technology. So, corporations, organizations, and countries don’t have much choice: they must find ways to digitally transform their organizations at increasing levels or face disastrous consequences.

Digital Transformation and the AI-Enhanced Organization

Since Industry 3.0 is at least 60 years old, and Industry 4.0 is now approaching three decades, many ask why companies haven’t already fully transformed their businesses to be digitally centric. Indeed, many of the above research institutions, consultancies, and think tanks are tackling that exact issue. The study conducted by McKinsey & Company said that “On average, industries are less than 40 percent digitized, despite the relatively deep penetration of these technologies in media, retail, and high tech”. Many studies point blame at the complexity of digitizing their businesses and difficulty working with their existing technology systems. It’s an odd paradox: these companies and organizations want to increasingly transform more of what they are doing, but their existing technology is getting in the way. The more technology an organization has, the harder it seems to transform them further. This sounds like a real problem.

In our newsletter and research on the AI-Enabled Future, we talk about the idea of the AI Enhanced Organization. In this vision of the future, we see three primary ways in which organizations will enhance their operations with AI. Summarizing the major conclusions from that research:


Read Original Article on https://ctovision.com/ai-in-the-context-of-digital-transformation/

Nursing for Sickest Patients Artificial Intelligence can provide Solution

In a hospital’s intensive care unit (ICU), the sickest patients receive round-the-clock care as they lie in beds with their bodies connected to a bevy of surrounding machines. This advanced medical equipment is designed to keep an ailing person alive. Intravenous fluids drip into the bloodstream, while mechanical ventilators push air into the lungs. Sensors attached to the body track heart rate, blood pressure, and other vital signs, while bedside monitors graph the data in undulating lines. When the machines record measurements that are outside of normal parameters, beeps and alarms ring out to alert the medical staff to potential problems.
While this scene is laden with high tech, the technology isn’t being used to best advantage. Each machine is monitoring a discrete part of the body, but the machines aren’t working in concert. The rich streams of data aren’t being captured or analyzed. And it’s impossible for the ICU team—critical-care physicians, nurses, respiratory therapists, pharmacists, and other specialists—to keep watch at every patient’s bedside.
The ICU of the future will make far better use of its machines and the continuous streams of data they generate. Monitors won’t work in isolation, but instead will pool their information to present a comprehensive picture of the patient’s health to doctors. And that information will also flow to artificial intelligence (AI) systems, which will autonomously adjust equipment settings to keep the patient in optimal condition.
At our company, Autonomous Healthcare, based in Hoboken, N.J., we’re designing and building some of the first AI systems for the ICU. These technologies are intended to provide vigilant and nuanced care, as if an expert were at the patient’s bedside every second, carefully calibrating treatment. Such systems could relieve the burden on the overtaxed staff in critical-care units. What’s more, if the technology helps patients get out of the ICU sooner, it could bring down the skyrocketing costs of health care. We’re focusing initially on hospitals in the United States, but our technology could be useful all around the world as populations age and the prevalence of chronic diseases grows.
The benefits could be huge. In the United States, ICUs are among the most expensive components of the health care system. About 55,000 patients are cared for in an ICU every day, with the typical daily cost ranging from US $3,000 to $10,000. The cumulative cost is more than $80 billion per year.
As baby boomers reach old age , ICUs are becoming increasingly important. Today, more than half of ICU patients in the United States are over the age of 65—a demographic group that’s expected to grow from 46 million in 2014 to 74 million by 2030. Similar trends in Europe and Asia make this a worldwide problem. To meet the growing demand for acute clinical care, ICUs will need to increase their capacity as well as their capabilities. Training more critical-care specialists is part of the solution—but so is automation. Far from replacing humans, AI systems could become part of the medical team, allowing doctors and nurses to deploy their skills when and where they’re needed most.
At Aloha Technology we are ready to provide the AI solution for your healtcare units. Just keep in touch with us.
Read original article on https://spectrum.ieee.org/biomedical/devices/ai-could-provide-momentbymoment-nursing-for-a-hospitals-sickest-patients

Does Synthetic Data Hold The Secret To Artificial Intelligence?

