Integrating Wearable with EHR/EMR Systems - TechBlocks
Gather real-world and real-time health data and integrate it into a patient’s medical record.
Wearable-EHR interface represents new innovations, providing the opportunity to collect real-life and real-time health data with integration into a patient’s medical record.
Understand more about the Wearable Technology
Contact Us - Cloud Engineering Services
As they continue to grapple with supply chain disruptions and complexities, companies are increasingly turning to technology and automation to help them work through these challenges.
This approach has become even more important during the current labor shortage, where “throwing more people at the problem” is no longer a viable or affordable option.
Want to know more? Connect with our experts to create custom solutions that might interest you.
Software Engineering for Retail & Digital Commerce Companies
Data Engineering for healthcare is the process of measuring and managing data for finding effective solutions for your patients. It must be implemented in every organization for effective and smooth results.
Product Engineering & Digital Transformation Services - TechBlocks
The world is changing at an unimaginable pace, but the digital-tech market does it thrice as fast. These 3 custom software solutions provide the smartest and the most advanced technologies that surpass the brand’s desires.
Contact Us - Cloud Engineering Services
We’ve worked with global companies to build high-availability and redundant systems that have been stress-tested to handle over 250,000 concurrent connections from IoT Devices with redundancies and fail back for critical situations, lag or weak device connectivity.
Software Engineering for Digital Health Companies
Digital disruption has reached the healthcare sector, and with it comes an imperative for life-science companies to retool core technology to remain competitive.
5 Tips on How to Improve UX Design for Mobile Devices
When it comes to running a successful retail business, a website is no longer enough. Shoppers use their mobile devices 286 percent more than they do on the internet.
Techblocks construct cross-platform, regulatory-compliant mobile applications for retail businesses. In order to speed up the app development process, we use rapid prototyping and pure-native development languages. Read More to Know How we can help Retail Companies with Mobile App development.
Software Engineering for Retail & Digital Commerce Companies
Take a look at our Retail Next Accelerator. It includes pre-composed, best-in-class technology to assist you in increasing your speed to market, lowering operational and implementation costs, and increasing customer satisfaction. Powering Unique Digital Experiences Across all Business Models and Touchpoints Of Retail.
Wearable Biofeedback Device startup collaborated with TechBlocks on the development of the first clinically validated wearable with scientifically proven touch therapy that actively helps your body recover from stress and increase Heart Rate Variability.
While working with them, we were able to quickly modernize existing frameworks and make the most out of current technologies while resolving several issues.
Wearable Biofeedback Device startup collaborated with TechBlocks on the development of the first clinically validated wearable with scientifically proven touch therapy that actively helps your body recover from stress and increase Heart Rate Variability.
While working with them, we were able to quickly modernize existing frameworks and make the most out of current technologies while resolving several issues.
When faced with enormous client demand, businesses are frequently unable to provide it because of the insufficient capability of their their business model.
When Koodo Mobile, one of Canada’s most successful low-cost mobile phone companies, began to face several issues around it’s constantly rising user base, they contacted TechBlocks. Customers’ expectations necessitated expanding the modal capacity. Re-engineering a company’s business model was one of the strategies we used to meet the needs of the company’s expanding client base.
The necessity for cost-cutting in healthcare delivery, as well as a growing emphasis on patient-centric care delivery to promote digital health, are driving the expansion of the Healthcare Market.
However, the deployment of linked medical devices and accompanying infrastructure demands large investments, which is why IoT adoption is increasing in healthcare. This, combined with the healthcare expertise, is projected to stymie market expansion in the future years.
2020 posed a new challenge for businesses due to the COVID-19 pandemic, and companies had to adopt remote working models? A whopping 43% of companies even closed temporarily. The ones that did survive, 78% of them took solace in cloud-native models and Kubernetes environments. This can be judged because the cloud-native market saw average spending of $2.3 Billion in 2019.
With a CAGR rate of 25.68%, the cloud-native market size is expected to reach a value of $9.2 Billion by 2025. While they sound similar, cloud-native is the practice of working entirely on the cloud instead of building a data center and then migrating the data to the cloud, which is the cloud hosting methodology. So, what exactly is the difference, and why is cloud-native the superior option? Find out.
While cloud hosting is the conventional method of hosting enterprise data, cloud-native is the new normal of data access and storage, just as COVID-19 has changed things. The following are the reasons why businesses of all sizes should adopt cloud-native:
While many would argue that an on-premise server is an excellent investment due to the control it provides, there are concerns as well. For example, backups are less effective with on-premise servers, and in case of a cyber-attack or a natural calamity, all of it may be lost.
Cloud-native allows you to create backups and store them in several locations so that the data can be restored when the services of the cloud resume. Therefore, on-premise server installations have dropped by 6% to $89 billion globally.
As an organization grows, the challenges of expanding the operations also become extensive. While building data centers at all-new locations may seem easy, the original server is not expandable itself. As a result, data centers are not scalable and consume a lot of space and resources. According to a QTS report, there are 13 vulnerabilities that a data center poses. With cloud-native, the user has the flexibility to access the data in a more secure manner that is also easily scalable.
With data centers, the size, and resources of the service increase as the app or website development scales up. This can cost around $5-6 million, which is separate from the costs of development. Cloud-native allows you to develop the app/website in distributed systems and then bring it together when the need arises. This reduces the time to hit the market post-development, which is significantly longer with traditional development practice.
Furthermore, the additional resources are automatically decommissioned when the usage is complete, making the app/website light to operate and maintain in the long term. Add the adaptiveness with the Kubernetes environment, and cloud-native automatically becomes the go-to option for development.
Many data center migrations to the cloud do not come with security measures that are fully adaptive for cloud applications. This means that the pre-existing security measures with data centers are not as effective. This is solved with cloud-native; wherein all security measures are created directly only for the cloud. Furthermore, all the security measures with cloud-native are compliance and regulation friendly, and hence can be deployed almost immediately.
Most companies choose to build a data center when their data is too sensitive to be stored on a cloud-managed by somebody else. On average, it costs about $1,000 per square foot of area. And to top it off, they consume an enormous amount of power to work. An average data center costs $10-12 million per megawatt for an enterprise. With cloud-native, these costs can be reduced by up to 70%, with prices starting as low as $100,000.
Cloud-native had seen its fair share of challenges since the cloud hosting model arrived before and was implemented at a broader scale, with 31% of public enterprises stating it imperative. However, in 2021, cloud hosting is becoming outdated due to infrastructure requirements and maintenance costs. The following are the broad differences between cloud-native and cloud hosting:
As the table reveals, the cloud-native model adopts the advantages of cloud hosting, drops the costs and requirements, and further builds on that premise, making it a more all-rounder model for the development of apps and websites.
With 70% of US companies already adopting cloud-native architecture and a complete transformation by 2025, it is only a matter of time. Cloud-native packs all the features of its predecessors like higher uptime, lower carbon footprints and adds the benefits of reduced overhead costs and faster implementation.
To top it off, it is seamlessly accessible through remote locations for COVID-19 working models and yet manages to adhere to all security measures to prevent data breaches. It is thus worthwhile to migrate to cloud-native.
Though a relatively new term, MACH architecture has been quickly growing in popularity. MACH supports a highly composable environment that suits the needs of any dynamic platform, especially that of e-commerce.
MACH serves as the acronym for
MACH architecture allows e-commerce developers to make rapid and frequent changes to their platforms by making components of their digital solutions scalable, pluggable, and replaceable as per the business’ requirements.
This framework allows business users to develop and create content pages, update product information and other static and dynamic content without needing to rely on developers, freeing up developers to focus on features and functionality.
What with logistics and bottom lines, heading an online store or service is a tough job. Add to that the fluctuations in customer demand and purchase behaviors, and you have your task cut out. Availability of a product is not the sole factor for a customer to make a purchase anymore. They are on the lookout for newer and innovative experiences, too.
The outbreak of the COVID-19 pandemic has radically changed customer purchase behavior by adding another dimension to it: a personalized buying experience. Already reeling under the pressure of fierce competition in the e-commerce industry, businesses now are seeking to adopt innovative technological approaches to satisfy the ever-increasing consumer demands, while generating revenue.
One of the innovative technological approaches to have emerged in times of such rapid changes is MACH. Touted as a superior alternative to the traditional monolithic architecture, MACH improves upon the much-popular headless commerce approach.
Initially, product sellers overly depended on e-commerce marketplace giants like Amazon and eBay. Though these giants helped them dip their toes in the water, businesses — especially those with enough brand recognition — wanted to cut out the middleman for maximum ROI.
Building, managing, and updating e-commerce applications on their own proved to be highly expensive and time-consuming. This was primarily because e-commerce platforms followed a monolithic architecture, where the front-end (the interface part) and the back-end (the logic part) meshed together. Even subtle changes to the front-end used to cost significant development hours.
All that changed with the introduction of turnkey Headless Commerce platforms like BigCommerce and Shopify. They followed an architecture where the front-end was completely decoupled from the back-end, allowing designers to make significant changes to the UI without having to meddle with the coding part.
Headless Commerce platforms helped businesses that did not have a team of expert developers to set up their online stores and run them successfully.
MACH was first conceptualized in 2018 by the commercetools, which developed its Cloud-based platform using MACH. In 2020, it founded a non-profit organization called the MACH Alliance, aiming to help other firms implement this architecture.
Working on the motto “Future proof enterprise technology and propel current and future digital experiences”, MACH is a fast-growing organization with over 40 certified members, including AWS and BigCommerce, that actively support and promote MACH principles.
The MACH architecture is a combination of four innovative architectural approaches that have their own characteristics. You may have heard of each of these development concepts in isolation or combined in a lot of use cases. An architecture becomes MACH only when all of the four are combined.
Let’s review each of the four components of MACH Architecture.
Microservices, as the name suggests, are architectural approaches in which software is developed and implemented as small independent services.
The same company might not manage these services and they communicate with each other through well-defined APIs. An application following the microservices architecture is built as independent components that perform specific functions but pull off multiple functions when run together.
As an analogy to your home theatre system, your TV, cable receiver, and amplifier are all interconnected – each piece provides one service:
Each of these services talk to each other using defined protocols to deliver individual components of the big picture, such as watching the big game.
All services are loosely coupled and any of these services can be deployed, operated, altered, and scaled independently without the need to make changes in others.
Since they do not share a single code base, services do not need to share their codes. If any service becomes too large and complex over time, it can be broken down into smaller services, too.
Application Programming Interface (API) is a software intermediary that acts as a communication channel between multiple applications. Just like a waiter who communicates your order to the kitchen and carries your dish back to you, an API handles requests from one application to another.
The API layer in the MACH architecture allows microservices to communicate with each other without exposing one’s data to another by sharing only what is necessary for a particular set of communication.
In the case of an online store, there are multiple APIs at play, but the most evident ones are the login API and payment APIs.
Most online stores allow customers to log in using other services like Google, Twitter, or Facebook accounts. The login API connects the online store with the third-party account and uses the credentials to log into the store.
The customers also have the choice to make payment via credit or debit card, and digital services like PayPal. Here, the payment API connects with other payment services, which are essentially individual microservices to fetch the needed payment.
Another example is a travel booking aggregator like Kayak, which uses APIs to connect with the databases of various airlines and displays every flight information on a single page.
Unlike the code-first approach, where the developers first develop the core services and the APIs later facilitate the communication, an API-first approach involves the development of APIs as the primary step. These APIs can serve all applications; applications can be developed and managed for all OS, devices, and platforms.
