by Tomás Freyer | May 9, 2023 | Artificial Intelligence
Predictive analytics tools are AI applications that have the potential to transform the healthcare industry, among others. By analyzing vast amounts of patient data, AI algorithms can predict the likelihood of developing certain diseases and identify which treatments are most likely to be effective for a particular patient, por example. In this blog post, we will explore how developing predictive analytics with AI can improve the goals of the healthcare industry.
Its contributions can be highly positive in these areas:
- Early Detection of Diseases: One of the main goals of the healthcare industry is to detect diseases early, when they are most treatable. Predictive analytics can help achieve this goal by analyzing patient data to identify those at risk of developing a disease. This allows doctors to intervene early with preventative measures or early treatments, increasing the chances of successful outcomes.
- Improved Patient Outcomes: The healthcare industry is focused on improving patient outcomes, and predictive analytics can help achieve this by identifying which treatments are most likely to be effective for a particular patient. By analyzing patient data, AI can predict how a patient is likely to respond to a particular treatment, allowing doctors to tailor their approach and improve the chances of success.
- Reduced Healthcare Costs: Another goal of the healthcare industry is to reduce healthcare costs. Predictive analytics can help achieve this by reducing the need for expensive and unnecessary treatments. By analyzing patient data, AI can predict which treatments are most likely to be effective for a particular patient, reducing the need for trial and error and potentially saving money on ineffective treatments.
- Personalized Medicine: The healthcare industry is increasingly focused on personalized medicine, and predictive analytics is a key part of achieving this objective. By analyzing patient data, AI can create personalized treatment plans based on a patient’s unique characteristics, such as genetics and environmental factors. This can lead to more effective treatments with fewer side effects.
- Improved Population Health: The healthcare industry is also focused on improving population health, and predictive analytics can help achieve this goal by identifying trends and patterns in patient data. By analyzing large datasets, AI can identify risk factors for certain diseases and help healthcare providers develop targeted interventions to improve the health of populations.
- Training: You could build your own training platform using OpenAI. Through the “Information Search” function you can get online data about drug types and typical information contained in a drug package insert and then you can design personalized exams. Using the “Text Analysis” function you can compare the text of the information obtained versus the text of the answer entered by the trainee and according to the % of accuracy obtained give a score to his answer.
In conclusion, the development of predictive analytics tools with AI can help improve the goals of the healthcare sector by enabling an infinite range of possibilities and solutions to industry needs. As with any AI application, it is important to ensure that predictive analytics is developed and used in an ethical and transparent manner, with the interests of patients at the Forefront.
When looking for a software development vendor working with an OpenAI-powered model, it is of high importance to verify that they have a strong commitment to ethical and patient-friendly practices in the development of AI applications for the healthcare sector. At Huenei we have a strong privacy and data protection policy that ensures that patient data is protected and used in a transparent and ethical manner, ensuring the best results and a highly satisfactory user experience.
by Tomás Freyer | May 6, 2023 | Artificial Intelligence
How can you make a Chat GPT integration with OpenAI models into a software development successfully?
Technology advances by leaps and bounds and provides us with more solutions and possibilities to explore in the world of development, which can take us to unimagined places. The need to be constantly at the forefront of this range of possibilities, leads us to be in training and learning 24/7, which allows us to incorporate new expertise to, for example, integrate OpenAI models within projects with cutting-edge technology, such as a Chat GPT integration.
In this blog post we want to share with you how together with one of our large clients we have managed to implement a concrete business case where we made a Chat GPT integration into a custom software solution.
The objective of the application is to provide a dynamic and flexible training platform for the sales force of a renowned pharmaceutical laboratory, with the ability to obtain online information without the need to perform previous data uploads, saving costs and time.
The software solution, beyond including standard user, group and profile administration functionalities, contains modules related to training management: roles, suggested exams per role, exam form and results tracking per exam, per role and per group.
The important innovation we achieved is the integration with Chat GPT combining two of its main functionalities: Information Search and Text Analysis.
After a series of concept tests carried out by our team of Prompt Engineers together with business specialists on the client’s side to refine the parameters that allow us to obtain information in an accurate, reliable and fair way in terms of the amount of bytes sent and received to optimize costs, we concluded the following:
- We use “Information Search” to obtain online information related to drug types, typical information contained in a drug package insert.
- We use “Text Analysis” to compare the text of the information obtained versus the text of the answer entered by the user and according to the % of accuracy obtained we give a score to his answer.
The sum of your scores will give you a final result that is recorded and will be part of your training record through integration with your LMS (Learn Management System).
The results are amazing with a tremendous positive impact for the client in terms of cost and time due to the high degree of automation of the process for training your sales force.
by Tomás Freyer | May 6, 2023 | Artificial Intelligence
Organizations are constantly seeking ways to boost productivity, streamline processes, and improve customer experience; Generative AI is helping them achieve that thanks to OpenAI benefits.
