The role of agility in digital transformation

Role of agility in digital transformation

One of the issues that have had the highest impact on the business landscape is digital transformation. After all, technological advancement has made it necessary to have a higher presence in digital domains. It is for the operational process and the promotion of the company.

Now, did you know what agility is in the digital process? Even knowing the meaning, there is much more to comment on it. It is one of the keys to helping you make the most of this process for future work. 

What is agility, and why do organizations need it for digital transformation success?

In the digital transformation landscape, agility is the inclusion of digital development at the right time. That is, a company can produce transformation-oriented equipment at a rate that benefits the company. This is to meet the needs of a client on time.

In other words, agility, in theory, is related to the company’s ability to react. After all, it is crucial to serving customer requests in the shortest possible time. Thanks to an agile foundation, the company can better respond to and solve problems quickly. 

How can you foster a culture of agility in your organization?

Before talking about digital agility, it is essential to talk about the company’s culture. After all, a team executes digital jobs that must demonstrate agility in their day-to-day management. Some options to promote this organizational culture are the following:

  • Cooperative work in which each team member plays an important role. It encourages problem-solving by taking advantage of each person’s abilities.
  • Trials that lead to sound decision-making should be tolerated.
  • There must also be a culture of empowerment in the work team. A boss or project leader cannot control everything and needs to delegate tasks. It is much more agile when it comes to fulfilling a business process.
  • The process must be worked with short, efficient cycles to know what can be improved. After all, it will be easier to spot bugs that can be fixed.

And, of course, incorporating technology becomes essential when talking about agility in digital work. Serving a client implies having all the tools to make the process as agile as possible. However, it all starts with the company culture itself. 

¿What are some critical components of an agile framework?

Of course, an agile framework cannot be proposed in digital transformation if the necessary elements are unavailable. In any company, these are fundamental to moving to digital operation. Among these elements, we can highlight the following:

  • Individuals having priority over any operation or tool. It is the individuals who can use their creativity to innovate and seek solutions to problems. In addition, the interactions between them lead to faster responses.
  • Software replaces the heavy load of documents that hinder the operational process. Technology allows us to face any challenge that arises in the business environment. In addition, the software can constantly improve, although interaction with individuals is key to this.
  • Adaptability is also being one of the purposes of agility in digital transformation. Although developers may work in organized plans, contingencies will always arise. Therefore, it is essential to know how to adapt to the problem.
  • Collaboration appears as a critical element for agility in digital work. If all the members of a team row towards the same place, it will be easier to reach the objective.

Agility encompasses many vital elements but these four stands out the most. From them, it will be easier to achieve objectives in terms of customer demands. 

Are there challenges or obstacles to achieving agility?

Indeed, some obstacles can stop the whole topic of agility in digital transformation. After all, the presence of a challenge will always be frequent in companies’ operations. The most common are the following:

  • Inadequate management of resources, producing an unnecessary addition of these.
  • Stagnant mentality in a specific work process or mechanism, without seeking to improve.
  • Organization and rigid plans that do not give rise to imagination and developing of new ideas.
  • Believing that only technology is a crucial element for agile work.
  • Low incentives that lead workers to improve.

Many obstacles can lead a company to fail in any future work with agility. It makes it necessary for developers to bet on new work strategies. 

How can you measure the success of your agile transformation?

Since you are applying digital transformation in your company, you will want to measure its progress. After all, it is what will make you know if it is an agile and beneficial process. Some indices are as follows:

  • Reduction of costs in the different operational processes of the company
  • Customer satisfaction with the service they have received
  • Incorporation of workers in the digital transformation process
  • Adherence of the agile transformation to the objectives and strategies of the company

Final thoughts

Of course, many more indicators help you determine the efficiency of digital transformation. It is essential to have an agency like FuzzyFish manage the entire digitization process.Don’t you know what FuzzyFish’s services are? We are the solution to achieve an agile transformation appropriate to the new times. Enter our website to discover everything we have to offer you.

Upfront & Fuzzy Fish: a tech alliance that delivered MVP in a month and the First Client in two

Upfront & Fuzzy Fish: a tech alliance that delivered MVP in a month and the First Client in two

The web platform that Fuzzy Fish designed from scratch for Upfront in just a month, allowed the fintech to obtain its first customer in less than two months. A tool that enables successful re-financing. 100% online and in just a couple of days. The development has two management flows and, since January 2022, includes more than 15 integrations that enabled the fintech duplicate month by month the number of transactions. Find out in this article the secret on how to turn an MVP into a successful and traceable business model.

The finding

In the USA market it is common that people buy utility vehicles for their independent work such as roof installers, construction business, delivery, Uber, among others, through the financing offered by car dealerships.

Upfront Co-founders analyzed the car financing market and found out an interesting fact: 61% of people with a current car loan could get a much lower interest rate, saving thousands of dollars – $2,193 in average -. “Car owners are leaving thousands of dollars on the table. We started Upfront to change that”.

