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Big data Trends in Healthcare Archives | Quantzig

Tag: Big data Trends in Healthcare

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Healthcare Analytics: How is It Improving Healthcare Operations Globally?

What is Healthcare Analytics?

Healthcare analytics aims at offering insights into patient records, hospital management, costs, and diagnoses. It covers a broad swath of the healthcare industry, offering insights on both the micro and macro level. Healthcare analytics, when combined with data visualization tools and business intelligence suites, helps healthcare companies operate better by offering real-time information that can support decision making and deliver actionable insights.

Are you facing difficulties in dealing with regulatory pressures in the healthcare industry and constantly changing market dynamics? Get in touch with us to know how healthcare analytics can help you deal with all your issues.

Why is Data Analytics Important in Healthcare?

With the adoption of digital tools like electronic health records (EHRs), data has become more structured. Furthermore, it has improved the analysis to a large extent. Moreover, the emergence of machine learning and artificial intelligence have made inferences and predictions easier than ever before.  The dramatically positive impact data analytics can have on the pressure health systems is more efficient and promises to enhance clinical outcomes. Ideas such as doctor-on-demand, video calls, and Wi-Fi-enabled blood pressure monitors were a fantasy a decade ago. But today they are mainstream and real. This is encouraging both consumers and healthcare providers to adopt healthcare analytics rapidly to lower costs, improve efficiency and enhance patient satisfaction.

Healthcare analytics provides consolidated and actionable insights and helps in risk mitigation and resolution of issues facilitating efficiency and accuracy in the process.

Benefits of Health Analytics

Benefit #1: Identifying and targeting the right people

Health plan serves a diverse group of people who may be at any point along the continuum of health and wellness. Healthcare analytics helps the healthcare companies to identify people who are at risk and could benefit from weight management, additional screenings or smoking cessation programs. Furthermore, healthcare analytics aids in providing care to those who need it best. This starts by analyzing multiple sources such as claims data, health risk assessments and a lot more. Without healthcare analytics, health plans would have to wait to find who requires careful coordination. Additionally, health plans can leverage healthcare analytics to analyze what are the factors that motivate people and how to change their behavior. Also, it helps in taking a closer look at screening rates among people in different demographic groups. This can further help in identifying barriers to screening and determining the best way to encourage target groups to complete the recommended screenings.

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Benefit #2: Increasing productivity with real-time healthcare analytics

Healthcare analytics offers relevant data that elevates operational efficiency. This is the reason why proactive healthcare organizations are turning to healthcare analytics for right-time data feeds to track costs and outcomes and improve decision-making. Furthermore, it also facilitates the standardization of staffing with real-time data that allows physicians to focus on one patient-centered activity at a time. Top healthcare organization has realized an improvement of 50 percent in its variance from benchmark lengths of stay and a reduction of 10 percent in readmissions for heart attacks and heart failure.

Benefit #3: Reducing inefficiencies in the supply chain

Healthcare companies accumulate a huge amount of data which is stored in silos across the entire enterprise. Data silos make it difficult to spot the opportunities of savings in the thousands of daily supply chains. Healthcare analytics helps in connecting these islands of information which leads to smarter and wiser buying decisions. Additionally, it provides the ability to gather and blend data on a common field. By leveraging healthcare analytics, companies can create dashboards with data from multiple sources. Furthermore, this will offer 360-degree assessments of supply chains and help in more accurate visuals, eliminating excess and obsolete inventory while reducing the involvement of clinical staff in replenishment and ordering.

Benefit #4: Automating ad hoc visual analysis

Healthcare analytics helps in automating spreadsheets for ad hoc financial reporting in healthcare. This rule out the tendency of mistakes that are made at the expense of accuracy, efficiency, and time. Data visualization thus allows to quickly automate processes that used to consume a large amount of time. Furthermore, by leveraging healthcare analytics and artificial intelligence, providers can see a significant improvement in revenue, patient access, lower cost, patient experience, and increased asset utilization.

We understand the challenges companies face in data-driven decision making and solving operational problems. Our analytics solutions provide best-in-class frameworks to introduce innovations frequently and strive for better clinical outcomes. Request a free demo below for more insights.