Could synthetic data be the solution to rapidly train artificial intelligence (AI) algorithms? There are advantages and disadvantages to synthetic data; however, many technology experts believe that synthetic data is the key to democratizing machine learning and to accelerate testing and adoption of artificial intelligence algorithms into our daily lives.
What is synthetic data?
When a computer artificially manufactures data rather than measures and collects it from real-world situations it’s called synthetic data. The data is anonymized and created based on the user-specified parameters so that it’s as close as possible to the properties of data from real-world scenarios.
One way to create synthetic data is to use real-world data but strip the identifying aspects such as names, emails, social security numbers and addresses from the data set so that it is anonymized. A generative model, one that can learn from real data, can also create a data set that closely resembles the properties of authentic data. As technology gets better, the gap between synthetic data and real data diminishes.
Synthetic data is useful in many situations. Similar to how a research scientist might use synthetic material to complete experiments at low risk, data scientists can leverage synthetic data to minimize time, cost and risk. In some cases, there isn’t a large enough data set available to train a machine learning algorithm effectively for every possible scenario so creating a data set can ensure comprehensive training. In other cases, real-world data cannot be used for testing, training or quality-assurance purposes due to privacy concerns, because the data is sensitive or it is for a highly regulated industry.
Advantages of synthetic data
Huge data sets are what powers deep learning machines and artificial intelligence algorithms that are expected to help solve very challenging issues. Companies such as Google, Facebook and Amazon have had a competitive advantage due to the amount of data they create daily as part of their business. Synthetic data allows organizations of every size and resource levels the possibility to also capitalize on learning that is powered by deep data sets which ultimately can democratize machine learning.
Creating synthetic data is more efficient and cost-effective than collecting real-world data in many cases. It can also be created on demand based on specifications rather than needing to wait to collect data once it occurs in reality. Synthetic data can also complement real-world data so that testing can occur for every imaginable variable even there isn’t a good example in the real data set. This allows organizations to accelerate the testing of system performance and training of new systems.
The limitations for using real data for learning and testing are reduced when using fabricated data sets. Recent research suggests that it is possible to get the same results using synthetic data as you would with authentic data sets.
Disadvantages of synthetic data
It can be challenging to create high-quality synthetic data especially if the system is complex. It’s important that the generative model creating the synthetic data is excellent or the data it generates will be affected. If synthetic data isn’t nearly identical to a real-world data set, it can compromise the quality of decision-making that is being done based on the data.
Even if synthetic data is really good, it is still a replica of specific properties of a real data set. A model looks for trends to replicate, so some of the random behaviors might be missed.
Applications of synthetic data
Whenever privacy concerns are an issue such as in the financial and healthcare industries or an enormous data set is required to train machine learning algorithms, synthetic data sets can propel progress. Here are just a few applications of synthetic data:

• Synthetic data with record-level data can be used from healthcare organisation to inform care protocols while protecting patient confidentiality. Simulated X-rays are combined with actual X-rays to train AI algorithms to identify conditions.
  
• Fraudulent activity detection systems can be tested and trained without exposing personal financial records.
  
• DevOps teams use synthetic data to test software and ensure quality.
  
• Machine learning algorithms are often trained with synthetic data.
  
• Waymo tested its autonomous vehicles by driving 8 million miles on real roads plus another 5 billion on simulated roadways. Other automakers are using video games such as Grand Theft Auto to aid its self-driving technology.
  