The idea was brilliant and there was a market to start: the demand of hundreds of users and stakeholders. What was missing was to translate the idea into an agile platform, with a tool that enabled a successful transaction, 100% online, in just a couple of days. Upfront needed a strong partner that could translate the idea into programming codes that would make it tangible and profitable. It was time to work with Fuzzy Fish.

From idea to code

With these requirements and after initial meetings, at Fuzzy Fish they fell in love with the possibility opened to them: innovate from a clean slate for an american fintech that today has become a success story. “For us, it started as a client and it became a work style” For Upfront, the MVP allowed them to get their first client. We started slow but steady and then it boomed, says  Sebastian Alvarez, project’s Tech Lead and proud to be part of the team that made it happen. “From a blank canvas, to a product in the cloud and then getting the first client in 2 months. There was no prototype or boilerplate. It was a development that started from scratch”.

“The great thing about Upfront as a business is that it can pre-offer you something very interesting, which is a cash deposit of the accumulated difference. With that money, the customer can make another investment or buy another vehicle. That makes it successful”. Sebastián Alvarez, Upfront Tech Lead.

At Fuzzy Fish they built an interdisciplinary, experienced and autonomous team of tech talents that was fully integrated with the client’s team to drive the project forward and to design the architecture, its different parts and how they were going to communicate with each other. There was a lot of brainstorming before writing a single line of code or “doing the homework,” as Sebastian says. In less than a month and a half, they developed Upfront’s web application https://saveupfront.co/ formatted as an MVP and this initial output is the basis of what is in place today, since it was deployed.

Swiftness in motion

The API that Fuzzy developed for Upfront manages 2 flows and interacts with more than 15 integrations all the time, which makes it super dynamic. With the Client’s name, ID and email, the system activates a circular feedback process: it queries, takes the data, saves it, displays it, and so on. 

In the first flow, the customer enters his basic data. The web app searches a wide range of offers among the lenders that are partners and provides a pre-offer. If the client confirms that he wants to go ahead with the transaction, a link appears that takes him to the second flow, where the data is verified. 

At this stage, the web app is linked to public, private and financial organizations and queries the client’s banking, credit and financial status. With all the information gathered, it enters a flexible decision engine, which is fed by stock market movements, stakeholders and financial markets info. The result of this search engine is sent to the client as a pre-offer, which is converted into a proper offer once all necessary documentation has been presented. Upfront’s operational team checks this documentation and makes the final decision, which releases the signing of the contract. At the end, Upfront withdraws, and leaves the lender and client linked for final deposit management. 

The success of Upfront is the low friction with the client, since it does not ask for validations or sensitive data, avoiding not only strenuous paperwork but also trips to the bank. The document uploading time is the lowest moment of discomfort, since the web is linked to different integrations that simplify the customer’s life.

These integrations made it possible for Upfront to obtain a monthly duplication in refinancing, avoiding user queries such as: “I got stuck in such and such a step, it won’t let me continue”. From January 2022, they went from 32 to 64 refinancings, to 128, and so on, month by month.

Highly integrated team

The project kicked off in May 2021, when Fuzzy Fish developers began writing their first lines of code. By June, the MVP was productive – with all the infrastructure and architecture completed. In July, Upfront converted its first refinancing. 

The strategic challenge that Fuzzy Fish overcame in less than a year was to shorten the gap between the MVP and the formation of a consolidated team, working full time for Upfront and side by side with the CTO.

Partnering with fintech developments of this magnitude, positions Fuzzy Fish among the first agencies dedicated to providing the best talent and nearshore engineering teams, ready to fully integrate and drive technology projects through unique IT solutions in the market and 100% customizable. This is a model case, an arrowhead, that spills over to the rest of the clients and projects that Fuzzy Fish has running and that, surely, will open the door to new markets, clients and industries that are interested in being at the forefront of technology.

Top strategic priorities in data-driven decision for 2023

Data-driven decisions

Data has become the new oil. It is the lifeblood of contemporary organizations, and its strategic importance is only going to grow in the coming years. To stay ahead of the curve, companies must make data-driven decisions a top priority.

To make your company evolve and earn money, a data-driven decision should be the order of the day. You cannot ignore its importance. Read on, and you’ll find out why.

Understanding the value of data in 2023

Although the data-driven decision is already made in the companies with the most significant global impact, they have not yet reached their most relevant phase. Those most versed in this subject believe that in 2023 it will be its boom. They think that in the year we are approaching 2023, the schemes established until now will collapse.

This is because companies will be accessing and differentiating data and metadata through machine learning, starting with the largest. Software being developed by 2023 will be more refined and aided by AI. That’s why analytics leaders like us, FuzzyFish, will be at the Forefront.

