Improve the innovation ecosystem in your company with these 5 ideas (Part 2)

In the previous post we talked about tips on how to improve the structures of work teams in a company to promote plural innovation spaces and how to allow workers to be the driving force of your innovation ecosystem.

In this second part we want to provide you with 5 tips to promote the culture of innovation focused on the management of work teams.

1. Be Transparent About Your Challenges

If the challenges and goals of the company are not shared, they will lead us to a situation where the new ideas generated by the work teams to innovate will not fit with the chosen path. In addition, they will not feed back on each other when they are not coordinated.

Being transparent about what you need to improve as a company will help everyone move in the same direction, looking for solutions to the same problems.

2. Admit (and learn from) your failures

Sharing the failure cases is as important as sharing the company’s success stories. Understanding where we were wrong and letting the new additions to the company know it will allow us to find ideas, motivations or thought processes to really introduce innovation in your company.

3. Take advantage of open innovation

A typical mistake many executives make is to focus on cultivating innovation solely within the company. This narrow mindedness excludes the great minds that exist outside of your organization. To avoid this mistake, take advantage of open innovation.

Open innovation is a process that allows companies to find solutions to their most difficult problems by obtaining input from outside the organization. The open innovation model continues to grow and will be essential when designing our strategies. If you are looking for articles on this topic we recommend this article by Henry Chesbrough.

4. Accept failure and make it the norm

It is inevitable that innovation carries the risk of failure. For every successful example of world-changing innovation, there are many failed ideas.

The reaction to this fact cannot be to try to run away from it, but we must accept it and learn to live with it as a characteristic of the sector. We must acknowledge the possibility of failure, de-dramatize it, and encourage risky initiatives to help employees approach innovation in a more open and inventive way. Failure is necessary because it leads to learning, adaptation and new concepts and models. The vast majority of innovations are the result of previous failures.

5. Participate in an innovation hub

Innovation Hubs are spaces where company representatives meet and share approaches to innovation. Having grown in popularity over the last decade, there are now hundreds of these centers around the world.

The Innovation Hub concept recognizes the importance of a multidisciplinary approach to innovation and shows the importance of collaboration in problem solving.

In our context we have available the European Digital Innovation Hubs (EDIHs). Take a look at innovation hubs near you and think about how you and your teams can get involved.

This type of practice to make better business decisions is no longer seen as unique to companies specializing in R+D+i, but increasingly SMEs are interested, which by fostering a culture of innovation make it possible to make the most of the knowledge accumulated in the company.

At Macrotest we use these ideas to improve day by day in our organization. In our R+D+i projects division, we seek to help companies develop their innovation projects with organizational improvements, search for financing and sharing our “know-how” thanks to our experience..

We are available to solve all your R&D&i project needs!

What are the benefits of hiring agile cells?

Benefits of hiring agile cells

In today’s era of digital transformation, companies are constantly looking for ways to improve their profitability and stay competitive in the marketplace. One way to achieve this is by adopting an agile cell approach to product and service development.

Agile cells are small, highly collaborative teams that work autonomously to develop a specific product or service. These teams are composed of members with complementary skills and focus on continuous delivery of value to the customer. Agile methodology has become popular in the technology sector, as it allows for greater flexibility and adaptability to changes in the market.

Implementing agile cells in a company can bring many benefits:

First, it enables greater innovation by allowing teams to work autonomously and make quick decisions. This also increases efficiency by reducing development times and enabling faster product and service launches.
Second, agile cells also improve business intelligence by enabling better communication and collaboration between different departments within a company. This increases the company’s ability to make informed decisions and adapt to changes in the market.
Finally, the adoption of agile cells can also improve a company’s profitability by enabling greater efficiency in product and service development.

At Macrotest, we count agile cells as an effective way to improve innovation, business intelligence and profitability across industries.

By enabling small, highly collaborative teams to work autonomously and focus on continuous delivery of customer value, companies can improve their adaptability and efficiency.

If you want to learn more about our agile cell service, please contact us at info@macrotest.es!

Improve the innovation ecosystem in your company with these 5 ideas (Part 1)

When we talk about how to improve a company’s innovative production, the most obvious solution is to increase the budget. Whether in training for workers, in new technicians or in a strategic plan. But these expenses are not enough in themselves, or above all these expenses will not be as efficient without the agitated internal organization and structure.