Simply put, APIs are developed separately first and then integrated into an application to connect several microservices to make a wholesome whole. This allows multiple developers to work together on a larger project without stepping on each other’s toes or causing conflicts in code commits.
There are SaaS vendors who host the entire application on a single server. This Cloud-hosted approach is fundamentally very different from the Cloud-Native approach predominant in the MACH architecture.
Here, the microservices, which are essentially SaaS services, are hosted on different servers located possibly in different locations. The developers create a network between these services using software-based architectures for easier communication between them.
The biggest takeaway of this approach is that it enables horizontal scaling of microservices since the storage requirements of one do not affect the other.
The Headless approach decouples the frontend from the backend while they are connected only through APIs.
This approach suits applications because they require multiple front-ends (interfaces) that adjust to multiple devices through which they are being accessed.
The backend or the logical part, irrespective of the touchpoint, usually remains the same and need not be worked on every time you want to build a new interface.
The Headless approach allows you to communicate with your customers through any device, as it caters to appropriate front-ends where you get complete design freedom in that you can create front-ends for each device while keeping the backend the same for all.
For example, let’s say you have a brick-and-mortar clothing store as well as an online store. You also have your products listed on online marketplaces like Amazon.
Due to COVID protocols, you cannot allow customers to try on clothes in stores; so, you have an AR device that allows virtual try-on.
Users access the online store through desktop computers, mobile phones, and tablets of different screen sizes. Within those devices, the user may access the store through a native app, a website, or through integration with other platforms.
All these touchpoints need front-ends of their own tailored to meet the need of the user’s experience.
The rest of the backend processes like inventory, product pricing, images, 3D models, and database management are nearly the same across all devices. Designing separate applications that have their own back-ends for each of these devices is excruciating, costly, and time-consuming. That’s where headless commerce comes to the aid.
By separating the frontend development from the entire process, it allows you to optimize or innovate on the customer experience you wish to deliver.
The headless approach helps businesses to deploy multiple frontend experiences across a variety of devices, allowing them to connect with their customers at any touchpoint. This does not mean only those devices through which a browser is accessed, but also external devices like vending machines, IoT, AR/VR devices, and more.
Changes to the interface can be made in the nick of time, if any immediate alteration is needed, without interfering with the backend. This gives greater flexibility to the application.
Overall, MACH architecture is a functional mix of all the four above approaches to make any application highly scalable, easy to develop and build, flexible, and modular. New features can be deployed faster than ever without having to expand the code-base or interrupting the existing features.
It becomes easier for you to connect with your customers across multiple channels without having to build different applications for each.
MACH is one of those innovative approaches that take your business to new technological heights while allowing you to provide your customers with an improved experience. MACH merges four architectural approaches, in which the application is built by connecting Cloud-Native independent microservices through APIs. It also allows you to create multiple front-ends without having to alter the backend. There are many software vendors now who provide businesses with platforms that run on MACH architecture. Some future-oriented businesses have already begun shifting to this approach, and acting on their cue might prove beneficial to your business, too.
Leveraging Digital Strategy to be and stay competitive
Sal Sribar, Senior Vice President at Gartner, told a group of executives in 2017, “Many businesses are stuck running digital projects. Some of them are very large, but digital projects are not a digital business.” The idea of digital transformation has been around for a few years. Mr. Sribar stated in 2017 “Four years into the digital shift, we find ourselves at the ‘peak of inflated expectations, and if the Gartner Hype Cycle teaches us anything, a trough is coming. Disillusionment always follows a period of extreme hype.”
This quote exemplifies the frustrations many executives feel with pushing forward digital transformation. They know it needs to be championed and come to fruition, but there are stumbling blocks along the way, including a broad resistance to change. And taking the steps towards this transformation means developing a plan. Unfortunately, a 2017 CIO study found more than half of surveyed CIOs did not have in place a formal digital transformation plan. Many of the respondents noted they’re working on digital projects, but the lack of a plan is telling in terms of them not seeing the transformation as a broader cultural undertaking.
What Exactly is Digital Transformation
Digital transformation is essentially a disruption. And the need for this disruption is often coming from new entrants to the market, or competitors that are doing things differently and are grabbing customers.
It changes how a company operates, how employees look at their work, and the ways the company relates to its customers. It means adding digital processes, systems, and other tools to the company’s entire operations with the goal of enhancing customer experiences, reducing risks, and finding new revenue-generating opportunities.
Companies that embrace digital transformation are looking to build a more agile, customer-centric, and efficient enterprise. They want to be able to put in place new opportunities quickly (perhaps a new mobile app) to help them disrupt their market and capture customers. The pressure for this transformation is increasing because many industries are commoditizing, and therefore providers need digital tools to stand out. They have to offer the most streamlined app and ordering processes. They have to respond to customer queries through any type of channel in order to become known as the best service provider. Companies are desperate for differentiation.
The need for a digital transformation strategy is also influenced by the customer’s expectations for immediacy which are driven by a changing demographic that is growing up with mobile and connectivity. While some CIOs and other C-suite executives might find the customers’ expectations to be unreasonable, they’re still the customers, and that means firms must “adapt or die.” Operational flexibility, fast access to innovation, and an improved customer experience are all drivers of digital transformation strategies. And these must all come together harmoniously if firms are to succeed.
Why Digital Transformation Matters
Digital transformation is important because it will positively impact key metrics, such as customer lifetime value and operational efficiency metrics. It’s a strategy that pays dividends across the organization, as internal teams are more connected to each other and data, operational tasks occur faster, and customers are engaged more deeply. Digital transformation means accepting the realities of today’s connected consumers. It involves offering multiple channels of communication, blending the in-store and virtual experiences, using social to connect people to the brand.
Ask the founders and investors of Blockbuster if they wished they pushed forward with a faster digital transformation. There are myriad other cautionary tales of companies that held significant market shares but didn’t move in time with the pace of change. Consider a brand such as Nike that makes money selling shoes, clothing, and equipment. It’s moving into digital through its own branded fitness trackers and even the launch of connected footwear which will further inform athletes about their progress and training. The company also features Nike+, a social community with running clubs, coaching, and events that blend together digital data and real-world experiences. Such digital transformations on the customer-facing side allow companies to stay relevant with Millennials and even younger demographics.
Digital transformation matters internally because it involves centralizing data and then putting in place new ways to become more agile and innovative. It promotes involvement by everyone in the organization, by giving them collaborative tools to let their voice be heard and to perform their tasks in more efficient and customer-facing ways. It also means gathering input from employees, before, during, and after transformation, so it can be confirmed the new processes are working properly “on the ground.” Digital tools can promote more autonomy among staff members, as they’re empowered by information access, and have the context they need to make data-based decisions.
An attractive, intuitive web storefront and an engaging online presence can make all the difference between brisk or sluggish sales for an eCommerce website. When customers gain a personalized shopping experience, one-click checkout, and other benefits of an engaging shopping experience, sales and profits improve. So, every expense and effort going into the development, hosting, and deploying of such sites become worthwhile.
With more than 100,000 online stores created on Magento, the open-source platform has emerged as one of the most preferred e-commerce platforms to set up highly customized and unique online shops. Magento is written using the PHP programming language and leverages elements of the Zend framework and the model-view-controller architecture. Developers can implement core files and extend the platform’s functionality by adding new plug-in modules available from third parties.
Easy deployment, integration capabilities, advanced customization, numerous layouts, plug-ins, and choice of hosting options are some of the advantages that helped it become a chosen platform for eCommerce developers. The platform has powerful marketing, search engine optimization, and catalog-management tools. It is PA-DSS and PCI compliant, cloud-optimized, and mobile-friendly.
The platform caters to the needs of small businesses, mid-market organizations, and large enterprises. With a choice between the free Magento open-source and cloud-optimized Magento Commerce with a license fee, the platform holds a large share of the eCommerce pie.
Many challenges have cropped up over the years with this open-source platform. Updates, patches, and advanced versions from the diligent development team have addressed these issues successfully.
Let’s look at some of the top challenges and how they’ve been addressed.
Speed
Speed is of paramount importance in eCommerce. Slow page loading and broken links can make or break a sale or a merchant’s credibility, with most first-time customers not returning to the site at all. eCommerce sites built using Magento’s open-source platform usually load faster but have often faced roadblocks due to speed issues. The presence of a large number of files affects the website’s speed.
Increased page loading speed, catalog page viewing capacity, faster order processing, and faster checkouts were features delivered by Magento 2. For low speed, the mitigation efforts include configuring a cache, updating to the latest version, and discarding redundant extensions, among other improvements.
When products were not visible in their native category, they were usually out of stock or the caches and indexes were out of date. These issues were widespread with Magento 1.
One resolution was to change the inventory configuration for displaying products that were out of stock. The experts suggested reindexing, index: reset, cache, and enabling the “All store views” version.
Open-source platforms suffer from patchy documentation. The resources and reading material for Magento are scattered across many Internet sites, making it hard for developers to find source codes, resolutions, and training resources. The project timelines and costs go out of step due to this challenge.
Magento provides support services as and when developers raise a request. But the time spent is unnecessary, and Magento’s response is usually slow. In contrast, this issue is mitigated by the communities on the web that provides quick support and resolutions.
Coming up in searches and being in the top rankings are crucial to making an online shopping site successful. Although Magento comes up in basic searches, it is wanting on many SEO parameters.
SEO has considerably improved in Magento 2 version. But it is still a good idea to implement additional SEO best practices, make your site fast and functional, and invest in content marketing to increase organic and inorganic growth.
With advanced features and capabilities such as security updates, bug fixes, third-party updates, and integrations, businesses eventually have to upgrade to the latest version of Magento. Still, the upgrade itself is not free of challenges. Enterprises often encounter performance issues and even breakdowns while updating. There have been instances of loss of data due to migrations to the new Magento version.
At the beginning of the upgrade, a well-laid strategy and an experienced solution provider are required. A reliable technology partner can help you gain tangible benefits: improved performance, better testing framework, and high quality of code.
Magento’s free code is relatively easy to deploy and customize. As a website owner, one is responsible for the necessary maintenance, keeping the code updated, keeping up with essential security patches, and migrating to the new version on time. Still, more advanced implementations could throw up errors after deployment or stop the development work altogether, until a Magento specialist evaluates and fixes the problem.
The Magento developer community has grown over the years, but free resources can only solve some problems. For custom code, better UI/UX, building customized extensions, and upgrading hassle-free, certified Magento developers and an experienced team can mitigate risks, prevent data losses, and minimize downtime.
The installation process has many issues, as it gets stuck, and errors of files and extensions crop up. Incorrect configuration settings could weaken the site’s performance.
Migration to the latest version would be required, besides changes to settings and code. There are solutions such as fixes, codes, and commands to each of these issues distributed across various websites, blogs, and social media posts.
The Magento 2 version resolved the problems with multiple admins, blank admin page error, and slow admin logins, but new issues kept cropping up. The inability to login to the admin panel after incorrect login entries was because most browsers allow only real domains to collect cookies.
The solution was to write a few lines of code into the Magento file to fix this issue.
There are challenges to adopting newer extensions that are often costly and take time to install. There could be errors when installing Magento extensions, and the installed extensions do not display at the frontend.
This issue can be resolved by relocating the files and deleting the cache. Ensuring extensions .phtml, .xml, and .css files are in their exact locations achieves these goals.
Data does not mean only the customer’s financial information but also the website’s code and customer base. In October 2021, the Magecart cyber gang targeted two dozen unpatched vulnerabilities in third-party Magento plug-ins. They used different strategies, including exploiting the extensions’ Hypertext Preprocessor (PHP) vulnerabilities to breach various stores. Many such cyberattacks have occurred because of failing to apply the latest security patches and not upgrading to the latest version.
