Automation has made a massive impact in the field of technology, as it enables procedures and processes to be carried out with minimal human intervention and with greater precision. Automation has applications across industries and verticals, playing roles in industrial and consumer landscapes, and has also made its mark in laboratory settings. Since laboratories are where scientific research takes place and hazardous materials are often used, precision and safety are important, making automation a valuable component of labs and an independent market in itself.
Laboratory or lab automation refers to the development of strategies and technologies that can facilitate the application of automation to a laboratory setting, where lab automation can reduce the need of humans in carrying out repetitive and straightforward procedures. Lab automation is a multi-disciplinary field that involves scientists and engineers to develop technologies that will be helpful in a lab. The requirements of lab automation are different from other forms of automation, with precision and recordable results playing an important role in boosting the productivity of labs.
Surge Of Lab Automation Technology In Recent Years
The current value of the global lab automation market or the Laboratory Information Management System (LIMS) market is estimated to be $3.50 billion, out of which the healthcare segment itself accounts for $1.11 billion. The global LIMS market is projected to grow to $4.91 billion by 2024, with the segment for healthcare reaching a value of $1.75 billion in the same period.
Laboratory automation services have the potential to increase efficiency by 80 percent while reducing 40 percent of configuration efforts and providing a return on the investment in under 3 months as implementation and training contribute to 40-45 percent of laboratory automation costs. Factors that pose a threat to the market primarily consist of the lack of availability of trained and skilled professionals and the costs involved in setting up and maintaining lab automation software. At a global level, non-uniform standards of integration slow down market growth.
Lab automation technology has witnessed a surge over the past few years, driven by innovations and advancements in the market, and a greater demand for LIMS services.
- The laboratory automation market can be identified on the basis of industry, for example, life science and healthcare, and on the basis of the role of the technology. The life sciences market accounts for approximately 35-40 percent of the lab automation market share, and biotechnology constitutes 20 percent. The biotechnology segment is expected to grow at a rapid pace, according to experts. Based on lab automation technology, the market can be divided into 6 broad categories, namely, robotics, liquid handling, laboratory execution and data management systems, multiplex and high-throughput ELISA systems, microplate readers, and informatics.
- The demand for laboratories overall is increasing at a global level and with it the demand for lab automation. Labs are being set up by contract research organizations (CROs), for academic research, healthcare research, diagnostics, pharmaceuticals, government research, scientific research, industrial research, biorepositories, biotechnology, chemicals industry and more. As competition increases at an industrial level, innovation, research and development are means for companies to develop new products to beat the competition.
- Technology plays a vital role in lab automation, and there are certain technologies that have made a major impact on the market in recent years. Cloud-based systems for backup security and services for Big Data analysis such as Software as a service (SaaS) and Platform as a service (PaaS) are making their impact on the market. Cloud services make sharing data easier and faster than ever, regardless of the location. SampleManager by Thermo Fisher has emerged as a popular integrated data management system, especially for scientific data.
Online LIMS offers real-time access, interactive data analyzers, auditing features and live daily workbooks. Artificial Intelligence (AI) in the form of Chatbots have become common in lab settings that can perform tactical and customer service roles. Although currently, chatbots are mostly used in oil and gas industry labs, they can be further integrated with traditional clinical labs as well. The Internet of Things (IoT) is another technology that is growing in popularity in lab automation and has significant potential. By linking IoT with lab automation, data can directly be transferred from scientific instruments to the machines without the physical need of humans, thereby drastically cutting down on processing times and chances for error.
- The lab automation market is immensely customizable, which has further increased its appeal across industries. LIMS has multiple variants across the broad categories of clinical, analytical, environment and manufacturing and can be developed and customized to suit the specific requirement. Although customization may require greater up-front costs in setup and training, in the long run, customized lab automation offers greater returns as it performs specialized tasks.
- At a regional level, North America retains its position as a dominant market in lab automation, with the presence and spread of major players of the industry in the region. Greater awareness about diseases, diagnosis processes and the role of labs, has led to a higher demand for lab automation in the area. Larger allocation of funds for research and development is also driving the market in the area.