Today we want to bring you 5 simple tips that you can introduce in your company to promote a culture of innovation. In this first part, we will talk about the structures of work teams, their internal dynamics and how we can improve our innovation ecosystem

1. Encourage People to Use Their Vacations

This idea may be obvious but with the demand for day-to-day work relegated to the background. A company’s most important asset is its workers and their accumulated knowledge. When employees are tired and burned out, they are not as productive or creative. Encouraging them to take vacations will help them de-stress, so they return to work with a clear mind that is able to think more creatively.

2. Reward Experimental Behavior

If you want innovative employees, then help encourage and reward experimental behavior. If the worker takes the initiative and tries something new that ends up benefiting the company, you can make an announcement and give them compensation (eg a gift card). The worker is the one who has more direct contact with the real needs of the day to day, and is able to analyze and imagine the most efficient methods of making their work more productive and comfortable. Showing your appreciation will motivate your entire team to do the same so you get the results you’re looking for.

3. Allow for Questions

The best way to encourage innovation at work is to encourage discussions and allow people to ask questions. It is essential to create a “no stupid questions” rule so that people dare to ask questions. When you encourage open conversations, you’ll create an environment that supports innovation.

4. Make diverse hires

Imagine a group of 10 people who come from a similar background and share the same basic assumptions. Now, think of a group of 10 diverse people with different backgrounds and experiences. Which group has the greatest capacity for innovation?

When you make diversity a priority in your company, you automatically increase the potential for innovation. After all, your business isn’t just trying to reach customers who are like you, your goal is to maximize your market and reach all parts of society. How can you do that if everyone you hire looks and thinks like you?

5. Adopt a non-hierarchical management approach

When it comes to fostering innovation in the workplace, a strict hierarchy can be a real problem. If your staff only think about innovation when they are specifically tasked to do so, you will never be able to reach your company’s full potential. The most innovative companies have a horizontal but strong management approach that allows employees to break down barriers between work areas. A lot of innovation comes from cross-pollination between teams and divisions, and the sharing of ideas and problems. This type of practice to make better business decisions is no longer seen as unique to companies specializing in R+D+i, but increasingly SMEs are interested, which by fostering a culture of innovation make it possible to make the most of the knowledge accumulated in the company.

In the next entry we will discuss how to improve the innovation strategy in your company and make the most of the opportunities in your innovative context.

We are available to solve all your R&D&i project needs!

Big Data, Business Intelligence and Data Science… turning data into valuable information

Big Data, Business Intelligence and Data Science

It is clear that in a world where digital transformation is here to stay, every organization must have the ability to collect, select, organize, analyze and interpret a large volume of data. In this sense, the proper management and knowledge of data are key and strategic in any business sector. For this reason, more and more companies are deciding to invest in data analytics solutions based on the premise that information is power (and that data is the currency of the digital economy).

In the current context, there are a number of methodologies that seek in some way to facilitate data-driven decision making. Companies that take on the challenge of knowing and interpreting their data benefit in a variety of ways, either by saving costs, gaining speed, improving customer service, anticipating the competition, improving the operational management of the business, and identifying new business opportunities. In short, obtaining these benefits will depend on the right choice of the most suitable data analysis processes for the company.

Concepts such as Big Data, Business Intelligence and Data Science have in common the intention of extracting value from information, although they do so in a different and complementary way.

Big Data refers to the storage of large volumes of data and the procedures used to find repetitive patterns within this data. Big Data focuses on the capture and processing of data, working with a large amount of complex data (structured and unstructured) coming from various sources, such as sensors, smart devices, websites and social networks, among others. The amount and complexity of this data makes it difficult to analyze and manage if the appropriate tools are not used.
Business Intelligence is responsible for data management, data organization and production of information from data. It is applied in organizations to fundamentally improve decision-making capabilities by performing data mining tasks, analyzing business information, and generating reports. Business intelligence is predominantly used for the analysis of stored historical data, impacting business performance, but without being able to predict future data. In this sense, it is oriented to the past, studying the historical evolution of the company to understand its development by finding analytical patterns. Business intelligence is the set of applications, methodologies and technologies capable of transforming data into valuable and structured information to be used for business purposes. It focuses specifically on internal company and industry data. Some examples of data analyzed through Business Intelligence are those related to marketing, customer service, sales, or data from the company’s human resources. It is precisely through Business Intelligence that the analysis of data obtained from Big Data can be carried out.
Data Science could be considered as an evolution of Business Intelligence. Its objective is the generation of value from the collection, classification, visualization and corresponding interpretation of data. This more complex data analysis helps the company to generate new knowledge by discovering and answering new questions. To do so, it uses a range of techniques involving statistics, computer science, predictive analytics, and machine learning. In this way, Data Science makes it possible to analyze massive data sets, seeking solutions to problems that have not yet been thought of. The data being analyzed are both internal and external, for example, videos, emails and social media content. Data Science experts can predict potential trends by exploring seemingly unconnected data sources, finding better ways to analyze the information.