Strategic priorities in data-driven decision

The basis of a data-driven decision is that it’s based on facts that will give the option of a commercial effect that substantially raises your company. So, the developers of this software aim that those who use them get:

1. The increase of your negotiations, therefore, your profits.

2. The effectiveness of the behavior achieved.

3. That all the operations to be carried out are optimized.

4. The team exceeds its performance.

5. Access the data source. That is, to the systems that can provide them to you. In this way, you can achieve investment returns and increase the number of active clients, productivity, continuous profitability, and gross profit margin.

6. Efficiently organize the information obtained.

7. Effectively analyze all data.

8. Conclude concretely and correctly based on the results of the analysis.

To achieve all the above, you must know very well what you want. Have a precise vision of your business. This will redirect the client who will be interested in your proposals or offers.

Develop a data-driven culture

This technology of data-driven decisions will be inserted in all future work. It is a digital transformation that cannot be left aside by anyone who wants to succeed.

Currently, it is the most effective way to understand how to reach the customer and make the sale happen. In addition, it complies with digital organization tasks that allow perfect control, which results in significant benefits.

You will feel supported and safe, making everything work with coordination and effectiveness. It will undoubtedly help you emerge quickly and keep your company well positioned.

Building a foundation for data governance

Technology that covers a series of procedures that offer you the guarantee of keeping protected:

  • The integrity of the company
  • Documents
  • Safety
  • The audit carried out on the data

Reliability is based on internal policies and controls that protect the information, including managing its quality in all phases. Data governance will be the most relevant asset for your company’s success. Its main objectives are:

  • To ensure the proper use of data
  • Precise analysis without going outside the rules
  • Also, that what is decided is correct and improves every day
  • That data management experts have better access to them
  • To reduce the costs invested in managing this data
  • That the data is of better quality

Knowing the importance of data governance, it is challenging for you to build a foundation for it.

Leveraging analytics for insights and decision-making

There are different types of data that help corporations to attract customers, among which are:

  • Accounting data.
  • Customer information received through CRM systems.
  • Data obtained through payments made in web stores.
  • ERP transactions.
  • Information recorded through calls, business systems, intelligent meters, weblogs, etc., is also known as “machine-generated.”
  • Data that comes through social networks.
  • The data companies generate with the invoices of their customers, suppliers, etc.
  • Biometric information is generated by placing fingerprints, facial recognition, or scanning the retina.

All these and other ways you provide your information, data, tastes, location, etc., are analyzed and distributed in such a way that they are used to capture your attention.

Therefore, data leaders and experts in these systems will be required in all public or private companies, banks, restaurants, and businesses.

Managing data complexity

The work will also increase when your company grows, so its flow will increase. This management will be your ally so that all growth is done with the organization while maintaining the company’s global vision.

You will not use rules that are not necessary, and you will put together procedures that are efficient to keep everything running smoothly.

The future of data leadership

By coming this far, you have already understood that data-driven decisions will lead in the future. The data is what will allow you to reach the clientele. Therefore, they will be the future work and what will make you truly successful.

Final thoughts

Data leadership will be a critical factor in any company’s future success. Those who can harness the power of data and use it to make informed decisions will be the ones who succeed. Data governance, analytics, and managing data complexity will all be important factors in data leadership.
Companies embracing these challenges and obstacles in data. Leadership will be in high demand in the coming years as more and more companies move towards a data-driven model. To stay ahead of the curve, in FuzzyFish we are a data-driven company.

Happiness in the workplace: Are your developers happy?

Happiness in the workplace

Finding a job that makes us happy is not easy. It is one of the most significant difficulties we go through in the professional world. At FuzzyFish, we know that happiness in the workplace is the key to success because a happy worker will be a productive worker.

As a company, we always think about the well-being of our employees. Thus, we are not just talking about a good work environment. We also understand that growth opportunities are the success secret.

This translates into the services we offer, the satisfied customer, and the quality of our brand; it all starts at home. Therefore, you must also take care of your workers to be successful. In the end, they are the corporate representation of your image.

Especially when it comes to developers, we know that what is valuable is the person behind the result. In addition, the skills we have hired and the value they add. For all this, offering them happiness at work will allow them to stay with us, and we can grow together.

The definition of happiness in the workplace

Happiness in the workplace means our employees’ well-being and directly relates to how our workers feel. The level of excellence of a company can be measured in sales, but there is much more behind them.

Happiness at work includes the achievement of essential goals for our corporate purposes to be achieved. For example, a happy developer will be punctual and motivated by challenges so that our developers will fulfill more optimally the responsibilities we assign to him.

This term is relatively new and has become very relevant. The reason is that we have verified that a company with job happiness has better sales and performance in the market.

What factors influence happiness in the workplace?

If we want to improve our employees’ happiness, the first thing we must be clear about is that not everything is about salary. If we keep high and strict demands, even if the salary is good, we will have stressed and unhappy employees.