The Asia Pacific region is considered to be a prospective market with great potential growth opportunities, driven by emerging economies, unmet medical needs, aging populations and demand to boost research and development facilities.
- The many benefits offered by lab automation have further increased their demand in the market. Using lab automation frees up human resources to attend to other tasks, performs repetitive tasks with utmost precision and efficiency, increases operational efficiency, reduces the need for humans to deal with hazardous materials, manages data, and optimizes the clinical workflow overall. Since machines require less downtime, they can work extended hours and also maintain data security and regulatory compliances. Using lab automation reduces operating costs significantly, making it more affordable for smaller companies to set up labs.
Lab automation technology has witnessed a significant surge in recent years with greater demand from diverse sectors for lab facilities. The customization capability of lab automation technology makes it suitable for nearly every facility and purpose. While developed markets currently have a larger market for lab automation, the demand from emerging economies is growing at a rapid pace. Apart from healthcare and life sciences, lab automation technology is used in biotechnology, CROs, academia and research and development. Cloud-based technologies, IoT and innovations are further expected to drive the market for lab automation technology in the coming years.
EMnify Data Streamer Launches New Integrations into Google Cloud Pub/Sub and Azure Event Hubs
EMnify, a leading cloud communication platform provider for IoT, announced new turnkey integrations into Azure Event Hubs and Google Cloud Pub/Sub via its EMnify Data Streamer – a feature that enables real-time streaming of connectivity data into the cloud and self-developed software stacks. These integrations empower IoT support and business teams whose applications are deployed on Azure and Google Cloud with complete network transparency to faster triage and resolve issues.
“When using traditional mobile services, connectivity data is often not easily accessible,” says Christian Henke, Head of Product at EMnify. “This leaves support teams in the dark when problems like excessive data consumption, roaming restrictions and network attachment failures arise.”
EMnify Data Streamer bridges this visibility gap by allowing IoT businesses to integrate real-time information on network events, service usage and costs directly into their applications and operational workflows. The new release extends Data Streamer integrations to Azure Event Hubs and Google Cloud Pub/Sub – besides the existing integration for Amazon Kinesis, Amazon S3, keen.io, Datadog, DevicePilot and Salesforce. Leveraging related services like Google BigQuery, Azure Times Series, and Azure PowerBI, users can build intuitive dashboards of all network activities and set up proactive alerts to stay informed of any abnormal events.
Integrating connectivity metadata with device and application data in their cloud services allows Enterprises to more quickly understand the root cause when no data is available for their customers – whether the problem lies in, for example, firmware updates, network attachment errors or the application not accepting incoming messages. 360-degree visibility further augments the overall security of IoT solutions against unknown security holes and zero-day exploits.
“The latest EMnify Data Streamer integrations upgrade the multi-cloud capabilities of our platform,” says Martin Giess, CTO and Co-Founder at EMnify. “They go in line with our automated cloud connect service which enables private networking between user devices, EMnify platform, and Azure or Google Cloud, securing end-to-end data communication and giving support teams remote device access.”
EMnify provides detailed guides on all available EMnify Data Streamer integrations, as well as how users can analyze and display connectivity data using supportive toolchains and third-party services.
5 ways Big Data can add to Digital Marketing
Long gone are the days when marketing success would be heavily dependent on subjectivity, intuition and huge promotion budgets pushing out marketing messages in your face at all possible touch points. It is a completely different ball game today, and it wouldn’t be wrong to say that marketing as a whole has evolved towards being a completely customer-centric and data-driven activity today; and the most effective strategies, irrespective of industry verticals, aim to deliver personalized customer experiences. This has been possible only due to the advent of big data, to gain valuable insights into customer preferences.
So, what really is big data?
Most organizations today have systems in place to capture and store massive data points from their all their customer interactions from research, sales and marketing. This data can be structured, semi structured or unstructured and will likely continue to increase in size. It can get overwhelming to make sense of this increasingly dynamic information. Big data is a means to analyze and extract valuable information from these complex and interlinked sets of data, and observe patterns that can help guide decision making.