This type of solutions based on data analysis to make better business decisions, are no longer seen as tools intended only for large companies, but are increasingly SMEs interested in these technologies and methodologies, working in an integrated way to get the most out of the growing volume of data.

At Macrotest we have the #DataLab division, seeking to help companies through comprehensive solutions for data management, data analysis and implementation of artificial intelligence for prediction and personalization of services.

We are at your disposal to solve all your data analysis needs!

It works on my notebook! Theory versus practice in Data Science

When you start on the road to a Data Driven company, you begin to understand how to use the tools that the current market offers such as artificial intelligence or Internet of Things. You hire data scientists who can solve your business problems without first asking yourself WHAT you need to do artificial intelligence and HOW you plan to do it.

The answer to the first question is simple, we need data. Now, the situation starts to get complicated when we try to answer our second question.

Everything seems perfect, but where do I have this data, what format does it take, is it easy to access, how often can I access it, is it complete, without errors, without null records, how long have I had this data, how long have I had this data? And assuming all this is solved, how easy is it to develop a Machine Learning model and implement it?

There are many questions, but there are also many answers depending on the problem to be solved.

When we talk about Data Science, we are not talking about a tool, skill or method, but more like a scientific approach that uses statistical theory, applied mathematics and computer tools to process large amounts of data. Data science is a detailed process that mainly involves preprocessing, analysis, visualization and prediction.

We all know that Data Science is a very powerful scientific approach, with all kinds of interesting applications. However, it is also well known that in Data Science there is a big gap between theory and practice: when it comes to theory, we know everything, but we don’t know how to apply it in real life.

For this reason it is important to prioritize when working with data. This list may change depending on the company, but most of them agree on many of these points.

Step 1 – Define the business problem

This first step is fundamental, and requires much more of the human factor for the understanding of the problem to be solved, the agreement of criteria for the definition of the objectives, scope and timeframe, than of the system itself that will be used as a means to reach them.

Surely the data scientist has many ways to solve a problem, but the one who must set the course of the solution must be the one who knows the business. Interaction and teamwork are essential.

Step 2 – Data acquisition

This step is perhaps where we find the biggest difference between theory and practice. In theory, when we want to make a machine learning model, all we need to do is download a dataset from sites such as Kaggle or Github and we will have clear, neat and well described information. In practice, sometimes the sources can be:

Very varied: which would take a previous work of ETL’s, modeling, etc.
Poorly described or without description: Without having a clear description of what variable we are working with we do not know what we have and if it can help us to solve our problem.
With erroneous data / null records: As it is often said in Data Science, Garbage in / Garbage out.
Unknown: In a sectorized company where the data are within the area that worked with them, the opportunity to combine them or use them for other business purposes may be lost.
With restricted access: Depending on the data security standards within the company, accessing data often becomes a titanic task and involves a bureaucratic process that is difficult to measure over time.

These and many problems with data sources can be solved with proper data governance and fundamentally a very well communicated organization.

Step 3 – Data preparation

This step involves data cleansing and data transformation, data cleansing is the most time consuming as it involves handling many complex scenarios such as inconsistent data types, misspelled attributes, missing values and duplicates. Then, in data transformation, we have to modify the data based on the defined mapping rules.

Step 4 – Exploratory Data Analysis

With the help of Exploratory Data Analysis we define and refine the selection of variables to be used for the development of our model. It is important to always keep in mind the solution we want to target.

Step 5 – Data modeling

The main activity of a data science project is known as data modeling. In this step, we repeatedly apply machine learning techniques of type strength such as KNN, decision trees, Naive Bayes, etc. to the data so that we can identify the model that best fits the business requirement. We train the model on the training dataset and test it to select the best performing model.