So, what can we do? Be flexible. Not everything has to be done according to a strict pattern but still, developers have to deliver their projects on time. At FuzzyFish, we recommend that you remember that your employees are also people. So it is better to be clear on deadlines.

Being aware of this will help us be part of their work-life balance and help them achieve their goals. Also, knowing their interests will be essential to keep them motivated. Between the routine of work, a work environment that feels empathetic and safe will add happiness.

How to measure the happiness of developers

A great way to measure the workplace happiness of our coding specialists is to pay attention to their performance. If it is low, something may be going on, and we may need to pay attention to their surroundings to help them.

When we hire, we must be aware of their personality characteristics. The key will be communicating, getting to know them, and maintaining that line of contact regularly.

In FuzzyFish, we have one-on-one interview spaces between the developers and people in charge of People care. This allows us to know our collaborators’ motivations and needs to serve them best. This is how we focus on the happiness in the workplace that we seek to achieve.

Strategies to increase the happiness of developers

From our commitment to increasing happiness in the workplace, we carry out a benefit policy centered on people’s experiences. In this way, we have actions and benefits focusing on the quality of life for our developers.

Another strategy we can apply is to offer them training and courses on topics that interest them, helping them continue learning and improving. Accepting and developing their ideas will also be essential to having a happy developer in the company. In FuzzyFish people come first. That is the reason why we invest in high-end and premium training courses.

Also, showing them the result of their work is an excellent strategy to increase their happiness and motivation. Developers often don’t see all their code accomplishes, so making it part of the final product will make a significant difference.

Please encourage them to take time off when they need it

Especially in this kind of work we don’t need to have them on total working hours, although it is often difficult to get them off the computer. At FuzzyFish, we propose 100% remote work to motivate your personal life.

We’ve debunked the myth that our employees need to be in the office for happiness in the workplace. Work is not a place; it results from the effort and time our developers have invested in the company.

Give them plenty of breaks to avoid burnout

By spending so many hours in front of a screen, the exhaustion of our developers is our worst enemy. We recommend establishing rest times or alternative activities that help to rest for short periods. We look for quality more than speed.

Having more complete measurement strategies such as pulse surveys will be our allies. These surveys constantly measure well-being, work environment, quality of software offered, and others essential to make constant improvements that increase happiness in the workplace.

Final thoughts

It’s essential to remember that happy employees are more productive. When developers feel comfortable and appreciated in their work environment, they will be more likely to produce high-quality work. Implementing the abovementioned strategies can help create a workplace conducive to happiness and success.

At FuzzyFish, we believe that happy employees are more productive employees. Therefore, we strongly emphasize creating a work environment that is conducive to happiness and success. By offering flexible schedules, 100% remote work options, and plenty of opportunities for breaks and training, we strive to create an atmosphere where our coding specialists can thrive.
We also use pulse surveys to constantly measure well-being, work environment, quality of software offered, and other factors essential to constantly improving. Our goal is to provide a workplace where our coding specialists can be happy and prosperous.

MVP vs. EVP: Is It Time to Introduce Ethics with an Ethical Viable Product?

MVP vs EVP development

For some time now, the idea of developing an Ethical Viable Product (EVP) instead of an MVP has been gaining strength in the market. Until now, companies have been using the MVP model due to the many advantages it offers.

However, like products, consumers have also been evolving, and developing functional products is no longer enough. Today, technology and digital products can greatly impact people, whether for better or worse.

So, is it time to consider ethics when developing new products and applications? Everything seems to indicate that it is. From a small startup to the largest company, they should include ethics from product development and during all subsequent phases.

How MVPs have successfully brought products to market?

One of the critical stages for any company is the development and launch of its initial products. Only one in ten startups survive this initiation period, usually thanks to implementing the MVP model in their businesses.

An MVP (minimum viable product) is a minimalist version of a product launched to collect consumer feedback.

This version usually offers all the main features of the final product but with limited functionality. In this way, by receiving feedback from their customers, developers focus on improving the product by meeting the specific needs of users.

Thanks to an MVP, companies can create solid and high-performance products, using the information obtained as a guide in product development. This business model has been helping thousands of startups succeed for over 20 years, even turning them into multi-million dollar businesses.

What is an EVP or an ethically viable product?

An EVP (Ethical Viable Product) is a product that does not cause any harm to its users or the environment. In the case of technological developments, it must guarantee that these do not negatively influence people’s behavior.

In recent years, the environmental issue has received more attention from companies. This is evidenced in the new marketing strategies emphasizing that their products are “environmentally friendly.”

In technology, the advancement of artificial intelligence and machine learning has become a challenge for developers. It is expected that in the future, the influence of AI in decision-making will increase.

This puts developers in a big dilemma: How can you ensure that the decisions made by the AI ​​are ethically correct? The answer to this question is clear: Ethically Viable Products (EVPs) should be created instead of MVPs.

To achieve this, developers must include ethics from the very concept of the product through the development stage, launch, and subsequent monitoring.