While synthetic data isn’t fool proof, it is an important tool to augment machine learning algorithms when real data is too expensive to collect, inaccessible due to privacy concerns or incomplete.
Aloha Technology Helps Global Companies Race to the Top With Artificial Intelligence and Machine Learning


Read Original Article on https://www.forbes.com/sites/bernardmarr/2018/11/05/does-synthetic-data-hold-the-secret-to-artificial-intelligence/#50742be342f8

Why AI-driven analytics will have the measure of the digital enterprise

As the name succinctly says, big data has always been about scope, scale and volume; a more the merrier ethos when it came to the intelligence suddenly at business's disposal
The sheer volume of insight generated by big data was considered a prerequisite for accurate decision-making. It brought gigabytes and terabytes to mainstream parlance, while signalling a whole new era of data handling and management with greater complexity and opportunity in terms of application.
However, as this data overload became the new norm, our expectations evolved to demand a more strategic approach to how we can derive greater value from the intelligence flooding our systems. Many have learnt the hard way that more isn’t always better when it comes to data-driven decision making, as quantity rarely surpasses quality when it comes to more discerning and meaningful interventions.
Aloha Technology's Digital Transformation solutions bring innovative technologies to assist enterprises of any size or industry.
Perhaps not surprisingly, this realisation brings us to a growing trend in the digital enterprise. Defined by a shift in mindset from simply collecting intelligence to the more forensic measures used to drill down into it and extract the specifics, the use of advanced analytics is enabling us to do more with less data. This move increasingly underpins higher operating margins and ultimately creates a competitive advantage.
Fuelled by machine learning technology, this traction is in fact, forcing a re-evaluation of the traditional ‘more is more’ Big Data strategy that has long been a pervasive mantra in the digital environment.
In this context, artificial intelligence combined with visual analytics becomes the game changer. This powerful proposition is perfectly equipped to sift through the reams of information and define the relationships and anomalies between the data sets to uncover actionable intelligence that augments human intelligence for greater business value.
While AI puts in the ground work, at a speed and scale impossible for a human to compete with, visual analytics provides a more accessible and intuitive approach to data analysis. This can have deeper repercussions for an organisation more broadly, specifically in terms of promoting a more entrenched data culture.
As a result, a greater section of the workforce can be involved in data-driven decision making, as opposed to a privileged few, a move that far from simply being a ‘nice to do’ will become a fundamental requirement to offset the scarcity of specialist data skills.
Figures from McKinsey and Company highlight the extent of the problem, with the US, for example, facing a shortage of 190,000 people with analytical data skills and 1.5 million managers and analysts equipped to understand and make decisions based on the analysis of Big Data.
So how does AI-powered analytical innovation and data democracy translate into tangible gains when applied to the real-world industry environment? Notable proponents such as the health, finance and manufacturing sectors have been quick to embrace the approach. Heatlhcare professionals are harnessing the technology to detect abnormalities in X-rays, for example. And banks are using the advanced algorithmic capabilities to drive deep content analysis of a customer’s financial status, objectives, risk aversion and can respond to the nuances of their personality and behaviour to best tailor the approach to the user’s needs.
Now we see others playing catch up, such as the oil and gas sector. Here, pressure over ever tighter margins induced by the global drop in oil price has demanded even greater accurate insight to optimise production, as well as to inform continuous monitoring and intervention needed for the smooth and seamless running of critical operations. As a result, a more measurable and quantifiable approach to the enterprise becomes the game changer, as science and business converge ever more closely to keep the business efficient and competitive.
Machine learning is harnessed to provide recommendations and to make predictions over the control and management of assets processing billions of data points in real-time from equipment ratings to thermal gradients. This creates a full picture and level of precision that removes all guess work from the equation.
As a result, gut feel is replaced with an augmented human brain, thanks to algorithmic prowess.
Read Original Article on https://www.information-age.com/ai-analytics-digital-enterprise-123471664/

Is your automated technology a threat to customer relationships?