Step 6 – Visualization and communication

This point is perhaps the most relevant of all because we can have the best data extraction and transformation process, the best trained Machine Learning model, but if we do not know how to visualize it, explain it, communicate it and give value to the business, all the previous work will not matter much. It is essential to reinforce soft skills at this point to know how to reach stakeholders.

Step 7 – Implementation and maintenance

And finally, in this step, the data scientist implements and maintains the model, tests the selected model in a pre-production environment before implementing it in the production environment, which is the best practice. After implementing it, we have to get real-time analytics and monitor and maintain the performance of the project.

As you will see, there is a huge difference between what we study (Theory) that practically starts and ends in a local Notebook versus what is needed to carry out the whole process in real life (Practice). It is for this reason that it is often overwhelming and sometimes frustrating to try to work with data and generate results.

That is why Macrotest #DataLab helps you all the way with our end-to-end solution so that you have a complete understanding of the tools, methodologies and processes.

How are agile cells composed?

How are composed the agile cells

Recall that in the previous note we talked about agile work cells. This is a way of organizing work similar to that of a living cell, reflecting its dynamism. In this environment, interdisciplinary and collaborative work is promoted, where each member of the cell contributes to the achievement of the objectives, always focused on the customer.

With respect to the roles that make up this type of cell, they generally represent different areas and disciplines, all of which are necessary to respond to the problems that led to the formation of the cell. In particular, a Product Owner is usually included, who maintains the vision of the final product and transmits it to all those involved, seeking to ensure that in each sprint the product is being adapted to the needs of the end user. He/she must also have interpersonal skills since he/she is in charge of interacting with all the actors involved in the project.

The Scrum Master is another role present in agile cells and acts as a facilitator, accompanying the process and seeking to ensure that the principles of the agile methodology are followed. His mission is to ensure the availability of the development team, eliminating obstacles that may arise and potentially affect the delivery of the product under the agreed terms. His skills at a strategic level, his ability to manage teamwork, and above all his problem-solving skills are important.

Of course, the Development Team, whose mission is fundamentally to develop the product, working in small teams where information is shared openly and a collaborative spirit reigns, cannot be missing. There may also be other roles, such as Front End Developer, Back End Developer, Machine Learning specialists, UX Designer, among others.

Despite the many advantages of agile work cells, there can also be certain drawbacks during their development. Some of them are mainly associated with the lack of experience of the team, when these cells are entirely made up of junior members. In this case, the creation of agile work cells mentored by a figure with a high level of seniority is a very interesting tool. In this way, even when the client hires a cell made up of junior profiles and the fees reflect this, having a senior profile in charge of acting as a mentor raises the quality of the deliverable product. This is because the mentor guides the group of junior members and also reviews their deliverables.

Another disadvantage to be avoided when working in agile cells is the lack of quality controls. In this sense, the eagerness to reduce development times to a minimum can lead to quality failures and ultimately to problems with the client. The role of a mentor with a high level of seniority can also contribute to avoiding this type of problems by guiding and reviewing the work developed by the team. These mentors provide their knowledge, tools, training and coaching to make the most of the team’s potential, but the most important thing is the experience they bring to a group of junior professionals. Their skills include not only technical skills, which are fundamental, but also interpersonal skills such as empathy, communication, patience and problem solving.

At Macrotest we have agile work cells and also mentored cells, where projects developed by junior professionals go to the next level thanks to the senior mentoring process, pursuing the highest quality standards.

Contact us for more information!

What does agile cell work consist of?

Working with agile cells

Nowadays, the development of projects through the organization in agile cells is widely spread. As its name suggests, this form of work organization seeks to resemble the behavior of a living cell, in constant change and dynamism. This model is in a way in opposition to the traditional model based on hierarchies, which no longer works successfully in a highly changing environment and with increasingly demanding end customers.

Following this living cell model, in an agile work cell each team member retains his or her autonomy but is in constant interrelation with the other members. In this sense, while each member has a very clear role, this role is complemented by the roles and tasks of the others.

This type of work cells are generally composed of a small number of interdisciplinary professionals who share certain characteristics. Among them, proactivity and creativity stand out, considering that these cells work in a self-managed manner and are free to find solutions in the process of responding to a specific need. It is also key to build good interpersonal relationships, seeking to make the work work work as a whole. Likewise, collaborative work is the essence of this type of cells, where each member contributes to the achievement of the objectives with a focus on the needs of the client, who is always in contact with the project.