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4 Effective Ways Healthcare Data Analytics is Reducing Healthcare Costs

Despite its promising growth prospects, healthcare service providers are hard pressed to find solutions to multiple complex issues including regulatory and policy changes, medicinal and technological advancements, rising costs, staff, and trained employees, maintain efficient operations and services, and support other healthcare initiatives. With increasing concerns for living healthier, longer, and lead more active lifestyles, healthcare costs have increased. Research reveals that the spending and healthcare costs often rise at rates more than the rate of inflation and is expected to increase even more in the years to come.

With the rising healthcare costs, co-pays and deductibles have become expensive and employers are burdened to take a bigger cut of their employees’ wages to pay for insurance premiums. This surge in healthcare costs will soon become a big barrier to the growth of the overall healthcare industry. Therefore, leaders must find alternative methods to combat rising healthcare costs. They must do the appropriate research to find funding, grants, and contributors to help them conduct research, set up programs and implement processes at the pace of change.

At Quantzig, we understand the impact that costs have on your business plans. And to help companies excel in an ever-competitive marketspace, our team of experts has highlighted four effective ways in which healthcare data analytics can reduce the Contact USrising costs of care.

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Can Big Data Finally Bring an End to Cancer?

Cancer is a disease that is as old as the human civilization itself. At present, it is the second leading cause of death after cardiovascular disease. Looking at the advancements in modern medicine, one may wonder, why haven’t we found a cure for cancer yet? Cancer is a complex disease and can affect various parts of the body. A single tumor can have billions and billions of cells with each cell capable of acquiring mutations individually. To find a cure, it is almost impossible to study each variation individually. Additionally, the disease is always changing, evolving, and adapting. The best chance of studying the disease is to understand the genetic makeup of the tumor, which has billions of genomic codes. Such studies are far beyond human comprehension and require a technology that can process such vast amount of information. Big data can make such calculations possible and aid in the cancer Free demotreatment.

Understanding cancer

Cancer is a genetic disease, and is caused by certain mutations in the genes that control our cell’s functioning, especially how they grow and divide. Variation or a fault in some genes can cause the cells to grow in an uncontrolled manner. Such errors can occur due to exposure to carcinogens, radiation, and surrounding biophysical environment.

Why is it so challenging to study cancer?

Its now clear that to study cancer, physicians must understand the make-up of a particular gene. However, for an extended period of time, it has been an almost impossible task. Consider this; the human gene is composed of four different types of chromosomes. The DNA in the largest chromosome, chromosome number 1, consists of approximately 220 million base pairs. Cancer can result from mutation or alteration in any one of such base pairs. Similarly, mutations can occur in any combination of such base pairs. As a result, it is impossible for humans to devise an effective cancer treatment plan by studying all such mutations.

How can big data help in finding cancer treatment?

Big data has the capability to analyze such a broad array of information not only across a single gene but also across genetic makeup across large samples of a cancer patient. It can find out the correlation between certain factors that cause a particular type of cancer. So how can big data aid the healthcare industry to find a cure for cancer?

Targeted treatments

Targeted treatment can be used to target cancer’s specific genes and proteins that fuel the growth of cancer cells. By testing a sample of the tumor, patients can be given new drugs and targeted therapy to figure out whether the tumor has a specific target. By analyzing samples across a large population, physicians will be able to improve the efficiency of such targeted treatments.

AI-driven diagnosis

One of the pioneers in the field of cancer treatment using AI is the supercomputer, IBM Watson. Since each cancer is different, and each person has different genes, Watson can recommend a cancer drug that will most likely treat a particular patient’s cancer. It is because the supercomputer is programmed with specific details on how thousands of medicines interact with the human body. From there, Watson can make recommendations on which medication interacts beneficially with the cell affected by the cancer-causing mutation.

Genomic data

It is evident that genomic data is enormous. It takes around 200GB of storage to capture the raw code output by a genome sequencer. The cure for cancer lies in such databases. Using comparative analysis, researchers can isolate the factors that lead to cancer. However, it is not as simple as it looks, it requires huge storage and immense computing power to perform such analysis. Big data can assist healthcare professionals to compute, harvest, and decode such significant amount of data and consequently contribute towards cancer treatment.

Radiation therapy

For now, radiotherapy is the major treatment mode for cancer along with surgery and chemotherapy. A large majority of cancer patients receive radiotherapy as a part of their treatment. However, there’s a problem with such treatment mode. Physicians need to know the exact amount of radiation required, too little and it won’t work, and too much can cause side-effects and damage healthy cells as well. Analyzing historical radiation data could be used to guide radiotherapy safety thereby improving treatment efficacy.