Put simply, big data is a means of processing large volumes of complex data sets to derive actionable insights. Given that the world is going digital, there is already much rich data available from earlier marketing activities, consumer behavior tracking, other databases and research, and it is now possible to paint an accurate picture for almost each consumer and create predictive models for future interactions. This could be used throughout the sales funnel, right from identifying the right consumer, to product design, marketing communication, demand forecasting as well as customer retention.
How can integrating big data into your digital marketing efforts help?
In today’s fragmented marketing landscape, one of the biggest challenges that marketers face is to engage with the right consumers at the right time with the right message. Here is where big data comes in – big data can not only help us understand customers better, it can also help us develop better strategies that are sure to give your business a competitive edge.
Being able to understand and predict consumer behavior accurately using various data based insights can indeed open up a whole new world of opportunities. Here are some of the ways you could use big data to bolster your digital marketing efforts:
- Data Visualization
Big Data makes it possible to make sense of the data, helping marketers recognize patterns, trends and problems, using different types of visual representation. This provides an easier way to understand what the data wants to say, and the different ways in which the data can be interlinked to mine new insights. Think of your social media analytics charts, or even the charts that you can find in Google Analytics, both of which are great examples of big data visualization.
- Consumer Insights
One of the key ways organizations can stay ahead of competition is by mining accurate consumer insights, and leveraging them in their business and marketing strategy. Why settle for ambiguous demographic and psychographic segmentation when you can get richer data for each of your consumers? Data such as what your consumer likes and what products he prefers, what he thinks about your company and preferred distribution channels or modes of interaction, repurchase patterns and more, can help you paint an accurate picture about consumer sentiments, and tweak your marketing initiatives accordingly.
- Predictive Analytics
Historical consumer data and current data can be combined to make fairly accurate predictions about their future behavior. For instance, which product are they more likely to buy and when, how much will they spend, which payment mode they will most likely use and so on. This could help you with forecasting demand for a specific product model in advance. You could also predict beforehand how your campaign might perform given certain parameters, or even when the demand curve for your product could go up or down. It is almost like having a looking glass into the future, which can help you segment and target your consumer groups accordingly, and design marketing initiatives that would better resonate with each segment.
- Customize Consumer Interactions
Once you are able to access latent consumer insights, it will also be possible to create customized online interactions with almost any consumer, based on data from your past interactions with them. Not only will this increase relevance, it will also likely increase engagement and ROI as well. Product recommendations from ecommerce sites, video recommendations on YouTube and Netflix are a case in point. This doesn’t stop at product recommendations. You could even customize your marketing communication in real time, based on past consumer interactions. For instance, you could send personalized emails or text messages based on their past purchases, life cycle stage, demographics and their internet search history, how they have spent their time on your website or mobile app and for that matter, even their response to your past marketing campaigns.
- Budget optimization
A thorough knowledge about whom to target, when to interact, what to say and where to say will make it easier to allocate your marketing budgets more effectively, and focus them on initiatives or consumer segments which are more likely to give you the results you want. This, when combined with data from which of your digital marketing channels are giving you higher CTRs and conversions is a recipe for success. Needless to say, this will also help to prevent budget spillage into areas by casting your marketing net too wide, or in the wrong sea! As you continue to use big data along with AI & ML, you will only get better at optimizing your marketing spends to a point where you will even be able to predict the results you can expect.
- Campaign Evaluation
With specific metrics for each of your multiple campaigns, it will become much easier to measure campaign performance. Unlike the days of yore when it wasn’t possible to accurately attribute campaign results, big data visualization can help one see precisely the ROI on each campaign, including but not limited to increase in sales, how each channel has contributed and even changes in consumer sentiment. This can be used as a blueprint to plan your future marketing campaigns.
As we would all agree, big data is transforming how marketing is done today, as it takes the guesswork out of what digital marketing initiatives will work. I would go on to say that the contribution of big data can only be limited by our imagination, because from where we stand today, the possibilities are truly endless.
5 Emerging Tech Trends Startups Should Follow
In recent years, technology has been evolving exponentially. It is clear that the current tech trends will make or break many companies in the following years. Tech trends will be the driving force behind many changes that await us.
If you want your startup to gain a competitive edge, these are the 5 most important emerging tech trends you should follow.