In short, it is about generating an environment of innovation and total openness, pursuing the ultimate goal that the whole is more than the sum of its parts. This way of working seeks to speed up software development times, recognizing the importance of human resources even above technologies.

When is it recommended to outsource by hiring an agile development team?

Agile cells are very useful when knowledge and experience are needed. There are different ways of working according to each project, and the cell can be managed by the client itself, by the company that provides the technology professionals or even jointly. Agile cells are also very useful when looking for an efficient end-to-end development, since they seek to minimize deviations from the initial estimate.

Outsourcing by hiring agile cells of IT professionals, allows the client to focus on the core of their business, reducing the technical barriers of new projects, investing only in what is needed according to the different types of profiles required.

In Macrotest we have work cells available for your projects, integrated by multidisciplinary and modular specialized teams that are integrated into the structure of your organizations to develop the technological solutions you require. If you want to know more about our agile cells service, please contact us and we will gladly provide you with all the necessary information. At your disposal you will find all our experience, highly qualified resources, the highest quality standards and our framework that has been evolving for years. All this expertise is at the service of our clients, seeking to optimize their business processes and ensure quality and efficiency in each of the projects entrusted to us.

In the next article we will tell you about a particular type of agile cell, which are the mentored cells. We look forward to sharing this next note with you!

Buying on the Internet… everything you should take into account

Buying over the internet

As we mentioned in the last blog post, e-commerce is growing exponentially both in Spain and worldwide. It is becoming more and more common and frequent to purchase products and services using the Internet, through various e-commerce platforms. Among the main advantages of buying online, we can highlight the possibility of buying at the time we want and without leaving home, without queuing, without waiting, quickly and conveniently, as well as being able to compare prices without having to go from store to store, and even get lower prices and more variety than in physical stores.

But, what should we take into account when buying online?

Below, we will review the main aspects to consider in order to carry out transactions in the best way.

One of the first tips would be to check the web when we see that the offers are too tempting, with a very noticeable price difference between different pages. In that case it is important to pay attention to whether the product is really new or used, or has defects in its packaging for some reason. It is always important to compare prices on different websites before deciding, taking advantage of the advantage of doing it very quickly. Another recommendation is to avoid using public wifi networks, such as in bars or cafes, as the greatest danger is the potential theft of the payment method data. You should also look for information about the store and see the opinions and ratings or reviews that other users have made.

Having an antivirus installed to detect possible threats can be very useful. Likewise, the mobile or computer from which the purchase will be made must be kept updated, since if there are any security or privacy problems, these are usually solved by means of updates. Something fundamental is to check that it is a secure connection. This can be done simply by verifying that the browser bar shows “HTTPS” instead of “HTTP”, and that a padlock appears next to the URL, which indicates that the online store has a security certificate and can be purchased securely.

When creating an account on an e-commerce platform, it is important to enter a secure password (combining letters and numbers), which is not the same as the one used in other services. It is also important not to save the payment method used for future transactions, because it is safer to enter the data every time it is necessary than to have all the bank details stored. If you have the possibility to pay by credit card, it is safer than using debit cards, because if it is necessary to return the product it is easier to get a refund to the credit card than to the debit card.

To make purchases in a more practical and agile way it is important to use filters, and thus obtain results as close as possible to our preferences, avoiding seeing a huge list of products that are not what we are looking for. Likewise, to take better advantage of online sales, it is very useful to monitor prices a few days before and thus ensure that the discounts are real. Another recommendation is to check the stores’ apps, since sometimes there are better discounts that operate exclusively for the app and not for the web. Other issues to observe are the possibility of product returns, the warranty, the shipping method, its times and costs, and customer service and after-sales service.

Remember that Macrotest is a partner of Easy Commerce, an omnichannel e-commerce software platform developed from more than 20 years of experience. We hope these tips will be useful when making purchases through e-commerce platforms!

What are and what is important to know about e-commerce platforms?

E-commerce platforms

E-commerce is here to stay. In recent times, the increase in e-commerce transactions has been exponential. In Spain, 23% of total purchases were made through the internet in 2020, and e-commerce exceeded €12.4 billion in the first quarter of 2021.

What are e-commerce platforms?

It is a technological solution to create and manage an online store, constituting the necessary software for companies to sell to their customers. E-commerce platforms facilitate all the operations of an online store, such as product display, sales, stock control, payments, and promotions.