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IR24

The Best Health Metrics to Use for Performance Measurement in the Healthcare Industry

The explosion of data science in the modern world has increased the importance of business intelligence, or BI, in the healthcare industry. The healthcare industry generates a lot of data from patients, process, tests, research, and operations. It is almost impossible to make sense of such unstructured data without using any relevant business intelligence tools. Furthermore, the healthcare industry can make use of predictive models and data visualization tools to gain insights regarding patient care, labor distribution, clinical operations, and general administration. The overall goal of the healthcare industry is to improve patient care and operational efficiency. Advanced BI softwareFree demo can help companies to achieve such goals by assessing their performance using various health metrics. Using such health metrics for evaluating performance can help single out improvement areas.

Average hospital stay

Average hospital stay is often an indicator of efficiency in the healthcare industry. This health metrics measures the average amount of time spent by patients admitted into healthcare facilities. Average length of stay (LOS) is often used as a quality metric by medical reimbursement companies to build a prospective payment system.

Hospital readmission rates

Such health metrics measure the number of patients who are readmitted to the healthcare facility shortly after their initial release. The metrics provide critical insight to the quality of care received by the patient at hospitals. Hospitals have to be alarmed when readmission rates rise as it can usually mean a shortage of staff, lack of materials, or point out areas with special needs.

Patient wait times

Patient wait time is widely used in the healthcare industry to measure the amount of time needed to receive treatment from the time they entered the healthcare facility. Patient wait time as a health metrics is useful in measuring patient contentment as well as hospital efficiency. Higher patient wait time is usually the result of understaffing or poor operational design. Measuring this metric over time enables hospitals to identify trends and redistribute labor to deliver more efficient patient management.

Bed or room turnover

In simple terms, health metrics such as bed or room turnover demonstrate how quickly patients are moving in and out of the facility. From a patient satisfaction perspective, it measures how efficient a hospital is, as a patient do not want to spend more time in the hospital. A high turnover rate depicts that hospitals are very efficient at treating patients. However, when coupling with hospital readmission rates, it can paint a complete picture whether they are really efficient or patient usually come back with the same problem.

Average treatment charge

Average treatment charge is of the major financial health metrics, which measures the average amount charged by a hospital to provide treatment to a patient. The metrics can be used by the healthcare industry to calculate the overall average or show an average of each treatment category.

Patient to staff ratio

There is no hard and fast rule that states that a healthcare facility should achieve a certain number to be effective. The ratio should be ideal since a higher patient to staff ratio will result in higher wait times and low care quality. On the hindsight, lower patient to staff ratio adds a financial burden to the hospitals and consequently increases the cost of care. It also exhibits administrative inefficiency and calls for hospitals to reconsider labor distribution.

Medication errors

The healthcare industry is striving hard to lower this health metrics, which measures the number of mistakes made in prescriptions. It also includes mistakes made in dosage and patient and applies both to inpatient and outpatient services.

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Redefining Healthcare: Top Healthcare Trends to Watch out for in 2018

With tremendous technological advancements and innovative healthcare trends in place, 2018 is poised to be a game-changing year for the healthcare industry. Earlier, healthcare was slated as one of the most ‘conservative’ industries, but with healthcare players embracing technological innovations into their operations it looks like they are finally ready to get rid of that tag. Several companies in this sector are redesigning old techniques and treatments to modernize healthcare and make healthcare facilities available even in most distant and rural areas. The positivity with which the healthcare industry will function in the coming years is expected to have a domino effect on some of the inter-related sectors such as the healthcare vendors and suppliers, the insurance industry, the banking industry,Free demo etc. We have highlighted a few healthcare trends that are expected to bring in fresh innovations and improve healthcare facilities in 2018:

Unveiling new drug pricing models

Though drug pricing has always been a sensitive topic, recent developments show consumers becoming more vocal in their opinion about the rising drug prices and high-deductible healthcare plans. As a result, we can expect to see an increase in governmental regulations to control the increasing drug prices. Recent surveys show that customers are more willing to pay dug prices in installments rather than paying them in one shot. Such healthcare trends would call for reforms in drug pricing models in 2018.