The new security features in Magento 2 version help prevent data loss but are not foolproof, as is the case with any other security feature. Yet, upgrading to the latest version has security benefits.
Magento has a global community of implementation partners, specialists, and developers that help enterprises and individuals build and optimize their valuable eCommerce store that generates large volumes of customers and sales.
TechBlocks–a leading digital product development firm with its extensive experience, strong execution discipline, and “customer first” attitude–will be a valuable partner in your journey to build and launch your successful eCommerce store.
With 2022 right around the corner, it seems only fitting to talk about what the future may hold for technology. Most people alive today have never seen the unprecedented level of change come as quickly as it has, leading to a level of uncomfortableness for businesses and consumers alike.
As a company that develops technology for some of the world’s leading companies, we have our ear close to the ground and our sights set on the future. We’re excited for what the future holds, and these are some of our 2022 technology predictions.
2020 started off the year with a massive transformation into Work From Home as many companies scrambled to deal with the fall out of the COVID-19 pandemic. As the dust starts to settle and many countries are seeing impressive vaccine penetration rates, the lines of Work from Home will evolve and become even more complicated.
While some companies move to a Work from Anywhere model, others may move back to a hybrid model of part-time in the office and part-time remote. This is going to lead to a de-densification of historically crammed office towers and office space, leading to a growth of mixed-use real estate, with office towers converting some floors into apartments, condos, or hotel spaces.
To continue to deal with remote work situations, employers are going to need to pay special attention to security concerns in environments that are full of devices and equipment they do not control.
Will we see employer-provided Internet connections specific for work devices at home? Will we see services like Windows 365 and Flex1 become more mainstream so IT departments can keep higher control of security?
We bet on virtualization leading the way for environments that require a higher level of security for remote devices.
10 years ago VR platforms like Oculus were just starting to emerge on the market, and it’s hard to believe that Google’s first attempt at augmented reality, Google Glass is almost 9 years old. Back in those early days, you needed to have a top-of-the-line desktop PC to run a VR headset and a heavy cable running out of the equipment, much like being jacked into the Matrix.
Today’s VR equipment is standalone and does not require a PC to act as a host. The cost of equipment is falling fast and is on par or better positioned than most smartphones with similar specs.
VR and AR wearables will continue to grow and reach a larger audience outside of core technophiles, gamers or enthusiasts.
Our prediction, these technologies will find a home in education and as assistive devices for those with physical or mental barriers. Companies like VRCity (Delphi Technologies) will find new and unique training opportunities when physical training is costly, dangerous, or otherwise prohibitive.
In addition, integrated augmented services will start showing up on other devices, like your TV or smartphone with companies like DroppTV building augmented and integrated shopping and e-commerce experiences.
As with Work from Anywhere, many health providers have learned that they do not need to be in their clinic full time anymore, and can comfortably deliver health advice from their PJ’s, their cottage, or anywhere with an Internet connection. Other professions are realizing the same thing and the shift towards remote service will continue to grow.
This is not without its problems as many health care providers have taken this remote healthcare position too far that is counterproductive towards providing quality health care to their patients.
We’ll likely see a course correction in 2022 where clinics begin encouraging more in-person appointments augmented by remote follow-ups for routine things like medication refills.
Remote health, in particular, requires a level of trust in technology to protect Doctor/Patient Confidentiality or Lawyer(Attorney)/Client privileged conversations. While end-to-end encryption is becoming more mainstream, not all technology is created equal. Some solutions are confusing to use creating frustration for the patient.
Many of the solutions we see today are a rush implementation to fill a need at a point in time. Our prediction, 2022 will lead to early maturity of remote health care solutions, including better video and audio integration, electronic medical records, and remote prescription refills.
With 5G penetration quickly rising and data-integrated devices like parking meters, cars, light switches and home appliances becoming more commonplace, we’re likely to start seeing everything coming with an internet connection built-in using WIFI, 5G or other UWB technologies.
In 2022, we’ll likely see greater control of our lives via smartphones and smartwatches for everything from access control of our houses and offices, but also remote control of our cars. Phones, like the Google Pixel 6 and Samsung Galaxy S21 come with built-in UWB radios allowing the phone to be used as a remote key to unlock the owners car in proximity to the car without needing an internet connection.
With this, we’re likely to see greater machine-to-machine (M2M) integration, allowing our cars to talk to other cars on the road, our appliances to talk to our power meters to manage peak vs. off-peak usage, and nearby notifications, and ultra-integrated data services.
As I am writing this, I am reminded that I only really use a laptop or formal computer in the context of work. My primary method of communication, information sharing, and education is my smartphone.
Like many people, a full-sized desktop, laptop, convertible devices or tablet does not serve a material purpose other than watching videos or working.
2022 will likely be a year of decline of standalone devices with a potential increase in convertible or multi-function devices, foldout large-format phones, or deeper integration with smart TV’s to take the place of traditional computers.
When COVID-19 first emerged, people were forced into their homes, to shy away from the public and become recluses within their own homes. With each wave of COVID passing and restrictions loosening up, we saw greater rates of people enjoying the outdoors. Campground reservation numbers sored beyond pre-pandemic levels creating shortages. The number of people outside walking, hiking, or playing recreational sports seemed to go leaps and bounds beyond anything we’ve seen in the last decade.
As people get bored of staying at home, we’ll see a great disconnect from home-based technologies as people set their sights on other forms of entertainment.
We’re also seeing attitudes shift on the usage and retention of persona data and calls for Surveillance Capitalism to fall. Users will expect greater transparency in how their data is used and how it is collected with a right to disconnect or delete their data at their request from any company they do business with.
This will likely lead to a continued slowing of growth or a decline in users on mainstream social media sites and a shift towards consumption-based payment models.
Machine learning is an application of AI where outcomes are predicted in advance, and the technology effectively learns and improves over time. This dynamic occurs without the need for human intervention, as machine learning is able to process data and pull insights on its own. Machine learning as a service (MLaaS) is a broader term of cloud platforms that can automate various processes. This can include data processing and evaluating models along with outputting predictions. Two of the leading platforms for MLaaS are Microsoft Azure and Machine Learning on Amazon Web Services. Each offers users speedy modeling training and easy deployments without the need for extensive data science experience. And both platforms hold the promise of helping firms to see their data as a way to look predictively towards (likely) future events, not just analyze what has already occurred.
Machine learning applications are moving into various industry applications. Google is utilizing machine learning to predict flight delays based on data points including location, weather, and late aircraft arrivals. The tool will compile this data and enable the flight to appear as “delayed” on booking and status engines when it reaches a certain likelihood threshold.
Microsoft’s Azure platform is used by UK-based Callcredit to determine if borrowers are at a higher risk of default. Callcredit utilizes Azure’s capabilities to predict problems with credit rating assessments and predictively spot fraudulent applications. It offered this enhanced machine learning to its customers such as credit card companies to help them avoid millions in bad debt. It’s also used by North American Eagle in their bid to break the land speed record. They’re using Azure Machine Learning to process data sets about speed performance in completely new ways in record time. The group uses this data gleaned from prior and current speed runs to build predictive models to help them increase speed while ensuring the safety of the human driver.
AWS’ platform is built with more automation and accessibility so that it appeals to a broader group of individuals who might not possess data science skills. With Azure’s Machine Learning, there is an assumption that the user understands modeling and the algorithms, but appreciates a more intuitive and friendly GUI.
Machine Learning for “The Masses”
Both of the platforms are seen as a broader “democratizing” of machine learning, similar to what occurred with Big Data analytics. Machine learning is poised to become a massive business, with a market reporting stating growth of the industry is expected to move from $1.41 billion USD in 2017 to $8.81 billion by 2020, a CAGR of 44.1%.
Automation and easier to use platforms such as Amazon’s SageMaker and the Microsoft Azure Machine Learning Studio are offering machine learning tools to workers with little or no formal data scientist training. Even with automation, getting the most out of either platform requires human intervention to pick the right algorithms and craft models that are most likely to create predictive results. Firms looking at either the AWS or Azure platform should consider working with an IT consultancy that boasts experience with both choices, and can provide guidance on the right solutions to fit needs.
Comparing and Contrasting
Microsoft Azure and Amazon Web Services (AWS) are two of the core platforms for conducting machine learning on data held in the cloud. Amazon’s solutions is known as Amazon Machine Learning and uses algorithms to spot patterns found in a company’s data. These models are then used to generate predictions. The platform is highly scalable and can create billions of daily predications, and with no hardware or software investment required, firms can adopt a “pay as you grow.”
AWS also offers SageMaker, a fully managed service for data scientists who want to create machine learning models using their own data source and a choice of several learning algorithms. It also integrates with language frameworks including Apache MXNet and TensorFlow. AWS is attracting users to SageMaker with the trusted reputation of the infrastructure and the ability to leverage the entire full stack on AWS, all the way up to deployment. AWS’ additional benefits include no setup costs, speed of model creation due to automation, and the proven Amazon architecture. Drawbacks include limited prediction capacity and the amount of automation mean it can be difficult to use it as a machine learning trailing tool. Meaning, the automation does “too much” and leaves fewer tasks for a person trying to learn the underlying methodologies at work.
Each platform does have different data location requirements, with Amazon users required to have data stored in an AWS store before conducting machine learning modeling. With Azure, smaller data sets can be pulled from other sources (including AWS) but bigger data sets must reside in Azure.
Compared to Amazon’s platform, Azure is often seen as more flexible in terms of algorithms. This is a core benefit of Azure, the ability to support dozens of methods of data classification. Microsoft provides a “cheat sheet” to help data scientists to pick the right algorithms for the particular use case. So for example, the user might be guided towards supervised or unsupervised algorithms, logistic regressions, neural networks, or Poisson algorithms. The platform also offers the Cortana Intelligence Gallery that is a community-provided group of machine learning tools that are available to the broader Azure user community. The breadth of algorithms offered by Azure can make it a more appealing choice for experienced data scientists who perform more complex modeling. A drawback of Azure for machine learning is it’s not the best choice for speedily implemented projects, especially compared to AWS.
AWS and Azure both offer their own APIs that aid users in text analysis. For example, users can leverage Amazon Transcribe which is a tool for recognizing spoken text that can transcribe call center data or audio archives. Another tool is Amazon Polly which turns text into speech, which then allows companies to create unique voices for chatbots. Amazon Translate conducts translations using neural networks to convert multiple language into and out of English. Azure offers a similar group of APIs which it calls Cognitive Services which also offers speech and language tools for translate, speech to text, voice certification, and other capabilities.
The TechBlocks Machine Learning Advantage
TechBlocks can provide guidance to the technical staff that needs to validate and test cloud machine learning services. Making the best MLaaS choice for a business can be tricky, and requires a careful review of both short and long-term data analytics needs. TechBlocks’ experienced consultants understand the benefits of both Azure and AWS implementations, and can prepare tailored recommendations for every client. We’re a Gold Partner with Microsoft, a certified AWS integrator, and understand how to leverage both platforms for maximum gain. IT staff responsible for validating services on Azure or AWS should contact TechBlocks to discuss the best options for their cloud initiatives. Visit www.tblocks.com to learn more.
The last two years posed new challenges for businesses due to the COVID-19 pandemic, and companies had to adopt remote working models. A whopping 43% of companies even closed down temporarily. The ones that did survive, 78% of them took solace in cloud-native models hosting and technology.