What is responsible for artificial intelligence?

One of the main elements to consider when developing an ethically viable product is the implementation of responsible artificial intelligence. With machine learning, you have to be careful about the AI’s database to perform its functions.

This AI must consider various ethical, moral, legal, and cultural issues and establish limits and rules for decision-making. This information must be delivered without deviations or prejudices since the AI will use that information when making complex decisions.

How EVP and RAI are combined?

Responsible artificial intelligence is closely related to an ethically viable product since it will be in charge of solving the problems faced. A product whose development includes ethics from its inception must be driven by an AI aligned with its design and purpose.

When using an RAI to create an EVP, developers must consider its security, fairness, reliability, inclusivity, and responsibility. If all these aspects can be combined in an EVP, the resulting product will be robust, ethical, and morally responsible.

Is it time to migrate from MVP to an EVP model?

As we said, we are in a moment of transition from the MVP to the EVP model. However, developing ethically viable products does not mean abandoning the LEAN methodology applied in an MVP but rather evolving an existing successful model.

Another aspect to consider is the environmental impact caused by each product, even if it is software or another technological product. Please, note that during the build stage, energy resources will be consumed by the development, hosting, and testing required before launch.

In simple words: How can you introduce ethics in your MVP?

If you are thinking of introducing ethics into your MVP, you should take a few steps to get there. First, you’ll need to appoint someone to lead an ethics team to oversee product development.

This person will be responsible for interacting with all the parties involved in the development phase, guaranteeing a final product according to the established parameters.

Second, ethics must be included in all phases of development, facilitating the integration of responsible artificial intelligence into the final product. After all, an ethically viable product will need to be driven by an RAI that is the decision maker.

Lastly, consider the regulations that could be applied to AI/ML systems, even contemplating those that could arise in the future. In this way, if a new law is passed, it will be easier for you to adapt your product to the new regulations.

Final thoughts

The MVP model has had great success in the past, but now it is time to move on to the EVP model. This new model takes into account the ethical implications of products and includes them from the design phase. Including ethics in product development is not only the right thing to do, but it is also necessary to create better products that have a positive impact on society.

What do you think? Is it time to introduce ethics with a viable ethical product?

Until you have experience, experiment: Why MVP matters

Why MVP matters

The MVP, or minimum viable product, is a critical concept in the startup world. The idea is to create a bare-bones version of your product or service and get it out to market quickly to gather feedback and learn from real users.

In entrepreneurial terms, tangible or digital, what the atom is to the matter is the smallest part of something you work hard to succeed in a more significant way. Faster and safer.

While running the process to create a new product carries on every uncertainty inside the development team and a lot of wondering about the UX view. That is because some theories were born to check and test customer working and reception BEFORE developing a Minimum Viable Product and walk strong with your ideas.

An MVP also becomes the first version of your product that speaks about the marketing prospect from an App or new software and ensures up to 25% of resources, saving an unnecessary and predictable capital risk. So, why does MVP matter?

What is an MVP?

The MVP is a product with just enough features to be usable by early customers, who can then provide feedback for further product development. The MVP is not a stripped-down version of the final product but is also not a fully-featured product.

The MVP is the first step in what is known as the Lean Startup methodology,  which is a way of starting and running a startup that is focused on minimizing waste and maximizing learning.

Why MVP matters in short

This approach has several advantages. First, it allows you to test your hypotheses about what users want and need without wasting time and money on development. Second, it will enable you to learn from users and make changes before you have a fully finished product.

The MVP is also a great way to get started if you don’t have much experience building products. By starting small, you can gain valuable experience and knowledge without putting yourself at too much risk.

So, if you’re starting a new project or product, don’t be afraid to experiment and start with an MVP. It could be the key to your success.

What is not an MVP? 

MVP is not a ‘Prototype’ or a ‘POC ‘ (Proof Of Concept). Even the concept is confused by a lot of Devs fans, ‘product’ (an MVP-product), as its name speaks, is a functional starter but not an incomplete solution for an asked need that is not just a ‘Prototype’ because this is not going on the field, at the right time, to catch opinions and analyze the relevance to the people.

The purpose of a prototype is to explore and verify proposals before discussing them with stakeholders and ultimately delivering final versions to development teams for their realization of what is not a POC. An MVP provides a complete description of an occurrence or idea, representing its prospective feasibility, success, and impact according to suggested usability, properties, capabilities, and overall structure. 

MVP examples

The new century. From a little earlier, in the ’90s, the concept of an MVP was cooked primordial from too many ideas, tags, steps, or labels of the complete how-to manual from XXI ways to get noticed. So, the references are the flat view, and each one of these revolutionary digital brands shines by itself because they work and grow.