Artificial intelligence will be your new coworker

Bureaucracy and administrative duties have taken away time from personalized care in the healthcare industry. Incorporating artificial intelligence is expected to put the human touch back into healthcare, which would make it one of the most promising healthcare trends to watch out for. Healthcare companies are leveraging AI for administrative tasks such as screening drug candidates, streamlining finance processes, and adverse event reporting, etc. which makes tasks easier and quicker. Also, this gives the staff more time for dedicating to improve personalized patient care.

Rise in consolidation and mergers

The past two years have seen several organizational agreements and partnerships in the healthcare industry. And this is expected to continue as one of the prominent healthcare trends in the industry in 2018 as well. Such collaborations between hospitals, clinics, and other and top and medium tier health systems will generate better services for patients. This trend is also expected to rapidly scale-up the use of modern technology used to serve the patients.

Cybersecurity threats on the rise

With technology adoption at its peak in the healthcare industry, the threat of hacking and insufficient security measures is also on the rise. Hackers gaining control over connected medical devices such as insulin pumps and pacemakers could cause significant chaos for healthcare companies. Hence, we can expect healthcare companies to become more proactive when it comes to securing medical equipment in the coming years. This also means that the top-notch network architectural services will have to become a norm rather than a requirement in the healthcare industry.

Focus on low-cost healthcare

Low-cost healthcare facilities are possibly one the major healthcare trends we all have been looking forward to. As far as healthcare companies are concerned, the most prominent dilemma in front of them would be to deliver the best possible results while keeping the prices down. This year, the growing budget pressure on healthcare companies will prompt them to formulate ways to provide quality healthcare.

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Best Use Cases of Big Data in Healthcare

Big data has transformed many industries by performing analysis and conducting forecasts that were previously deemed impossible. One such area where big data has brought about a considerable change is in the healthcare industry. The use of big data in healthcare has the potential to reduce the treatment costs, improve operational efficiency, improve patient outcomes, and improve the quality of life. Today, healthcare professionals have access to large volumes of data like the EHR, which help them devise effective strategies. The rising cost of healthcare services is a major factor behind the use of big data in healthcare. For instance, healthcare expenses represent about 17.6% ofFree demo the nation’s GDP in the US. Smart, data-driven thinking can significantly reduce such expenses without compromising on outcomes. Here are some of the best examples of the use of big data in healthcare.

Big data assists in operational management in hospitals

One of the most significant problems faced by healthcare facilities is to allocate healthcare personnel in a given shift optimally. Too few and the quality of patient care deteriorates, too many and it unnecessarily increases the operational cost. Four hospitals in Paris, which are part of the Assistance Publique-Hôpitaux de Paris, have been using big data to forecast the patient footfalls at a given time and date. A key data point to perform such analysis is obtained from historical hospital admissions record, which goes back as far as ten years. The data scientists then performed a time series analysis to see relevant patterns in admissions rate. Feeding this data into machine learning programs can fetch the best algorithms to predict the future admission trend.

Electronic Health Records (EHR)

EHR is one of the most prominent examples of the use of big data in healthcare. It is a master repository of patient data that includes their demographic information, medical history, test results, and allergies. These records are then shared among healthcare practitioners in both public and private sector to provide better care. The healthcare practitioners can add new data into the records as they give care to the patients without the fear of data duplication. The advancements in EHR have progressed to such levels that it can also trigger warnings to track prescriptions and send reminders when a patient gets a new lab test. The US has been the model country in implementing the EHR with a 94% adoption rate, while other countries are still struggling to implement them fully.

Prevention of medicine abuse

Medicine abuse can be fatal and lead to consequences as bad as accidental deaths. In the US alone, opioid abuse has caused more accidental deaths than road accidents, overtaking it as the most common cause of accidental death. The Obama administration spent close to $1.1 billion to tackle this problem. However, scientists at Blue Cross Sheild have started working towards the problem, which would cost a fraction of that $1.1 billion. In partnership with big data experts at Fuzzy Logix, they start out by analyzing years of insurance and pharmacy data to identify 742 risk factors that predict whether someone is at risk for abusing opioids. As a result, it helped the concerned authority to prevent drug abuse cases by identifying the people who were at a higher risk.

A cure for cancer

The Obama administration came up with Cancer Moonshot program, which had panels that made recommendations towards finding an effective cure for cancer. One such suggestion made from the panel included the case of big data use. Medical researchers are studying a variety of data to find trends and treatments and recovery rates of cancer patients. The researchers can spot the treatment plan with the highest success rate and also point out the best treatment plan for each patient. Additionally, by examining tumor samples and patient treatment records, data scientists can figure out how specific mutations and cancer proteins interact with a variety of treatment plans provided to the patient. One of the most promising use cases of big data in healthcare industry has to be genetically sequencing cancer tissue samples from cancer trial patients to find a viable solution.