With a CAGR rate of 25.7%, the cloud-native market size is expected to reach a value of $9.2 Billion by 2025. While they sound similar, cloud-native is the practice of working entirely on the cloud instead of building a data center and then migrating the data to the cloud, which is the cloud hosting methodology. So what exactly is the difference, and why is cloud-native the superior option?
While the two terms both mention the word cloud, they are different in their approach. Cloud Hosting is more like traditional infrastructure in that you are renting server space, network infrastructure, or other resources from a company. This would be similar to the dedicated hosting model that was popular with small and medium-sized businesses in the early 2000’s. This is really no different than building your own data center where you occupy physical equipment – the difference is it’s someone else’s equipment and facilities.
Cloud-Native, on the other hand, embraces the virtualization of infrastructure and computing platforms into virtual machines with virtual-network connectivity, virtual firewalls, and other cloud-native infrastructure.
As mentioned above, businesses have typically had a few options for hosting and managing their technology. On-Premise, Cloud Hosting, and Cloud-Native all have their benefits, depending on your business objectives and largely driven by regulatory compliance.
In this article, we’ll talk about 5 reasons why you should consider adopting a cloud-native approach to your technology ecosystem.
On-Premise servers require a lot of consideration from power availability and backup batteries, network redundancy, cooling equipment, physical security, and more.
Cloud providers like AWS, Azure, and GCP maintain robust data centers globally that help distribute your platforms across multiple data centers or zones, and across different physical equipment ensuring uptime and reliability is maintained.
As an organization grows, the challenges of expanding the operations also become extensive. While building data centers at all-new locations may seem easy, the original server is not expandable itself. As a result, data centers are not scalable and consume a lot of space and resources. According to a QTS report, there are 13 vulnerabilities that a data center poses. With cloud-native, the user has the flexibility to access the data in a more secure manner that is also easily scalable.
Cloud-native allows you to develop the app/website in distributed systems and then bring it together when the need arises. This reduces the time to hit the market post-development, which is significantly longer with traditional development practice.
Furthermore, the additional resources are automatically decommissioned when the usage is complete, making the app/website light to operate and maintain in the long term. Add the adaptiveness with the Kubernetes environment, and cloud-native automatically becomes the go-to option for development.
Many data center migrations to the cloud do not come with security measures that are fully adaptive for cloud applications. This means that the pre-existing security measures with data centers are not as effective. This is solved with cloud-native; wherein all security measures are created directly only for the cloud. Furthermore, all of the security measures with cloud-native are compliance and regulation friendly, and hence can be deployed almost immediately.
Most companies choose to build a data center when their data is too sensitive to be stored on a cloud-managed by somebody else. On average, it costs about $1,000 per square foot of area. And to top it off, they consume an enormous amount of power to work. An average data center costs $10-12 million per megawatt for an enterprise. With cloud-native, these costs can be reduced by up to 70%, with prices starting as low as $100,000.
Cloud-native had seen its fair share of challenges since the cloud hosting model arrived before and was implemented at a broader scale, with 31% of public enterprises stating it imperative. However, in 2021, cloud hosting is becoming a thing of the past due to the infrastructure requirements and maintenance costs. The following are the broad differences between cloud-native and cloud hosting:
As the table reveals, the cloud-native model adopts the advantages of cloud hosting, drops the costs and requirements, and further builds on that premise, making it a more all-rounder model for the development of apps and websites.
With 70% of US companies already adopting cloud-native architecture and a complete transformation by 2025, it is only a matter of time. Cloud-native packs all the features of its predecessors like higher uptime, lower carbon footprints and adds the benefits of reduced overhead costs and faster implementation.
To top it off, it is seamlessly accessible through remote locations for COVID-19 working models and yet manages to adhere to all security measures to prevent data breaches. It is thus worthwhile to migrate to cloud-native.
Cloud migration helps your organization to modernize mission-critical applications by increasing agility and flexibility.
In 2021, worldwide end-user spending on public cloud services is forecast to grow 23.1% to a total of $332.3 billion, according to the latest forecast from Gartner.
Gartner also predicts the future of cloud and edge infrastructure by showing the picture of changing the enterprise infrastructure, new opportunities, and new threats for I&O leaders.
According to Gartner’s prediction, enterprise infrastructure will be connected by more than 15 billion IoT (Internet of things) devices by 2029. So, if the I&O leaders don’t properly coordinate when and how they will be connected then all the trusted, untrusted, corporate, and guest devices can pose a risk to the enterprises.
Also, this is common for IT organizations to find the IoT devices on their networks and they can install, secure, or manage themselves. If the enterprises will segment or isolate the devices, then they can save themselves from cyberattacks.
A dimensional research survey found that less than 5% of cloud migration had been successful and more than 50% were over budget or delayed because of the lack of knowledge or well-developed process.
But if you don’t want to repeat the same mistakes as others did then you can explore the below cloud migration readiness checklist for migrating the IT system.
Consider the intended checklist below and address it to maximize your chances of successful cloud migration.
Identify a compelling business reason for migrating to the cloud
Identify and reach out to business stakeholders, IT, executive sponsors throughout your organization for a funding commitment. Ensure you have an executive champion who can help clear roadblocks and other barriers
Do you have the right internal staff to complete a migration project? What resources will you need?
Find a Microsoft Partner who can help with your migration project to help reduce time to market.
Evaluate your cloud readiness by using the Strategic Migration Assessment and Readiness Tool
Develop a plan for cloud adoption & migration by establishing the objectives and priorities
Create a personalized business case by using the Total Cost of Ownership (TCO) calculator for potential savings estimation and cost planning
Encourage your internal team to complete the following Azure certifications;
to help ensure you are setup for success and can manage your migration long term
Discover and assess your current application server environment and critical dependencies
Assign a project manager and business analyst to the project to develop a detailed scope, project roadmap and detailed work packages
Read and identify your migration & digital estate modernization options such as rehosting, refactoring, rearchitecting
Set up an Azure landing zone designed to accept the migrated workloads (with some important components such as – networking, identity, management, security, and governance)
Train your migration team and check their prior experience in the migration process
Secure your Azure workloads by designing for the following aspects such as – (i) identity & access, (ii) app/data security, (iii) network security, (iv) threat protection, (v) security management
Assess and migrate with low complexity workloads as a pilot for successful migration journey
Run a test migration by using Azure migrate that doesn’t impact on-premises machines & then migrate groups of physical or virtual servers at scale
Use Azure database migration service for database migration from on-premises to Azure
Monitor Azure cloud spend and recommend the cost-saving options by using the tools
Explore and visit the Azure security center, policy, and Azure blueprints after migration to ensure the resources are deployed in a consistent and repeatable way
Monitor the health performance and enhance the security of your Azure apps, infrastructure, and network
Backup plan for critical data and ensuring disaster recovery objectives
Say “blockchain” and the word that most frequently comes to mind is “cryptocurrency”. And with good reason. Blockchain technology was invented to support the invention of the world’s first-ever cryptocurrency: Bitcoin.
Launched in early 2009 by someone calling themselves Satoshi Nakamoto, Bitcoin remains the world’s most valuable cryptocurrency. Valued at over $40,000 in April 2022, experts predict that the crypto will cross $81,680 in 2022, and $420,240 by 2030. Without blockchain technology, Bitcoin would not exist, much less achieve such stunning success.
And yet, blockchain is about more than just Bitcoin or cryptocurrencies. Over the years, a number of new applications and use cases have emerged for blockchain technology. All kinds of organizations can leverage its power for the use cases that matter most to their businesses and customers. They can also automate processes, minimize supply chain disruptions, protect data and intellectual property, and reduce fraud. Ultimately, blockchain provides powerful capabilities that empower businesses to cut costs and boost their bottom line.
This article explores these benefits of blockchain in detail. It also pulls back the curtain how blockchain works and how organizations can determine if they need blockchain for their needs. So, if you are a product owner, developer, or organizational leader curious about blockchain and its potential, this article is for you!
What is Blockchain?
Blockchain is a distributed ledger technology (DLT) where all transactions happen on a decentralized peer-to-peer (P2P) network and are stored in a decentralized ledger. Simply put, blockchain is a type of database that stores transactions and related information in a digital format. The database is distributed and decentralized, meaning it exists on multiple nodes on a computer network.
Blockchain technology records transactions in a secure way. These transactions may be orders, payments, accounts, escrows, stock splits, or anything else involving multiple parties making some kind of a deal. Transaction participants can confirm these transactions and track the assets involved in the transaction, including intangible assets like cryptocurrencies, patents and intellectual property, and tangible assets like land, buildings (e.g., homes), or cash.
Over the years, blockchain technology has evolved from its original crypto/Bitcoin roots to now incorporate dozens of real-world applications and use cases. For instance, blockchain is used for international fund transfers, capital market settlements, public voting systems, accounting and audits, supply chains, insurance claims, and much more.
Regardless of its purpose or application, every blockchain network comprises of the following few key building blocks:
DLT is the primary foundation of any blockchain network. All transaction participations and permissioned network members can access the ledger and its transaction records. Every transaction gets recorded and this happens only once per transaction.
This is how blockchain consistently maintains an immutable record of transactions. It also eliminates duplicate records that are a common problem on many other networks and databases.
The blockchain database collects information from transactions in groups or blocks. Each block can hold a set of information and has a specific storage capacity. Numerous blocks are chained together, hence the name blockchain. Moreover, strong cryptographical protocols protect these blocks from tampering and data breaches.
Smart contracts are a unique feature of blockchain. A smart contract is a set of rules and conditions stored on the blockchain and executed automatically during a transaction. Smart contracts bring greater predictability, trust, confidence, and speed to transactions.
Many kinds of transactions rely on smart contracts on a blockchain network, including:
The blockchain ledger is both shared, which allows multiple participants to view and access it, as well as immutable, which prevents anyone from changing or tampering a recorded transaction.
If a particular record includes an error, say, because someone tried to change it deliberately or maliciously, the error must be reversed. To do this, a new transaction must be added to the ledger. Once this is done, both transactions will become visible on the network and remain there permanently.
Blockchain works the same way regardless of transactions, users, or applications. Here are the processes involved in a typical transaction:
The blockchain’s operation starts when a user requests a transaction. The transaction is entered into the network and shows the movement of the associated asset that all participants can “see”.
For instance, an individual may transfer some funds to a different country or a hospital may update some patient records or a media company may distribute premium video content to consumers.
The blockchain’s P2P network consists of multiple computers known as nodes. These nodes are scattered all over the world, giving the blockchain its inherently distributed nature. The requested transaction is entered into this network. These nodes use algorithms to solve a series of complex mathematical equations in order to validate the transaction and confirm the identity of users.
Once the network confirms that the transaction and user are both genuine, the information is clustered into blocks. A block can store multiple transactions and all their relevant information until its storage capacity is reached. When a block becomes full, it is closed and linked to the previous full block to lengthen the chain of information. No other block can be inserted between two existing blocks. A new block will then be created to record new transactions. This new block will also be added to the chain once it becomes full.
After a transaction is added to the existing blockchain, it is said to be completed. At this point, it becomes permanent and immutable. Further, the network’s transaction verification mechanism makes it near-impossible to hack the system, disrupt transactions, or modify data.
Blockchain was first proposed as a research project in 1991. It then entered the mainstream in 2009 when Bitcoin was launched. Since those early days, the use of blockchain has exploded and the number of blockchain applications has increased exponentially because it delivers numerous benefits.
Blockchain in conversation usually refers to public blockchain technology, such as Ethereum. For enterprise, private blockchain ledgers can be setup to provide a secure, purpose-built application. Companies like Microsoft offer pre-built Blockchain Services on their Azure platform, making it easier for companies to adopt blockchain.