Then is just a check question about traditional and practical solutions such as Airbnb, Amazon, Uber, Facebook, Dropbox, Snapchat, and indeed all the new startups at date. The standard choice that all these masters of UX experience token at the first moment was the care walking, the proper perspective, trust in users’ media reactions, and great ideas created from natural observation:

Dropbox

The first version of Dropbox was a simple tool that allowed users to sync their files between computers. It was nothing fancy, but it did the job and helped people solve a real problem.

Airbnb

The early versions of Airbnb focused on helping people find a place to stay when traveling. They didn’t have all the bells and whistles of today’s platform, but they had the core functionality that people needed.

Dropbox and Airbnb started small and built out their products over time based on user feedback. And both companies are now huge successes.

So, there you have it: MVPs matter because they allow you to experiment, learn from users, and make changes without putting too much at risk. If you’re starting a new project, don’t be afraid to start small and iterate until you find a winning formula. MVPs are a vital part of the startup process.

The MVP is also not a product you release and then forget. An MVP is meant to be a living, breathing thing that you continue to work on and improve over time. Remember, the goal is to learn from users and make changes based on that feedback. So, don’t be afraid to experiment and iterate on your MVP until you find a winning formula.

Benefits of building an MVP

Fortunately, there are many reasons and several benefits to building an MVP. These include:

  • Allowing you to test your hypotheses without sinking a lot of time and money into development
  • It gives you a chance to learn from users and make changes before you have a fully finished product
  • Helping you gain valuable experience and knowledge if you don’t have a lot of experience in building products
  • Starting small and focusing on the essentials
  • Being a living, breathing thing that you continue to work on and improve over time

Same issues can be talked like check-listed points to mark when the exercise looks like it must:

  • Validate the hypothesis
  • Сollect feedback from real-time UX’s
  • Adjust the right solution
  • Expand and catch the audience more quickly
  • Start making a profit before it is complete by selling the MVP
  • Encourage the investors to add the project
  • Save money on market and target audience analysis by combining analysis with development

In the end.

  • “Imagine, MVP product is like a tasting sample of the fancy multi-tier wedding cake. Before ordering it for reception, you get a couple of pieces to choose biscuits and frosting, provide your feedback and let the baker make corrections.”

How does a software factory start to plan an MVP?

Although general MVP concepts are very accessible to public learning and practicing to build a commutable itinerary away the goal, just for this reading, we could highlight some basis (keywords: Problem-Public-Competitors)for fast-memo, such as:

  1. First, it must determine the trouble or need (or hobby) to resolve. Answer some big questions about targets, features, and hooks at clients in a previous and safe phase.
  2. Find an objective public to compact it at maximum. Meanwhile, Devs create some ‘avatars’ from it, checking statistic information such as ages, sex, education level, earnings, etc.
  3. Analyze the market objectively before your proposal, watching and researching potential competitors and proceed to recheck the balance, discovering weaknesses/advantages from others to set your hypothesis and marching behavior from MVP that belongs to you.
  4. Establish the UX’s flow. It means the path to follow while interacting with the product. This way may assimilate where and what features are more relevant to them, so develop the design, sequence algorithm, and many more periclase and valuable details.
  5. Try testing A/B mode on the MVP. Alpha tests are this class of proofs when it is evaluated by the immediate environment, as own Devs and closer people; and Betas ones include the same evaluation from real users that try the product at purpose during a bit time, to add elaborated opinions about it. This focused and cycling data source is dynamic until the result is caught.

 Final thoughts

The MVP is a crucial part of the startup process. It allows you to test your hypotheses without investing time and money into development. MVPs also will enable you to learn from users and make changes before you have a fully finished product.

Building an MVP can be a great way to gain valuable experience and knowledge if you don’t have much experience building products. MVPs also allow you to start small and focus on the essentials.

An MVP is not a finished product but a living, breathing thing that you continue to work on and improve over time. Ultimately, the goal of an MVP is to validate your hypotheses, collect feedback from users, and adjust your solution as needed.

Remember:

  • MVPs may be used to test the product and the marketing. For example, cookies, mail lists behaviors, conversions, ROI, costs, operative spending, and design.
  • The truth is that several types of MVPdo exist. In the middle of all this previous information, suddenly, you would find additional tags that define each process of creating and developing. Thus, it would help if you faced these main things as Wizard of Oz, which is suitable for testing the solution, counting with a few features. Piecemeal is the best to try ideas, already existing services, and sites without paying extra resources. Concierge MVP refers to a human-based resolving method with solutions at the reviews taken from real subjects as first ‘consumers’ and picks up constructive feedback winning time; and Single Feature type, called ‘One painkiller’ as a template to verify the technical feasibility of the baby product. Say just the meaningful ones. Only.
  • You can find and onboard an in-house developer or outsource the process to build an MVP. The excellent advice is to choose an off-site team for MVP product development. Two reasons: it is seamless and budget-friendly. 