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Top Challenges in Clinical Data Management

Today, all modern industries and companies are embracing the power of digital technologies. The healthcare industry is also following the trend by using patient data management systems, which keeps track of patient information and medical history thereby replacing handwritten medical files. Since patient data is sensitive, medical companies and professionals should adopt new strategies to manage such healthcare data securely. Clinical data management simplifies a lot of operational tasks thereby increases the efficiency of healthcare providers. However, it Free democan be challenging to manage such large and complex sets of healthcare data. Clinical data management is further complicated by various government regulations and compliance issues.

HIPAA Compliance

The Health Insurance Portability and Accountability Act (HIPAA) requires security measures for EHRs to be shared among medical practitioners and be made accessible to patients. Majority of the healthcare providers have to balance between operating a closed-network system and implementing shared data access and security protocols. Also, after providing a platform to share data between practitioners, a data breach could cost healthcare companies significantly higher than in other industries.

Sharing Patient Data

Sharing patient data is still a grey area for players in the medical industry. Some regulations restrict sharing of data with a medical representative and other medical professionals. To tackle such issues, the medical industry is working on strategies like EHRs and cloud computing to facilitate sharing of clinical data. Additionally, integrating and standardizing the sharing platform for every medical professional to grant access to healthcare data is also an ongoing challenge.

Mobile Computing

The demanding nature of today’s digital technology has placed great importance on mobile computing. Professionals want access to data at the comfort within their fingertips. However, shifting the platform to mobile devices seems quite a challenge in the field of clinical data management. It’s a lot easier to upload medical entries to a tablet directly then scribbling on medical charts for transcription later. The problem arises when providing a secure wireless access throughout the care facility to medical professionals. It requires developing a completely new security and compliance protocols for mobile devices.

Operational Analytics

The clinical data management systems and EHRs have helped improve the quality of care that is provided to the patients. Alongside patients, healthcare professionals and workforce has also benefitted with a substantial increase in operational efficiency. For instance, healthcare workforce management is largely measured using patient care and healthcare data, which isn’t an ideal metric for performance measurement. As a result, it has urged HIS managers to look for new strategies to mine healthcare data in order to perform productivity and profitability analytics to identify true measure of performance and identify improvement areas.

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3 Secrets to Success for Digital Transformation in The Healthcare Industry

Irrespective of the industry, digital transformation has been widely accepted with open arms by all. In highly sensitive sectors such as the healthcare industry, digital transformation and technology are more than just a utility. Many players in this industry have long relied on technology as an essential tool for R&D, tracking patient information, scheduling payments, launching new care operations, etc. Healthcare companies are increasingly making use of data analytics and cloud storage to put the data available to them to their best advantage while simultaneously keeping their customers happy. Today ‘customer experience’ has become a commandment that players in the healthcare industry swear by; therefore, it has become a part and parcel of healthcare services to encourage digital transformation and integrate latest technologies into their services to improve the customer experience and satisfaction levels. But how can players in the healthcare industry go about successfully switching over to digital technologies? We have narrowed down three core principles that would help healthcare companies transition to digitization:Free demo

Keep A Close Watch On The Changing Landscape

Technology has taken over the world today, and the customers are well aware of the technological advancements happening around them. Due to this, it is essential for healthcare companies to keep close tabs on the technological developments and digital transformations happening around them. Latest advancements such as 3D printing, robotics, machine learning and big data analytics have already started to work wonders in the field of healthcare. The healthcare industry players need to incorporate this technology into their operations by identifying the ones that are most feasible for them.

Strengthen Your Core Management Capabilities

To ensure the effectiveness of digital transformation, healthcare industry companies must ensure that they have an active staff base who are open to new technology and have the necessary skills and expertise in the same. Healthcare companies must see to it that the gaps in skilled staffing are overcome so that implementing advanced technology will be easier in the organization.

Identify Means For Offering Targeted Digital Products And Services

Personalization is a growing trend in the healthcare industry. Patient requirements vary from one another. Therefore, companies in the industry must identify ways in which they can target their digital offerings to customers based on their needs. To obtain better patient outcomes, various device manufacturers in the medical field are incorporating digital solutions into their products such as predictive diagnostics, remote monitoring of patients, fully digital surgical units, etc. Healthcare industry players must identify which of these would be best suited for providing an ultimate customer experience and adopt the same.