The benefits of using enterprise blockchain can be compelling for businesses to consider adopting.
One of the biggest benefits of enterprise blockchain is that it offers advanced security and trustworthiness compared to other databases or networks. One reason is that it is a “members-only” network, which means that its records are confidential, and only visible and accessible to authorized members.
Further, each entry on the database is encrypted, stored on a permanent block, and confirmed by P2P networks. The ledger itself is tamper-proof, thus guaranteeing the fidelity and integrity of records. All these qualities allow participants to trust blockchain transactions without having to involve a third party or a central clearing authority.
In addition to its security and trust benefits, blockchain also offers an unbeatable combination of transparency and privacy. All permissioned members get a single source of the truth, so they can see every transaction from the start until it is validated, accepted, added to a block, and finally completed. At the same time, no one outside the network can see the data, protecting it from prying eyes and potential breaches.
All validated transactions are recorded permanently on the shared ledger. In addition, all users collectively control the database and provide consensus on data accuracy. So, there’s no chance for any user – including system administrators – to modify, manipulate, or delete a transaction. Traditional databases and networks don’t provide this level of transparency or immutability.
Blockchain technology has a lot of potential to create tangible value for organizations. It is already used in a number of industries including:
Over the coming years, enterprise implementations will proliferate to even more sectors. These implementations will deliver all these benefits to organizations and their stakeholders:
Virtually any kind of transaction can take place on a blockchain. The technology removes the need for third parties to validate, verify, or reconcile transactions. Moreover, it helps automates many processes with the help of data blocks, algorithms, and smart contracts. All these qualities can reduce IT, labor, and data management costs for businesses.
For instance, businesses that accept credit card payments may incur a small fee that’s imposed by banks or payment-processing companies. But blockchain and cryptocurrencies require no centralized authority so there’s no middleman or associated fees.
A blockchain network is capable of tracking all kinds of transactions and assets since every transaction gets recorded and its data always remains immutable and available for view. This is why a real estate company can track property ownership and the transfer of this ownership at any time during a transaction.
Similarly, a food products company can trace its products’ lifecycle all the way from farm to plate. Even non-profits can use blockchain to trace their donations, and track where funds are coming from and where they are going.
Reconciliations are required in many kinds of transactions, especially if there are multiple parties holding out-of-date or slightly different information. These differences make it harder to trust the transaction or each other.
Enterprise blockchain helps resolve this common challenge. Since it is based on a distributed ledger that’s shared among authorized members, everyone can see the same data at any given point of time. Moreover, smart contracts establish the terms of the transaction which are executed automatically.
All of this makes it easier to facilitate and verify transactions, while removing the need for time-wasting reconciliations or duplicate record-keeping.
Organizations all over the world and in every industry worry about cyberattacks and data breaches. Per the Identity Theft Resource Center’s 2021 Data Breach Report, there were a record 1,862 breaches in 2021, up 68% from 2020 and well exceeding the previous record of 1,506 set in 2017.
According to IBM, the average cost of a data breach has gone up from $3.86 million in 2020 to $4.24 million. These numbers reflect a grim picture of a year where high-profile cyberattacks targeted all kinds of companies, including large oil pipelines, financial companies, healthcare organizations, and even social media firms like LinkedIn and Facebook.
Blockchain protects data from data breaches and exfiltration by ensuring that only authorized users can view or access it. Further, the data is always stored in an encrypted format and no one can modify it. Even if a hacker does manage to get their hands on a copy of the blockchain, they can only compromise a single copy of the information rather than the entire network.
Blockchain’s built-in encryption also helps prevent fraudulent transactions in a wide range of areas, including money transfers, trading, voting, and real estate. It can also help authenticate and trace physical goods to prevent their counterfeiting – a common issue in the pharmaceuticals, luxury retail, electronics, and art industries.
The technology can also combat a serious problem for countries everywhere – money laundering. Since blockchain networks can trace funds at every stage of a transfer, it’s harder for criminals to hide the source of their funds, which is exactly what they do to convert dirty money into clean (or laundered) money.
By preventing money laundering, blockchain enables governments to tackle other crimes that rely on the availability of laundered money. These include terrorism, human trafficking, and drug trafficking.
A blockchain network provides reliable record-keeping and trustworthy data storage. This enables businesses to identify and verify the identities of their clients and customers – a system that’s commonly known as “Know Your Customer” (KYC).
In this article, we have seen how, as a decentralized, secure, and immutable form of record-keeping, blockchain is unrivaled by any other kind of technology. However, blockchain is far from perfect. For one, it can be fairly complex and expensive to implement, making it harder for smaller firms to adopt it for their use cases.
Another challenge is that the regulatory regime around blockchain is uncertain, which is a worrying prospect for organizations with a heavy compliance burden. Transaction speeds are also limited on blockchain networks since blocks have to validate and confirm each transaction before it can be finalized.
Finally, there is a shortage of experts who can help companies with the implementation of blockchain networks, making it harder to adopt the technology. TechBlocks is one such technology partner that can help businesses implement public or private blockchains.
For all these reasons, organizations should not impulsively jump onto the blockchain bandwagon. Rather, it’s worthwhile to first do a self-assessment to gauge their need for the security, data immutability, and transparency that blockchain can provide.
It’s may be useful to review some of the questions below to understand if you can benefit from blockchain.
A company that collects and manages a lot of sensitive data such as customers’ personally identifiable information (PII) or patients’ healthcare information needs to safely store and protect this data.
They must also comply with stringent laws or regulations on information security and consumer privacy. In these cases, blockchain can be very useful.
Blockchain is also a good choice for organizations that need to protect valuable intellectual property or other kinds of intangible assets. Since assets can be traced at any time on the network, it’s almost impossible for fraudsters to steal a patent or make illegal copies of a brand asset.
As we have seen, the decentralized nature of blockchain allows organizations to carry out and trust transactions without involving a third party such as a central clearing authority. Many organizations can carry out transactions without middlemen if they could verify the transactions and get assurance that all involved parties can be trusted. This includes companies in real estate, banking and finance, healthcare, media, energy, and even government.
Without blockchain, organizations have to maintain a separate database for their transactions and data. A blockchain’s shared database is a consensus-based system with instant traceability and full transparency from end-to-end. Plus, all transactions are time- and date-stamped, and only authorized users can see them. All of this increases trust and transparency across the entire network.
Blockchain’s transparency makes it easy to trace all kinds of physical assets through supply chains. Manufacturers, suppliers, and logistics companies can track products or raw materials in real time. They can also record the origins of materials, verify product authenticity, and confirm that products remain safe for consumption.
The growing popularity of blockchain means that global spending on the technology is expected to reach a staggering $17.9 billion by 2024. This represents a healthy CAGR growth of 46.4%.
Organizations in all sorts of industries are becoming more aware of the power and potential of blockchain. And yet, what we are seeing now is just the tip of the iceberg. In the coming years, many more blockchain applications will be developed. And when that happens, blockchain will help solve many real-world problems and enhance the human experience. And that can only be a good thing!
A product roadmap provides end-to-end visibility into timelines, including the sequencing of priorities, that support your product-based initiatives. It is the distillation of your vision for a product and how it connects the near-term product changes to the mid-term strategic milestones.
Even in a highly dynamic setting, a product roadmap is the ‘why’ behind ‘what’ you are building. The type of roadmap that you create essentially echoes the requirements of your organization, stakeholders, and customers. This article discusses feature-oriented roadmaps in detail. The other most used flavors of product roadmaps are Goal-oriented, Theme-oriented, and Release-oriented.
In an increasingly volatile market, organizations are scrambling to plan their future product portfolios and create reliable feature-driven roadmaps. With the technological landscape getting inundated with innovative products, it is easy to be misled by non-essential features, which may not align with the product vision and strategy.
The erstwhile processes of building feature roadmaps have now paved the way for a more purpose-driven, customer-centric approach. While ensuring that your roadmap is focused on this approach, the challenges are around determining the business value that a new set of features represents, that is, whether they are nice-to-have-but-not-essential addition to the product capabilities.
As a product manager, you can start by asking these key questions about the roadmap that you are building:
Through this approach, managers attribute weightage to each proposed feature, which is then evaluated and given a score. Since the score corresponds to priority, a product or feature with a higher score will likely be integrated into the product roadmap sooner than a product or feature with a lower score.
Further, before enlisting features to be integrated into a product roadmap plan, it is crucial that feedback from your customers and end-users is collated and optimized for prioritization. With customer experience being a key market differentiator, non-compliance may result in a loss of revenue.
For a Product Manager, prioritizing features can be a daunting task. Even the largest organizations are constrained by time and resources, with new features being added to multiple products as an ongoing activity. Invariably, without effective roadmap prioritization, new features’ development will continue to stay in the pipeline.
Surveys are the most effective way of collecting and analyzing usability feedback and gathering a range of metrics. They are largely categorized into Product feedback surveys, Website feedback surveys, and Micro surveys.
These feedback-driven surveys enable the product team to evaluate the mismatch between what they believe is a cutting-edge feature and what the customers think about the usability and experience that the feature offers.
A product team can use frameworks – such as Objectives and Key Results (OKRs), Reach, Impact, Confidence, and Effort (RICE) Scoring models, and Must-have, Should-have, Could-have, Won’t-have (MoSCoW) – for prioritizing features in the product roadmap.
New ideas for products, features, or services must ideally be sourced from customer feedback using surveys, as discussed earlier. The first step to building a successful roadmap is integrating strategy with your road-mapping process. Generally, the top-down strategic planning and communication approach serves as a touchpoint for the executive leadership, development, marketing, and support teams to get on board with the strategy.
To summarize, the product team must follow these key steps in the feature road-mapping process:
The short answer is no.
Developers are a key factor in charting out the feature roadmaps in that they guide product resources in the run-up to feature rollout. However, at the end of the day, it’s the product manager who serves as the strategic lead, who binds all the disparate components together and coordinates with all the moving parts.
The product manager or product owner needs to work closely with business users to ensure the needs of the business are being served by the roadmap.
There are several instances of how product managers grapple with planning, creating, and communicating comprehensive feature roadmaps with their stakeholders. They have now begun to realize that road-mapping is not based on a ‘one-size-fits-all’ approach, though their overarching goal remains the same. There is no best way of building and publishing a feature roadmap given the motley group of products and businesses.
However, from a product management standpoint, the following do’s and don’ts’ can help you create effective feature roadmaps:
A feature roadmap is a live, flexible, ‘work-in-progress’ document that is incrementally updated to reflect product planning and strategic direction and should not be a one-time, set-in-stone effort. With the evolution in feature roadmaps being inevitable throughout the development lifecycle, clear strategic goals and alignment with the organizational vision are achieved through comprehensive planning and cross-functional collaboration.
The design thinking approach is a set of principles and methods for solving complicated problems by prioritizing user interests. Design thinking helps solve a problem practically and creatively.
It distills empirical knowledge from various fields – including architecture, engineering, and business – and adopts solution-focused methods for resolving issues.
While a background in design is not needed for design thinking, prioritizing human interests is imperative as user needs are at the heart of design thinking, which is why it attempts to understand their needs and create an effective solution.
While solution-based thinking focuses on finding constructive solutions to a problem, problem-based thinking concentrates on opportunities instead of obstacles and constraints. Empirical research conducted by Bryan Lawson at the University of Sheffield illustrates the key differences between the two approaches.
The study sought to determine how a group of designers and scientists would approach a particular problem. Student groups were required to build one-layer buildings from colored blocks in line with this. While the building represents the desired outcome (the solution), there were unwritten rules concerning the placement and relationship of certain blocks (the limitations).