Artificial Intelligence (AI) and Machine Learning
Artificial intelligence may be the biggest tech trend at the moment. AI and machine learning have made their way into our homes and workplaces. From creating personalized shopping experiences to helping us answer emails and analyze data, AI is revolutionizing the way we live and work.
AI and machine learning have become tools that help us interpret and understand the world around us. An increasing number of companies and professionals, including healthcare providers, stock traders, and car companies, are relying on machine learning to improve their performance, services, or products.
For instance, the volume of data we collect on COVID-19 infection rates and the success of the measures we take to slow down the pandemic is constantly increasing. To find efficient solutions for COVID-19-related problems, researchers are feeding this data to machine learning algorithms.
From analyzing interactions uncovered through contact tracking to monitoring the capacity of public areas, self-learning algorithms have the ability to spot connections that human analysis is not able to detect.
From socializing and shopping to recruitment, meetings, and virtual working environments, more human activity will take place online as a result of the pandemic. Businesses will use machine learning algorithms to analyze and understand the changing patterns of consumer behavior. The AI tools we use to analyze these behavioral shifts will become more commonplace.
More and more organizations will build the necessary infrastructure and set aside funds for AI technologies. Others will rely on AI as a service (discussed below).
The use of robots is becoming more common in the assisted living and care sectors. When it comes to interacting with the elderly and other members of society that are vulnerable to infection, these robots will become increasingly important.
Instead of using robots to replace human interactions, companies will use them to offer new channels of communication.
Businesses across the board are already using virtual assistants and chatbots powered by AI to offer 24/7 support to their customers. The next step will be using physical robots to provide 24/7 in-home and in-the-workplace help to everyone who needs it.
Companies are increasingly turning to robotics providers for services such as security and cleaning. The stock prices of companies involved in supplying robots are soaring at the moment.
Extended Reality (XR)
Extended reality includes augmented reality, virtual reality, and mixed reality. The term covers technology that uses cameras, headsets, or glasses to merge the virtual and physical worlds. By 2022, the XR market is projected to surpass $200 billion.
Soon, XR will allow consumers to head to lunch in some faraway country or shop for a new house as if they were actually on-site.
We are already seeing an increase in the use of AR and VR tools in education. The University of Virginia has developed a VR based classroom that helps teachers improve their classroom management skills.
Some manufacturing companies have started to use VR for on-the-job training because it is safer. It also allows them to simulate dangerous scenarios without actual danger.
5G and Enhanced Connectivity
5G doesn’t just mean that we will be spending less time waiting for YouTube videos to launch or webpages to load. Each time mobile connectivity evolved to a new level, we discovered new use cases for the internet.
For instance, 3G made data-driven services and web browsing useful on mobile devices. And, as bandwidths increased with the introduction of 4G, streaming video and music platforms started to grow.
Cloud-based gaming platforms such as NVidia’s GeForce or Google’s Stadia or advanced technologies such as VR and AR will become much more viable when 5G launches worldwide.
Since we won’t need to be tethered to a particular location when 5G becomes commonplace, fiber-based and cable networks may become redundant.
Eventually, 5G will make all other major tech trends available anywhere, any time. There are already some practical examples of this. For instance, Samlar, a Norwegian fishery operator, uses a pilot 5G Telenor Norway network to automate the feeding and care of its fish.
The “As-A-Service” Revolution
AI, robotics, and other technological advancements have become so accessible partially thanks to the “as-a-service” revolution. The “as-a-service” sector provides services that we need to work through on-demand, cloud-based platforms. It’s one of the reasons why even small businesses and solopreneurs can take advantage of groundbreaking technologies.
Many innovators and startups in all industries no longer need to invest huge amounts of money in specialized equipment, tools, and people in order to deploy cutting-edge tech thanks to the many cloud offerings from companies such as Amazon, Microsoft, and Google.
About the Author:
Michael has been working in marketing for almost a decade and has worked with a huge range of clients, which has made him knowledgeable on many different subjects. He has recently rediscovered a passion for writing and hopes to make it a daily habit. You can read more of Michael’s work at Qeedle.
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