React Test-driven Development: How to implement

In the last decade, has succeeded a new and massive interest in the developer’s community about clean code, just because it offers some great tests to run while they are building apps, and real expectation -avoiding to/ express it like concern- to keep on walking ahead with these tasks and getting best and viable, each day the planning.

But reality tells us that it is not true that this stuff exists. There is no way we can copy or replicate automatically on each project while we get the best results. At least it will work and reach the standards equally. Let’s imagine you are in charge of one with a lot of e2e tests, and you win more value than others because it needs logic and the app is based on the UX interaction; what would not be happening in another project of yours, if you win significant relevance by having unitary tests more granular, at the reason of components recycling.

Reality says too, that what does exist, is the feature inside its app that programs the best auto-solution itself. To make this, the test-driven development (DD) is the ‘one’ tool to balance your codifying developments. So, from here let’s talk about this subject, of React JS like the landing of ‘how to’ do this duty.

Importance of Test-Driven Development (TDD)

Kent Beck created the TDD technique in 2002. The objective was to develop new software in writing short cycles as part of the eXtreme Programming (XP) methodology. First, executing an automated test failing, second making a minimum required to pass, and finally, making the refactor step to eliminate redundancies. Yes, a cycle.

The red, green, and refactor are the essence of test-driven development.

What about TDD
Image by Digite

Then we have these colored steps, to ensure our app is working and to catch personal guarantees: Red to start an automated test, planning before it fails, and watching a red text on test runners. Green to try a little fix-it some way, getting the green text on test runners. And target applying refactor tricks, good practices from SOLID, and other code principles created. The red-green-refactor cycle is repeated as many times as necessary until the feature has been completed.

Why should you use test-driven development with React?

The main reason for increased software quality is not the TDD practice by itself but the automated tests produced through it. The common question is: ¿What is the difference between using a test-driven development and writing the test later?

The developer gets feedback from the test. The difference is in the amount of feedback, precisely. When the developer writes the tests, only after implementing the production code, a lot of time has passed already without the developer getting any feedback on it.

The earlier the developer receives feedback, the better. When one has too much code already written, changes can be cumbersome and costly. Conversely, the less written code, the lower the cost of change.

And that’s precisely what happens with TDD practitioners: They get feedback at a time when change is still cheap. The other reason is that when following TDD a high test coverage is guaranteed, whereas a traditional approach might leave you with only a few tests when time runs short.

When to use Jest and React testing Library?

React testing library Is not an alternative to Jest. Each performs a clear task and you need them both to test your components. Jest is a test runner that finds other tests, runs them, and determines whether these passed or failed. Additionally, Jest offers us functions for test suites, test cases, and assertions. Let’s clear both definitions.

Jest is a test runner that finds other tests, runs them, and determines whether these passed or failed. Additionally, it offers some functions for making suite cases as well as Assertions which both help in testing our components effectively with ease of mind knowing they won’t cause any surprises when used together!

Jest is a JavaScript testing framework that allows developers to run tests on JavaScript and TypeScript code and integrates well with React. It is a framework designed with simplicity in mind and offers a powerful and elegant API to build isolated tests, snapshot comparison, mocking, test coverage, and much more.

So, React Testing Library

React Testing Library is a JavaScript testing utility built specifically to test React components, that simulates users’ interactions on isolated components, and asserts their outputs to guarantee the U is behaving correctly. React Testing Library provides virtual DOMs for testing React components.

Any time tests are run without a web browser, we must have a virtual DOM to render apps there, interact with the elements, and observe if the virtual DOM behaves like it should: like changing the width of a div on a button click.

Final thoughts

React Testing Library is not specific to any testing framework, but we can use it with any other testing library. Although Jest is recommended and preferred by many developers create-react-app uses both: Jest and React Testing Library by default.

Additionally, react-scripts automatically set up our server to watch for changes. So, if the test file is modified, the server automatically compiles and runs the test without needing to restart your server.

Terraform vs. AWS CloudFormation

Terraform vs. AWS CloudFormation

Jump down from your cloud! And let’s talk about clouding information, and the serious thing is to make the best choice between Terraform vs. AWS CloudFormation. There are two main ways to manage infrastructure on AWS: Terraform and CloudFormation. Both have their pros and cons, but in general, Terraform is more popular and widely used than CloudFormation. Here’s a quick overview of the main differences between both.

Terraform is a tool for building, changing, and versioning infrastructure safely and efficiently. Terraform can manage existing and popular service providers as well as custom in-house solutions.

CloudFormation is a tool for modeling and provisioning AWS resources. It allows you to use a template to create and delete all the resources needed for your application in an orderly and predictable fashion.

To assimilate the concept, you will have to learn about the infrastructure as a code, to blow all doubts about how you could start to build under a software basis if you get genuine interest in this. Followed by the exposure to the benefits and troubles of both popular options.

Is Terraform and CloudFormation the same?

No, Terraform is not the same as CloudFormation. They are both infrastructure as code (IaC) tools, but they differ in terms of how they are used and what they are used for. There are too many differences in conception and design. If the question refers to Terraform and CloudFormation working in the same industry, yes.