Lawson’s results were reported in his book How Designers Think, in which he noted that scientists focused on identifying the problem (problem-based thinking). In contrast, designers stressed the need to discover the proper solution: “The scientists utilized a technique of rapidly trying out a succession of designs that used as many different blocks and combinations of blocks as feasible… As a result, they attempted to maximize the knowledge accessible to them regarding the permitted combinations.
If they could figure out the rule determining which block combinations were permitted, they could then look for an arrangement that would optimize the required color across the pattern”. Lawson’s results are at the core of Design Thinking, which is an iterative process based on continuous experimentation until the best solution is found.
Design Thinking is a user-centric and progressive approach. To gain a deeper understanding of Design Thinking, consider the four principles articulated by Christoph Meinel and Harry Leifer of Stanford University’s Hasso-Plattner Institute of Design.
The Four Design Thinking Principles:
According to the Hasso-Plattner Institute of Design at Stanford (also known as d.school), the Design Thinking process may be broken down into five parts or phases based on these four principles:
Let’s take a closer look at each of these.
Empathy is an essential beginning point for Design Thinking. The first step of the process is spent getting to know the user and learning about their wants, needs, and goals. This step entails seeing and interacting with people to comprehend their psychological and emotional states.
During this phase, the designer attempts to set aside their assumptions to gain genuine insights into the consumer.
The problem is defined in the second step of the Design Thinking process. The designers compile all their results from the empathize phase and attempt to answer questions: What issues and barriers do the consumers encounter? What patterns emerge? What is the primary user issue they must address?
The designers get a clear problem statement by the end of this stage. The trick here is to define the problem in terms of the user; rather than saying “We need to…,” frame it in terms of the user: “Retirees in the Bay Area require…” After the problems have been articulated, the process to start figuring out the answers begins.
After gaining a firm grasp of user issues and a clear problem statement, it’s time to consider potential solutions. The third stage of the Design Thinking process is where creativity occurs, and it is critical to emphasize that the ideation stage is a judgment-free zone.
Designers will hold brainstorming sessions to generate as many different viewpoints and ideas as possible. Designers can utilize various ideation techniques, ranging from brainstorming and mind-mapping to bodystorming (roleplay situations) and provocation — an extreme lateral-thinking strategy requiring designers to challenge themselves. After the brainstorming process, the designers narrow it down to a few ideas to enter the penultimate stage.
The fourth stage of the Design Thinking process is about experimentation and transforming ideas into concrete objects. A prototype is a scaled-down version of the product that includes the potential solutions identified in previous stages.
This step is critical for putting each solution to the test and identifying any restrictions or weaknesses. Depending on how well the proposed solutions perform in prototype form, they may be approved, enhanced, redesigned, or rejected throughout the prototype stage.
User testing follows prototyping. However, it is crucial to highlight that this is rarely the conclusion of the Design Thinking process.
In practice, the findings of the testing process will often bring you back to a previous step, offering the insights you need to rephrase the initial problem statement or generate fresh ideas you had not considered earlier.
No! When looking at these well-defined processes, you might see a logical sequence with a predetermined order. On the other hand, the Design Thinking process is not linear; it is flexible and fluid, looping back and around and in on itself!
With each discovery brought about by a new phase, you will need to rethink and reinterpret what you have done before — you will never be traveling in a straight line!
There are numerous advantages to employing a Design Thinking methodology, whether in a business, educational, personal, or social environment. Design Thinking, first and foremost, promotes creativity and innovation. As humans, we rely on the knowledge and experiences we have gained to guide our behavior.
We develop patterns and routines that, while valuable in some instances, might limit our ability to solve problems. Another significant advantage of Design Thinking is that it prioritizes humans.
Emphasizing empathy encourages businesses and organizations to think about the real people who use their products and services, increasing their chances of delivering meaningful user experiences. It implies better and more useful goods that genuinely improve the users’ lives, resulting in happier customers and a better bottom line.
As a designer, you significantly impact the goods and experiences that your firm brings to the market.
Integrating Design Thinking into your process may provide substantial business value, ensuring that the things you design are desired by clients and are financially and resource-wise sustainable. With that in mind, consider some of the primary advantages of employing Design Thinking at work:
Reduces time-to-market dramatically: because of its emphasis on problem-solving and developing viable solutions, Design Thinking can significantly reduce the time spent on design and development — particularly when combined with lean and agile methodologies.
Cost savings and higher ROI: getting successful goods to market faster saves the company money. Design Thinking has been shown to produce a substantial return on investment.
Improves customer retention and loyalty: Design Thinking provides a user-centric approach, increasing user engagement and customer retention over time.
Encourages innovation: Design Thinking is all about questioning assumptions and existing beliefs, and it encourages all stakeholders to think outside the box. This generates an innovative culture that reaches well beyond the design team.
Can be used across the organization: a nice thing about Design Thinking is that it is not just for designers. It promotes cross-team collaboration and utilizes collective thinking. Further, it may be used by almost any team in any business.
Whether you are attempting to develop a company-wide Design thinking culture or simply wanting to enhance your approach to user-centric design, Design Thinking helps you innovate, focus on the user, and design products that solve genuine problems.
When it comes to fixing ‘wicked problems,’ Design Thinking comes in handy. Horst Rittel, a design theorist, invented the phrase “wicked problem” in the 1970s to describe tough challenges that are highly ambiguous in nature. There are many unknown aspects to wicked problems; there is no definitive answer, unlike “tame” situations.
Resolving one component of a complex problem is likely to disclose or create new challenges. Another distinguishing feature of wicked problems is that they have no endpoint; as the nature of the problem evolves, so must the solution. Solving difficult problems is thus a constant process that necessitates Design Thinking! Poverty, starvation, and climate change are examples of wicked challenges in our society today.
You have probably seen a lot of similarities between Design Thinking and user experience design by now, and you are probably wondering how they relate to one another. Both are strongly user-centric and driven by empathy, and UX designers will employ many of the Design Thinking phases, such as user research, prototyping, and testing. Despite their similarities, there are some critical differences between the two.
For one thing, the impact of Design Thinking is typically seen at a more strategic level; it examines a problem area to uncover feasible solutions in the context of understanding users, technology feasibility, and business objectives.
Design Thinking is being embraced and utilized by all levels of the organization, including C-level executives. If Design Thinking is concerned with identifying answers, UX design is concerned with developing those solutions and ensuring that they are useable, accessible, and enjoyable for the user.
Consider Design Thinking to be a toolkit that UX designers can utilize. If you work in the UX design profession, it is one of many critical approaches you will rely on to generate exceptional user experiences.
All areas in a company can benefit from Design Thinking. It can be aided by bright, airy physical workspaces that accommodate how employees prefer to work. To apply design thinking to all initiatives, managers should first define the consumers they are attempting to assist and then use the five stages of Design Thinking to describe and address the identified problems. Using a Design-Thinking process increases the likelihood that a company will be inventive, creative, more human and ultimately successful.
2021 was the second-worst in terms of the number of patient record breaches across healthcare service providers. Some estimates rank the largest of the nearly 45 million breaches of patient records in 2021 as some of the worst in history.
Given the constant threats patient records face, the healthcare industry is duty-bound to explore compliance to augment its security perimeter while protecting sensitive data.
Data sanctity and security are of paramount importance in the healthcare industry, which is entrusted with sensitive patient information, such as social security numbers, insurance details, names, addresses, current health conditions, prescribed medications, and hospitals visited.
This data in the hands of cybercriminals can open the floodgates for social engineering attacks on patients. The sensitivity of personal information enables medical records to be sold at exorbitant prices on the dark web, as close to $1,000 per record; approximately over ten times more than the average breached credit card records.
The Health Insurance Portability and Accountability Act (HIPAA) defines a certain set of standards for keeping sensitive patient data secure. Organizations and covered entities (anyone who has access to patient information and provides support for treatment, payment, or operations) that handle Protected Health Information (PHI) must adhere to physical, network, and process security measures for HIPAA Compliance.
PHI encompasses everything from patients’ medical records and social security numbers to financial information to addresses, phone numbers, and photos. The wording of the Act mandates that other entities, such as subcontractors or related business associates, must also comply with HIPAA.
By embracing technology, the healthcare industry provides better and faster access to patient healthcare information. However, the same technological advancement turns into a thorn in the flesh when, owing to inadequate compliance, the healthcare industry leaves such sensitive data susceptible to external threats.
The HIPAA Act lays down the guidelines for safekeeping patient medical records. Any failure to stick to the norms can invite hefty penalties from the Office for Civil Rights (OCR). The penalties can run up to $50,000 for every violation and a maximum of $1.5 million for repeat violations per year.
HIPAA attempts to strike a balance between privacy and accessibility of high-value patient records, such that the best care is offered to the patients but not at the expense of their security.
While safeguards regulating the use of PHI – stored, transmitted, and accessed electronically (ePHI) – already exist, the HIPAA Security Rule came as an addendum to the HIPAA to account for the technological advances in healthcare.
Let’s dive deeper into the HIPAA Security Rule and HIPAA compliant solutions, which are relevant for patient privacy protection:
Many of the conventions covered under HIPAA are similar to that of zero-trust security with strict reporting requirements. Adhering to the HIPAA norms involve a great deal of difficulty, owing to which businesses are increasingly seeking solutions from specialists.
According to a study, the global Healthcare Cloud Computing market may grow at a Compound Annual Growth Rate (CAGR) of 14% between 2019 and 2026 and reach an estimated market value of around $40 billion by 2026.
In terms of industry outlook, the global Cloud computing market would expand substantially because of favorable regulations, elevated healthcare investments, increased public awareness, and a ‘never-seen-before’ demand for regulatory adherence and patient-care data privacy implementation concerns.
The limiting factors for the global healthcare industry are the increasing number of Cloud data violations and data portability complications. Given that data protection is a key component of HIPAA regulations, responsible health organizations are cognizant of the business opportunities in the Cloud healthcare domain. Though the Cloud offers a more secure, innovative platform for businesses for hosting some of their IT infrastructures as opposed to on-premises solutions, the core issue of being HIPAA compliant with public Cloud provider services remains.
Host cloud providers, such as Azure, AWS and GCP cannot claim to be HIPAA Certified hosting providers today due to no federal standard. Instead, these providers standards are more aligned with security programs, such as the Federal Risk and Management Program (FedRAMP) and supported by Business Associate Agreements (BAA) with customers who need to maintain HPIAA compliance.
FedRAMP is a cybersecurity risk management program for the purchase and use of Cloud products and services used by US federal agencies. Only Cloud service providers (CSP) with FedRAMP approval may work with government agencies.
The Office of Management and Budget (OMB) launched the program in response to the 2011 Cloud-First Policy by the US government.
A FedRAMP-Authorized CSP framework not only helps evaluate your organizational compliance requirements but also offers a host of security benefits and efficiencies:
While the Cloud is a viable alternative for many businesses trying to achieve HIPAA compliance, not all Cloud systems conform to the HIPAA Privacy and Security Rule’s guidelines.
Some of the core server functionalities that are needed to deliver effective HIPAA-compliant Cloud hosting services are:
HIPAA seeks to protect sensitive patient data and lay down the guidelines for data handling. However, the challenges of hefty penalties for non-compliance are a concern for small businesses operating on a budget.
The solution for implementing PHI and ePHI security and safeguards, therefore, begins by answering the fundamental question ‘What is HIPAA compliance?’.