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IR39

What are the Next Big Things in Store for Retail Healthcare

The healthcare industry’s slow shift toward retailization has opened the doors for convenience care and modern healthcare facilities for customers. Affordability, convenience, and access are now becoming the motto that the healthcare industry swears by. Let us look at some of the key trends that are likely to reshape the face of modern retail healthcare:Free demo

Virtual Care

You would have often seen in movies of the 70’s and 80’s, when a person falls ill the doctor is summoned home. But in today’s scenario where healthcare has become a way of life, it is impossible for doctors to physically go to individual patient’s homes and provide treatment. This is where digitization has made life simpler for people. It makes it possible for you to consult your doctor through a digital medium without having to go to the clinic. Virtual clinics are becoming increasingly popular in retail healthcare owing to the convenience it provides to the customers as well as the doctors.

Big Data Analytics

Big data analytics is transforming the way healthcare was seen earlier. With the introduction of retail healthcare, companies are becoming more focused on providing individual and specialized care to patients. The enormous amount of patient data available with hospitals is used in conjunction with big data analytics to provide better treatment to the healthcare customers. Hospital can now examine the past medical records of customers and provide them with tailor made services to give them an enhanced experience compared to a conventional hospital visit.

Virtual Reality Tools

The healthcare retail industry is reaping the benefits of VR technology. This technology has proved highly effective in  healthcare analytics due to its ability to control pre-and post-surgery patient anxiety. The virtual reality tools are also being used by the medical industry for medical education and clinician training. VR has made it easier to teach medical students anatomy, pharmacology, and surgery, giving them much more clarity than traditional learning models.

Healthcare IoT

The retail healthcare industry is leaving no stone unturned to enhance their patient care and experience. The players in the medical industry are using IoT to tackle issues such as patient engagement, patient safety, and chronic disease management. Other important benefits of IoT in healthcare retail include better communication between patient and care teams, accelerated speed of response time in medical emergencies, shortened hospital stays, proactive patient monitoring through smart beds etc.

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IR19

Answers to the 3 “Big Questions” in Artificial Intelligence

For years, the business world interpreted data to formulate meaningful business strategies using traditional analytics. However, technology has made life more easy and advanced for us. Technologies like artificial intelligence are slowly transforming our everyday lives just like how the internet and smartphones did years ago. So here are three answers to the three questions about analytics and AI technology that probably would have run through your mind at some point in time.Free demo

Why is Artificial Intelligence the Next Big Thing in the World Of Technology?

Before the invention of AI technology, did you think anything could be as superior or much more advanced than the human brain? Well if the answer is no, then that is precisely why there is so much hype around artificial intelligence. Artificial intelligence can do what the human brain does in a much faster and organized manner. This feature of the AI technology has attracted players from various industries such as healthcare, heavy industries, air transport, gaming, etc. to adopt and incorporate this technology into their business operations.

Why Should You Not ‘Leapfrog’ to Artificial Intelligence Ignoring Analytics?

The world is headed for a new era of transformation with technologies like artificial intelligence in place. Though analytics had been the basic foundation stone for formulating important business decisions, over the years companies have started relying more on technology to wash their hands off analyzing complex data sets and arriving at the right solutions. However, companies should understand that as much as AI technology has been a boon, bypassing analytics is not a smart shortcut to incorporate AI technology as analytics is one of the key milestones on the path to being successful in artificial intelligence. Analytics helps companies to drill down various historical and current information about the business to have a broader view of the business scenario. Therefore, it is fallacious for companies to believe that they can ignore analytics and incorporate only AI technology into their business.

Despite its Superior Technological Expertise, Why Are People Still Skeptical About the Future of Artificial Intelligence?

It has been rightly said that nobody or nothing is perfect. The AI technology is also not free from flaws. Artificial intelligence lacks in the following areas that are making many skeptical about its utility in the long run. A few of these challenges are listed below:

  • Lack of emotional intelligence to enhance customer experience
  • The tasks performed by AI technology are specialized and cannot be altered easily
  • Machines using artificial intelligence will replace more jobs
  • Difficult to carry out tasks which require collaboration with various segments or departments

 

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