Companies claim that automating communication with the customer is making their journey much more efficient and streamlined. But is that really the case or are companies just putting a barrier between them and their customers?
We’ve all been there: trying to call our bank, GP, or utility provider, and having to press an infinite number of keys to get through to an automated voice that will make us wait on the line while letting us know that we’re number 20 in the queue. Companies claim that automating communication with the customer is making their journey much more efficient and streamlined. But is that really the case or are companies just putting a barrier between them and their customers?

The broken process: using technology to replace human interactions

It seems almost impossible nowadays for customers to get through to anyone on the phone when calling a company. Bearing in mind customers are likely to only pick up the phone when they want to sort something out quickly or they have a problem, this poor experience is probably going to have a damaging effect on brand perception and loyalty. A Times investigation for instance recently found that Britain’s Big Six energy suppliers were taking more than 20 minutes to answer customer phone calls in some instances, prompting many to switch suppliers. In today’s competitive market, businesses cannot risk losing their customers because of poor service. They need to develop good relationships with them rather than relying on technology to do it for them. They need to stop hiding behind automated processes and chatbots and distancing themselves from their customers.
Forcing customers to communicate with robots through several layers of filtering and recorded voices can make them more frustrated and their lives more difficult than a quick conversation with a customer service agent. For customers, there is nothing worse than feeling like the organisation they are trying to reach is not prioritising their needs. Avoiding unpleasant conversations by hiding behind technology only makes it harder for customers to trust the brand and build a positive relationship with it.

The solution: using technology to enhance human interaction

Fortunately, we live now in an age of unprecedented technological advancement; which means that for every pain point organisations have, there is usually some technology available to solve it. Advancements in telephony technology mean that businesses have the resources to make the phone experience much more enjoyable and insightful for both their customers and their staff. Businesses no longer need to see the phone as the conduit for difficult conversations, but as one for insights that benefit the business.
The first thing organisations need to keep in mind, when it comes to their customers, is that they want to have the company’s whole and undivided attention. This means a personalised experience, which entails knowing your customers well enough to provide that experience. When customers know they are being cared for, they start thinking positively about brands, and might be inclined to expand their conversations beyond complaints or issues. When conversations become more pleasant, this is an opportunity for brands to build positive relationships with their customers and gain more insights. There are now smart solutions that allow companies to record information about every conversation that they have with a customer over the phone; keeping track of their details, what was discussed and even the tone of the customer’s voice to track whether it was a positive or negative call. When a customer calls back, the system uses that information to provide a personalised journey right from the beginning. Often it is strong emotions – stress or confusion – that lead us to pick up the phone. Making that experience as easy and helpful as possible will make a huge difference to that customers’ perception of your brand.
Technology can also help businesses provide greater job satisfaction to customer service agents by ensuring their skills are properly used and they get the training they need. Skills-based routing can for instance allow customers to be automatically directed to an agent equipped with the skills needed for that particular customer’s profile; this is made possible thanks to artificial intelligence collecting and analysing data from previous interactions between the customer and the brand like Aloha Technology.
When speaking to a customer, a salesperson or call centre worker will be able to help them quicker and more effectively if they have information about previous conversations, language preference and company name at their fingertips. Not only will this improve customer service, but it will also make staff more efficient and productive. By that same measure, technology can also be used to spot ways to improve staff performance. For example, Artificial Intelligence is starting to be used to determine good calls from bad calls. As well as helping personalise the experience for the customer, as discussed above, this is also crucial information for staff development. In a contact centre environment, where calls and sales performance are recorded and logged, managers can listen to the calls to identify particular trends and spot potential areas of improvement. That way the employer can provide training specific to the individual’s needs. In the same environment, managing how calls are allocated between the team ensures that workers are not overloaded, and employees can create a more relaxed and productive working environment. Ultimately, businesses want their call centre staff spending less time redirecting or inadequately answering customer queries and more time on building relationships with customers – which an automated phone system cannot do by itself.

Read article on https://www.itproportal.com/features/is-your-automated-technology-a-threat-to-customer-relationships/