These tools are designed to apply changes in infrastructure to code file level, and it has been a success for organizations to save overcoats and resolve each challenge from their estate in minutes.

Terraform is a tool from Hashicorp that allows you to define your infrastructure as code. This means that you can use a single configuration file to manage all of your AWS resources. Terraform also supports multiple cloud providers, so you can use it to manage resources on other clouds besides AWS.

CloudFormation is an AWS-specific tool that allows you to define your infrastructure as code. This means that you can use a single configuration file to manage all of your AWS resources.

The big deal is that just one of these is more friendly than another if we are discussing compatible tools in the market.

Checking the balance Terraform’s <Pros and >Cons

Terraform is currently the open code most known cloud provider tool created by HashiCorp to onboard implementations from an agnostic concept of HCL and:

  • Find the freedom to integrate and display it with many cloud providers, such as laaS, CDK, and even BBDD as Google Cloud Platform, Azure, GitHub, GitLab, Datadog, and a lot else.
  • Language and intuitive user interface: Terraform uses a similar JSON; the HashiCorp Language (HCL) defines the resources, and other data and results are straightforward to catch and follow the documentation, even to junior developers.
  • Terraform performance executes itself faster than CDK from AWS because it takes longer to convert the code at CloudFormation templates.
  • Terraform, as an open-source project, is not free. So, it offers licenses to devs users like an enterprise product, including support.
  • When dealing with the right IAC tool, as part of a big project being run by several devs. Although it is as simple as learning a new code, some programming data handling results are not easy to do. At least not for juniors.
  • There are still some provider options missing. So, some work needs to be done manually.
  • The state file management could be better. Although wrapper solutions like Terragrunt exist, Terraform’s native capabilities, with state management, would be even better.

Cloudformation pros and cons

CloudFormation is accessible to provision AWS resources and updates them. It supports rollback. It also allows you to see the changes that will be applied using changesets. It is transactional; either all the resources are updated, or none are.

  • AWS is the world’s leading cloud computing service, with twice the market share of the following cloud provider after it. There are over 200 services on AWS that can serve hundreds and thousands of use cases.
  • CloudFormation will save you plenty of time if you have multiple environments for your application. You create one template and use it for all, knowing they will behave as expected.
  • It has well-designed documentation, which helps me to effectively use the features and integrate with other AWS services.
  • CloudFormation’s templates cannot have complex logic, making them easy to understand. But this limited logic support sometimes forces us to create separate files for our development and production environments.
  • The syntax is notably more confusing. HashiCorp’s HCL makes it much easier to write and visualize what it is trying to create. CloudFormation only works on AWS; if you are working on anything else, you’ll have to learn a different tool.
  • Once you create the stack in CloudFormation, it is impossible to change the stack’s name.
  • For troubleshooting, tracking error logs in the associated Cloud Watch entries is quite challenging in CloudFormation.

How does Terraform fit in your infrastructure?

Terraform has several advantages over manually managing your infrastructure: Terraform can manage infrastructure on multiple cloud platforms. The human-readable configuration language helps you write infrastructure code quickly. Terraform’s state allows you to track resource changes throughout your deployments.

How does CloudFormation fit in your infrastructure?

Rather than bothering with this, CloudFormation offers a way to model the structure and configuration of all of your resources. This is done with a YAML or JSON template, which contains all the required info for your product stack, including resources that need to be created, parameters and configuration for those resources, and the outputs they return. This file can be version controlled through Git and even used to create a continuous deployment pipeline that will automatically push changes.

What about Ansible and Puppet?

Ansible and Puppet are both configuration management tools. This means that they can be used to manage your infrastructure, but they are not specific to AWS. Both Ansible and Puppet can be used to manage AWS resources, but they will require additional plugins or modules to do so.

Ansible is widely considered to be simpler to install and use. For this reason, although it is not the best alternative for Terraform, it does fit very well in the next phase after creating the infrastructure, which is provisioning it.

Puppet is model-driven and was built with systems administrators in mind. It Follows a client-server (or agent-master) architecture; you install Puppet Server on one or more servers and then install Puppet Agent on all the modes you want to manage.

Final thoughts

Overall, both the AWS CDK and Terraform are mature and powerful tools. Terraform has a slight drawback when it comes to data manipulation. Using workarounds and performing data transformations becomes easier once you get familiar with writing Terraform.

Terraform is an obvious choice for multi-cloud operations; however, the AWS CDK is an excellent option if you want to use AWS as your cloud provider.

But that is why if we add to Terraform the use of other specific provisioning tools, such as Ansible, which, among other advantages, will be able to inform us of the errors and more helpful information found during a said phase, we can have a complete solution to automate the entire process of creating and configuring new resources on demand.

Leave your experience and intuition to decide when you must face up to them.