For small and medium-sized businesses, the three types of safeguards that are an elementary component of HIPAA compliance are:
Mitigation of risks to ePHIs can be outsourced to a reliable and compliant Cloud service provider and web hosting company, which offers cutting-edge methodologies for maintaining compliance through restricted access, malware protection, and more.
HIPAA compliance is more than a simple set of regulations that businesses must adhere to as they foster trust between healthcare providers and patients. Staying within the norms of HIPAA compliance is a prerequisite for healthcare businesses seeking to ensure patient satisfaction and tackle cybercrime.
The most optimal method to secure data is by drafting a HIPAA compliance checklist and aligning it with the established regulations, and more importantly, with your business strategy:
The healthcare industry must balance data security and the growing need for easy access to healthcare providers, insurers, partners, and other affiliate entities. Though Cloud adoption aims to offer a more secure and HIPAA compliant environment for generating PHIs, only a competent hosting service may meet the stringent requirements through an array of cybersecurity tools and resources. The checklist, along with other compliance documents, when validated with the service provider, underscores the importance of the security of sensitive patient data. Every patient has the right to privacy, and the onus of abiding by these rights largely lies with healthcare organizations.
HIPAA, HITECH, and HITRUST are topics that are commonly referred to within the healthcare information technology (IT) space, since these three entities all relate in a certain way to the protection and security of health information. Although HIPAA, HITECH, and HITRUST are all interrelated in this way, they have distinct differences that bestow specific functions in the data privacy and information security space.
A clear understanding of the intricacies amongst these three complex topics is necessary in every discipline that encompasses healthcare systems. However, they are often confused with one another since they overlap in nature. In short, HIPAA is an act that outlines the compliance expectations for the protection of health information, including transmission and management. HITECH, which falls under the HIPAA umbrella, expands the latter to include additional modernized legislation that broadens the scope of health information security and protection. Lastly, HITRUST is an organization that provides certification to organizations for demonstrated compliance with both HIPAA and HITECH regulations.
Because HIPAA, HITECH, and HITRUST all have broad implications to the protection and privacy of information and healthcare IT, the differences amongst them should be well understood. To clarify these differences, this article will further explain the purpose of each entity, identify distinctions between them, and elucidate the relationship and interplay amongst the triad.
HIPAA, which is short for the Health Insurance Portability and Accountability Act, was first enacted in August of 1996. This act required that the United States Department of Health and Human Services (DHHS) Secretary issue national guidelines for the security of electronic protected health information (e-PHI), electronic interchange, and health information privacy as well as security. The three tiers of necessary health information exchange under HIPAA include treatment, payment, and operations. During a time of immense technological advancement, HIPAA also established to accommodate the modernization occurring within the healthcare industry. Most notably, this set of regulations addressed the advancements of technology and telecommunication within the healthcare industry, aiming to legislate issues surrounding data access, privacy, and sharing.
HIPAA also established several rights for those in the United States that receive health care services under the Privacy Rule. The Privacy Rule established standards regarding an individual’s right to personal health information accessibility, how an individual’s protected information is used, and an individual’s entitlement to understand and influence the way their health information is utilized. Through these mechanisms, the Privacy Rule ensures the protection of an individual’s health information, while also allowing access to those that need it to make informed medical and administrative decisions. Therefore, the Privacy Rule is flexible enough to be applied to an array of use cases related to the exchange of health information.
Since HIPAA was enacted at the beginning of the dot-com era, technology has only further advanced to what we know it to be today. Along with these developments, the utilization of health information and its privacy also had to adapt to a more modern and evolving electronic landscape. As such, the Health Information Technology for Economic and Clinical Health Act was passed
HITECH
The HIPAA Privacy Rule was modernized with the inception of the Health Information Technology for Economic and Clinical Health (HITECH) Act. This act was passed by Congress in 2009, representing a new piece of legislation under HIPAA. HITECH added valuable updates to HIPAA that encouraged the use of secure electronic health records (EHR) and expanded the scope of responsibility surrounding covered entities. These major additions included:
These additions are further described in detail below.
HITECH expands HIPAA by not just regulating the protection of health information but also the way it to shared electronically amongst patients, physicians, and healthcare systems. Under HITECH, an individual has the right to access their electronic health information held by covered entities and their business associates. In an instance where a covered entity utilizes an EHR to maintain an individual’s PHI, it is the individual’s right to obtain a copy of the PHI electronically, if desired. Additionally, the individual can ask the entity to provide a copy to another entity or designated individual, given that the decision is both clear and specific.
The HITECH Act also enacted new requirements for HIPAA-covered entities, particularly with regards to business associates. A business associate is defined as an individual or entity that performs specific duties or responsibilities requiring the use or exchange of protected health information. Business associates work on behalf of a covered entity. The HITECH Act ensures that such business associates of covered entities comply with HIPAA rules.
In 2013, the DHHS Office for Civil Rights (OCR) provided a ruling to change the HIPAA Privacy, Security, Breach Notification, and Enforcement Rules. Amongst these changes was a final rule that ensures HIPAA Rules also apply to business associates. Therefore, business associates are considered directly liable for HIPAA violations, which expands the requirements of HIPAA beyond just hospitals and insurance companies and furthermore applies to anyone managing PHI.
Outside of its inclusion of business associates, the HITECH Act also expanded the range of the HIPAA Privacy and Security Rules. This expansion implemented several provisions and more intense penalties for non-compliance, thereby increasing criminal and civil enforcement. For example, the HITECH Act implemented four hierarchical categories of violations, with each level having a corresponding penalty. The penalty amounts increase significantly with each violation, with penalty amounts extending up to $1.5 million.
HIPAA provides foundational guidelines surrounding the release of information, while HITECH builds upon these standards regarding data breaches. In the event of an unsecured breach, HITECH outlines notification requirements for covered entities to abide by. HIPAA-covered entities are required to alert affected individuals after any level of a data breach. For breaches that affect less than 500 people, entities should notify the DHHS Secretary annually. If the breach affects greater than 500 people, the entity must contact both the DHHS Secretary as well as the media immediately. This change holds covered entities and business associates accountable to specific government bodies and the affected individual(s) for providing adequate protection of such health information.
Another term that is frequently associated with HIPAA and HITECH is HITRUST. HITRUST, also known as the Health Information Trust Alliance, is not a law like HIPAA or HITECH. Instead, it is a well-known private organization. Founded in 2007, HITRUST created a Common Security Framework (CSF), which offers an approach for organizations to ensure adherence to several regulatory standards as well as risk management.
The CSF provides a method that can be utilized by all types of entities to create, maintain, and exchange sensitive or regulated information. The HITRUST CSF integrates with nationally and internationally accepted security and privacy-related standards, including HIPAA, ISO, NIST, PCI, and GDPR. By doing so, it provides a widespread set of security and privacy controls to ensure compliance across the globe.
Not all the controls contained within the CSF are relevant to HIPAA standards, however, all HIPAA requirements are embedded within the framework.
Anyone who manages PHI, including companies like TechBlocks, must comply with HIPAA and associated HITECH regulations. The implementation of the HITECH Act both changed and strengthened the pre-existing foundational HIPAA legislation. As aforementioned, the HITECH Act strengthens HIPAA in several ways, most notably via the inclusion of the breach notification rule, the accountability of business associates in data breaches, and the expansion of the violation and penalty infrastructure. These changes impact businesses, specifically in our sector, who must develop solutions to address both sets of rules.
It is important for any organization that utilizes protected health information to be HIPAA compliant. However, no HIPAA certification existed to prove compliance until the enactment of HITRUST. HITRUST establishes a standardization of compliance for any institution by upholding HIPAA and HITECH standards.
While technology has edged its way into all aspects of our lives, one area that has seen a significant improvement in convenience, data-driven insights, and increased service to others is within the healthcare ecosystem.
Significant technological advances in the medical field involve imaging services, surgical robotics, and automation, which can be seen at the forefront of care. However, one aspect of technology that has been making waves into a modern role in disease state management and health improvement, is wearables.
The past few years have seen a staggering increase in the utilization of wearable devices, which include those that focus primarily on health and wellness. As their usage and benefits are further observed, it can only be expected that more consumers and organizations, including physicians and clinical trial teams, continue to use these devices to their full spectrum.
There are numerous types of health-related wearable devices currently available. Many are categorized as activity trackers, which are the most basic form. Other devices include monitoring wearables that can measure vitals (ex: body temperature, heart rate, blood pressure, etc.) and upload said data to a secure portal.
Another sector of medical wearables, and the most advanced type, involve therapeutic devices that measure patient metrics in real-time and adjust treatment as needed. Examples of therapeutic wearables include insulin pumps, rehabilitation applications, and respiratory therapy monitoring.
Since medicine and healthcare is not a one size fits all industry, medical wearables are the future of treatment improvement as well as independence.
Clinical research, and its capabilities, have expanded exponentially due to wearable technology. Perhaps one of the most significant benefits offered is the ability to amass trial participants from a limitless geographical location.
With wearable monitoring devices, participants can come from far and wide, which helps to ensure that the trial subjects are the best possible participants based on research criteria. Researchers have the ability to record and measure diagnostic data remotely, allowing them to expand the pool of participants and enlist those from various backgrounds and locations.
Wearables also allow clinical trial teams to monitor a participant’s health more vigilantly and in real-time. Doing so provides researchers with continuous monitory data trends and ensures immediate notification should any of the physiologic factors fall outside of the normal range, requiring medical attention. This improves the current practice standard of care and attention for study participants as well as data accuracy for reporting and file management.
The COVID-19 pandemic brought on a surge of “care in place” practices, and ideologies implemented to protect physicians as well as patients. However, this practice required a reimagining of the healthcare system ‘norm’ and would have been impossible, or incredibly unsuccessful, without the evolution of wearable technology.
Many medical wearables provide the unique ability for continuous monitoring of a patient’s health. Previously, continuous monitoring required a costly hospital stay or a series of outpatient visits/check-ups. Manual devices were used to obtain readings or were given to a patient with the instruction to self-test or monitor throughout the day and record appropriately in a paper log.
Since patient compliance is one of the most challenging burdens in healthcare, manual devices are not an optimal present-day option for the majority of patients. Many people have trouble remembering to take their medications daily, let alone perform manual pulse checks or blood sugar readings.
Medical wearables currently on the market allow for uninterrupted monitoring, which requires little to no effort from the consumer. Many devices support data syncing and transfer for seamless transmission of critical information.
Most physicians can admit that one of the most challenging aspects of patient care, especially for those suffering from a chronic condition, is acknowledging that treatment success largely depends on a patient’s willingness to follow a doctor’s guidance, which is deemed adherence.
Practitioners can suggest a range of lifestyle changes or therapies that can help prevent a chronic condition from progressing. But unless the patient follows these guidelines, the treatment plan provided is essentially up to the patient. As the old proverb says, you can lead a horse to water, but you cannot force it to drink.
The Journal of Medical Internet Research published a study in 2019, which found that patients using digital health trackers were more adherent to their medications, with greater adherence observed in cases of more frequent tracking. Beyond just medication compliance, the utilization of health wearables resulted in more patients following their therapy guidelines, which ultimately lead to better outcomes and healthier lifestyles.
Medical wearables have also been shown to increase a patient’s engagement in self-care, which is an essential component of improving one’s self-directed health. Individuals who primarily suffer from poor self-care are those suffering from multiple comorbidities. In many cases, the conditions themselves make it challenging to practice healthier habits or even find the motivation to at least try. Individuals with multiple disease states can significantly benefit from improved self-care. With the evolution of health wearables, consumers can overcome monitoring barriers and ultimately improve quality of life, help prevent complications, and promote better living.