It is clear that nowadays having a way to reach customers online is key for any company. However, it is important to know what to evaluate when choosing an e-commerce platform.

Among the main aspects we should consider its reliability, its flexibility, the interface for buyers, the ease of use for the company itself (for example, that the configuration panel is intuitive, or the fact of having a mobile application to manage the store), the possibility of accessing analytical data that can be used to design growth strategies, and the support service (preferably 24/7).

When evaluating the interface for customers, we could consider whether the platform has attractive themes to make products look better, whether product views with videos and close-ups can be configured, whether it has a shipping calculator, whether it has call-to-action buttons and comment boxes for customers to post reviews.

We could also analyze the platform according to the size of the company in question, since there are options for specialized packages for small, medium and large companies, with features suited to the requirements of each type of company, even considering whether the type of business is B2B or B2C.

Currently, these types of platforms go beyond being an online store, integrating products, payments and shipments with different sales channels, such as social networks (Facebook or Instagram). Among the main advantages of having an e-commerce platform are the possibility of selling to and from anywhere in the world, the fact of being present and available 24/7 for customers, the reduction of costs compared to a physical store, the simplicity in the automation of inventory management, as well as the possibility of collecting a large amount of valuable data about buyers.

Macrotest is a partner of Easycommerce, with an omnichannel e-commerce software platform developed based on more than 20 years of experience in different countries and in conjunction with different business partners. Among its main features are that it is multichannel, 100% interoperable, cross border, and has multiple integrations with permanent updates.

If you are thinking of incorporating an e-commerce platform, we are waiting for you!

Technology trends… what’s the latest?

Technology trends

Technology is advancing continuously, at an unprecedented pace, and its application is taking place in the most diverse sectors. Agriculture and health are two of the most dynamic sectors where technology is constantly advancing. Below, we review some of the most relevant developments in terms of technological trends.

In the agricultural sector in particular, technological innovations are of such magnitude that they have led to the emergence of new concepts such as “green revolution” or “agriculture 4.0”. An example can be environmental monitoring through electronic sensors installed on crops and the possibility of automating irrigation systems. Another of the most frequent technological applications is the use of drones that, through remote sensing, make it possible to obtain images and videos remotely. The application of artificial intelligence to the management of a large volume of data from agricultural machinery, for example, is also key, as is the Internet of Things (IoT), which allows real-time information to be obtained and facilitates traceability through the installation of devices such as chips. It also highlights the automation of machines and the use of GPS in tractors, allowing to know the exact measurements and distances in crops. The application of Big Data also entails a series of important benefits in the agricultural sector, such as obtaining information on weather conditions, the state of the soil, the crops planted, the amount of inputs needed according to the environment, and identifying anomalies in crops, such as pests or diseases.

In short, the application of these different technologies in agriculture allows not only to improve yields or increase efficiency in the use of resources, but also to anticipate and identify certain risks. For example, at Macrotest we have the Agroint solution for intelligent crop management, minimizing the impact of pests, diseases and weeds through monitoring and geolocated records from cell phones.

The health sector is not lagging behind in terms of new technological trends. In recent years, technology applied to healthcare has not only focused its efforts on saving lives, but also on making daily life more comfortable.

Among the main technologies is the use of virtual reality in medical training, involving realistic scenarios such as surgery or emergencies. Once again, the application of artificial intelligence appears as fundamental, whether to monitor patients, assist surgeries by means of automated devices, or even predict the situation of high-risk patients.

Another trend is access to remote healthcare, for example through online chat platforms available 24 hours a day through chatbots that apply artificial intelligence, or even medical consultations by video call. There are also implantable and ingestible sensors that facilitate the diagnosis, treatment and monitoring of certain diseases through the Internet of Things.

Mobile applications can also be mentioned, which contribute to improving the healthcare system through the prevention, control and treatment of numerous diseases, including monitoring the follow-up of patients with diseases such as diabetes or epilepsy. Meanwhile, Cloud Computing applied to the healthcare sector makes it possible to speed up access to patients’ clinical data, as well as to improve communication between healthcare centers. These trends as a whole currently imply benefits both for healthcare professionals and for the users of the healthcare system.

In this line in Macrotest we have developed a solution for patients who suffered a stroke which allows the realization of their rehabilitation from home, based on years of research, development and innovation.

We are waiting for you to deepen these applications that promote the development of the agro and health sectors.