Improving mental health has also been a major topic of discussion as of late since a vast majority of people suffer from a myriad of chronic conditions. Stress is one of the biggest root causes of mental health disorders and plays a significant role in depression and anxiety. It also has the potential to increase one’s risk of physiological conditions, like heart disease, stroke, diabetes, and obesity.
As shown, stress not only affects mental health but also can contribute to poor physical wellbeing. Wearable devices such as Apollo Neuro and Lief usher in a new field of wearables that help modernize the way mood disorders are being monitored and treated.
Apollo Neuro allows mood disorders to be treated in a whole new non-pharmacologic way. Through the proprietary use of inaudible vibrations, these devices have the potential to alter mood through our sense of touch. This device is self-directed and allows the user to choose their desired mood, whether it be ‘Energy and Wake up’ or ‘Relax and Unwind.’
Lief monitors heart rate variability (HRV) to help a consumer identify their daily living stressors and self-regulate accordingly.
Both devices are drug-free therapies that allow a user to find balance and improve their mood disorder at their own pace.
Whitecoat syndrome is a relevant phenomenon where a patient’s vitals measured at the doctor’s office are worse than they are during the regular course of daily living. The most common occurrence is increased blood pressure due to the stress of going to and/or being at the physician’s office.
A 2013 study in the journal Hypertension found that approximately 15-30% of individuals who have a high blood pressure reading at the doctor’s office suffer from white coat syndrome, which is an acute stress-related response instead of a serious chronic condition.
This syndrome can lead to inaccurate diagnoses and furthermore treatment if the vital data used at each health visit develops a trend toward hypertension over time. While taking vitals at each visit may offer only a snapshot of a patient’s blood pressure or respiratory rate, wearables provide a more comprehensive picture of a patient’s health during their normal course of daily living and activities.
Significant changes in one’s vitals can be triggered by work stress, lack of daily activity, time change, insomnia, etc. These markers can be identified using trends in wearable data, which can help differentiate a chronic condition from an acute response. A patient’s health action plan will ultimately benefit from following real-time trends in vital data as opposed to focusing on singular ‘snapshots’ in time.
Significant gaps in healthcare can be observed across racial, geographical, and socioeconomic lines. All of which can have a major impact on one’s level of care. Wearable devices help bridge these gaps in numerous ways, including cost-effectiveness, language barriers, and independent living.
Although technology and health literacy remain a struggle for senior citizens, in particular, health wearables have been shown to improve independent living amongst the elderly. An American Advisors Group (AAG) survey found that over 90% of seniors between the ages of 60 and 75 wanted to remain living in their primary residence. However, a significant hurdle that makes many wary of foregoing assisted living facilities is the increased risk of falls.
According to the U.S. Center for Disease Control (CDC), one out of four Americans > 65 years of age fall on an annual basis. Furthermore, only half of these fall cases actually discuss it with their doctor, which is quite an alarming statistic. A new generation of wearables, like GreatCall, offers real-time fall detection, which can then alert caregivers or emergency services, allowing for immediate care.
The continued advancement and application of medical wearable devices within the healthcare realm are promising for both consumers and medical professionals. As wearables continue to improve mental and physical health, a new door opens for the field of medicine that does not primarily focus on medication. Instead, wearables bring data-driven technology to the forefront for a better comprehensive insight into the patient as a whole as well as extending the focus onto non-invasive care. Also, they allow consumers to live independently and ditch doctor’s office check-ups, as digital medicine is the new age of providing care.
These devices have endless applications and provide the basis that health can be monitored and improved remotely and at minimal expense. All of the wearable applications mentioned increase the quality of patient care at many different aspects of the healthcare paradigm. The future of health wearable devices is bright and will continue to overcome current barriers that are regarded as ‘norms’ of healthcare.
The design thinking approach is a set of principles and methods for solving complicated problems by prioritizing user interests. Design thinking helps solve a problem practically and creatively.
It distills empirical knowledge from various fields – including architecture, engineering, and business – and adopts solution-focused methods for resolving issues.
While a background in design is not needed for design thinking, prioritizing human interests is imperative as user needs are at the heart of design thinking, which is why it attempts to understand their needs and create an effective solution.
While solution-based thinking focuses on finding constructive solutions to a problem, problem-based thinking concentrates on opportunities instead of obstacles and constraints. Empirical research conducted by Bryan Lawson at the University of Sheffield illustrates the key differences between the two approaches.
The study sought to determine how a group of designers and scientists would approach a particular problem. Student groups were required to build one-layer buildings from colored blocks in line with this. While the building represents the desired outcome (the solution), there were unwritten rules concerning the placement and relationship of certain blocks (the limitations).
Lawson’s results were reported in his book How Designers Think, in which he noted that scientists focused on identifying the problem (problem-based thinking). In contrast, designers stressed the need to discover the proper solution: “The scientists utilized a technique of rapidly trying out a succession of designs that used as many different blocks and combinations of blocks as feasible… As a result, they attempted to maximize the knowledge accessible to them regarding the permitted combinations.
If they could figure out the rule determining which block combinations were permitted, they could then look for an arrangement that would optimize the required color across the pattern”. Lawson’s results are at the core of Design Thinking, which is an iterative process based on continuous experimentation until the best solution is found.
Design Thinking is a user-centric and progressive approach. To gain a deeper understanding of Design Thinking, consider the four principles articulated by Christoph Meinel and Harry Leifer of Stanford University’s Hasso-Plattner Institute of Design.
The Four Design Thinking Principles:
According to the Hasso-Plattner Institute of Design at Stanford (also known as d.school), the Design Thinking process may be broken down into five parts or phases based on these four principles:
Let’s take a closer look at each of these.
Empathy is an essential beginning point for Design Thinking. The first step of the process is spent getting to know the user and learning about their wants, needs, and goals. This step entails seeing and interacting with people to comprehend their psychological and emotional states.
During this phase, the designer attempts to set aside their assumptions to gain genuine insights into the consumer.
The problem is defined in the second step of the Design Thinking process. The designers compile all their results from the empathize phase and attempt to answer questions: What issues and barriers do the consumers encounter? What patterns emerge? What is the primary user issue they must address?
The designers get a clear problem statement by the end of this stage. The trick here is to define the problem in terms of the user; rather than saying “We need to…,” frame it in terms of the user: “Retirees in the Bay Area require…” After the problems have been articulated, the process to start figuring out the answers begins.
After gaining a firm grasp of user issues and a clear problem statement, it’s time to consider potential solutions. The third stage of the Design Thinking process is where creativity occurs, and it is critical to emphasize that the ideation stage is a judgment-free zone.
Designers will hold brainstorming sessions to generate as many different viewpoints and ideas as possible. Designers can utilize various ideation techniques, ranging from brainstorming and mind-mapping to bodystorming (roleplay situations) and provocation — an extreme lateral-thinking strategy requiring designers to challenge themselves. After the brainstorming process, the designers narrow it down to a few ideas to enter the penultimate stage.
The fourth stage of the Design Thinking process is about experimentation and transforming ideas into concrete objects. A prototype is a scaled-down version of the product that includes the potential solutions identified in previous stages.
This step is critical for putting each solution to the test and identifying any restrictions or weaknesses. Depending on how well the proposed solutions perform in prototype form, they may be approved, enhanced, redesigned, or rejected throughout the prototype stage.
User testing follows prototyping. However, it is crucial to highlight that this is rarely the conclusion of the Design Thinking process.
In practice, the findings of the testing process will often bring you back to a previous step, offering the insights you need to rephrase the initial problem statement or generate fresh ideas you had not considered earlier.
No! When looking at these well-defined processes, you might see a logical sequence with a predetermined order. On the other hand, the Design Thinking process is not linear; it is flexible and fluid, looping back and around and in on itself!
With each discovery brought about by a new phase, you will need to rethink and reinterpret what you have done before — you will never be traveling in a straight line!
There are numerous advantages to employing a Design Thinking methodology, whether in a business, educational, personal, or social environment. Design Thinking, first and foremost, promotes creativity and innovation. As humans, we rely on the knowledge and experiences we have gained to guide our behavior.
We develop patterns and routines that, while valuable in some instances, might limit our ability to solve problems. Another significant advantage of Design Thinking is that it prioritizes humans.
Emphasizing empathy encourages businesses and organizations to think about the real people who use their products and services, increasing their chances of delivering meaningful user experiences. It implies better and more useful goods that genuinely improve the users’ lives, resulting in happier customers and a better bottom line.
As a designer, you significantly impact the goods and experiences that your firm brings to the market.
Integrating Design Thinking into your process may provide substantial business value, ensuring that the things you design are desired by clients and are financially and resource-wise sustainable. With that in mind, consider some of the primary advantages of employing Design Thinking at work:
Reduces time-to-market dramatically: because of its emphasis on problem-solving and developing viable solutions, Design Thinking can significantly reduce the time spent on design and development — particularly when combined with lean and agile methodologies.
Cost savings and higher ROI: getting successful goods to market faster saves the company money. Design Thinking has been shown to produce a substantial return on investment.
Improves customer retention and loyalty: Design Thinking provides a user-centric approach, increasing user engagement and customer retention over time.
Encourages innovation: Design Thinking is all about questioning assumptions and existing beliefs, and it encourages all stakeholders to think outside the box. This generates an innovative culture that reaches well beyond the design team.
Can be used across the organization: a nice thing about Design Thinking is that it is not just for designers. It promotes cross-team collaboration and utilizes collective thinking. Further, it may be used by almost any team in any business.
Whether you are attempting to develop a company-wide Design thinking culture or simply wanting to enhance your approach to user-centric design, Design Thinking helps you innovate, focus on the user, and design products that solve genuine problems.
When it comes to fixing ‘wicked problems,’ Design Thinking comes in handy. Horst Rittel, a design theorist, invented the phrase “wicked problem” in the 1970s to describe tough challenges that are highly ambiguous in nature. There are many unknown aspects to wicked problems; there is no definitive answer, unlike “tame” situations.
Resolving one component of a complex problem is likely to disclose or create new challenges. Another distinguishing feature of wicked problems is that they have no endpoint; as the nature of the problem evolves, so must the solution. Solving difficult problems is thus a constant process that necessitates Design Thinking! Poverty, starvation, and climate change are examples of wicked challenges in our society today.
You have probably seen a lot of similarities between Design Thinking and user experience design by now, and you are probably wondering how they relate to one another. Both are strongly user-centric and driven by empathy, and UX designers will employ many of the Design Thinking phases, such as user research, prototyping, and testing. Despite their similarities, there are some critical differences between the two.
For one thing, the impact of Design Thinking is typically seen at a more strategic level; it examines a problem area to uncover feasible solutions in the context of understanding users, technology feasibility, and business objectives.
Design Thinking is being embraced and utilized by all levels of the organization, including C-level executives. If Design Thinking is concerned with identifying answers, UX design is concerned with developing those solutions and ensuring that they are useable, accessible, and enjoyable for the user.
Consider Design Thinking to be a toolkit that UX designers can utilize. If you work in the UX design profession, it is one of many critical approaches you will rely on to generate exceptional user experiences.
All areas in a company can benefit from Design Thinking. It can be aided by bright, airy physical workspaces that accommodate how employees prefer to work. To apply design thinking to all initiatives, managers should first define the consumers they are attempting to assist and then use the five stages of Design Thinking to describe and address the identified problems. Using a Design-Thinking process increases the likelihood that a company will be inventive, creative, more human, and ultimately successful.
This article was originally published on tblocks.com
https://www.tblocks.com/articles/thoughts/what-is-design-thinking/