Generative AI can be particularly useful in business software applications in several ways. Let’s go through some OpenAI benefits:
- Data Analysis: Generative AI can be used to analyze large amounts of data and identify patterns and trends. This can help businesses make better decisions and optimize their operations. For example, generative AI can be used to analyze customer data to identify buying patterns and preferences, which can help businesses tailor their marketing strategies to specific customer groups.
- Personalization: Generative AI can be used to personalize the user experience in applications by generating customized content for each user. For example, a news application can generate personalized news articles for each user based on their reading habits and interests.
- Training: Generative AI can be used to create customized content training in many subjects for different departments of your organization. (Sales force, technical training, etc.)
- Predictive Maintenance: Generative AI can be used to predict equipment failures and maintenance needs by analyzing data from sensors and other sources. This can help businesses avoid costly downtime and reduce maintenance costs by performing maintenance only when needed.
- Regionalization: Generative AI can be used to regionalize your app to different languages and expand its global reach.
Generative AI can help businesses streamline operations, reduce costs, and make better decisions by leveraging the power of data analysis and machine learning. However, businesses must exercise quality control over the generated content to ensure its accuracy and consistency.
In conclusion, Generative AI is proving to be a game-changer for businesses looking to improve their operations and customer experience. OpenAI benefits organizations by providing them with advanced data analysis, personalization, training, predictive maintenance, and regionalization capabilities. By leveraging these benefits, businesses can increase productivity, reduce costs, and make better decisions. However, it is crucial for businesses to ensure the accuracy and consistency of the results through quality control measures. With OpenAI model-powered development services, businesses can create customized models that deliver real results and take their operations to new heights.
As a provider of OpenAI model-powered development services we can help you create custom models that deliver real results and take your business to new heights.
by Tomás Freyer | May 6, 2023 | Process & Management
Digital product development management is a complex process that involves several steps, from idea generation to product launch and post-launch evaluation. To ensure success, it is important to understand the key aspects of digital product development management and best practices for effective management.
In this article, we will explore the steps involved in digital product development management and provide a checklist for successful management. But first, let’s discuss what digital product development management is and why it is important.
Understanding Digital Product Development Management
Digital product development management is creating and managing digital products, such as software, applications, and websites. Effective digital product development management ensures that products are designed and developed with the end user in mind, and are delivered on time and within budget.
This activity has several benefits, including improved product quality, faster time-to-market, and increased customer satisfaction. However, managing product development can also be challenging due to the constantly evolving digital landscape and the need to stay ahead of the competition.
Critical Steps in Digital Product Development Management
Product development management involves a series of key steps that are critical to the success of any digital product. By following these steps and incorporating best practices, businesses can increase their chances of creating successful digital products that meet the needs of their target audience. Let’s outline the five key steps in product development management and provide tips and best practices for each step.
- Idea generation and concept development: This is the first step in the development of digital products. During this phase, ideas are generated, and concepts are developed. It is important to involve all stakeholders, including developers, designers, marketers, and business analysts.
- Market research and competitive analysis: In this step, market research is conducted to understand the needs and preferences of the target audience. Competitive analysis is also conducted to identify potential competitors and understand their strengths and weaknesses.
- Product design and prototyping: During this phase, the product design is created, and prototypes are developed. User feedback is collected to refine the design and ensure that it meets the needs of the target audience.
- Development and testing: This is the phase where the product is developed and tested. It is important to ensure that the product is developed according to the design and that it meets the needs of the target audience.
- Launch and post-launch: In this step, the product is launched, and a post-launch evaluation is conducted to determine whether the product is meeting the needs of the target audience. User feedback is collected and analyzed to identify areas for improvement.
Best Practices for Digital Product Development Management
To ensure successful product development management, it is important to follow best practices. Some of these best practices include:
- Team collaboration and communication: Effective collaboration and communication among team members are essential for successful product development. Regular team meetings and clear communication channels should be established.
- Effective project management: Effective project management is critical for succeeding in the development of digital products. Project milestones should be established, and progress should be regularly monitored.
- Utilizing Agile methodologies: Agile methodologies are becoming increasingly popular in digital product development management. Agile methodologies involve iterative development, which allows for flexibility and the ability to quickly respond to changes.
- Incorporating user feedback throughout the development process: User feedback should be collected and analyzed throughout the development process to ensure that the product meets the needs of the target audience.
Checklist for Successful Digital Product Development Management
To ensure successful product development management, at Huenei we use a checklist that summarizes all the important aspects of the process. We share it with you below so that you can take advantage of our experience and our work methodology in your projects:
- Establish clear goals and objectives for the product.
- Conduct market research and competitive analysis.
- Involve all stakeholders in idea generation and concept development.
- Create a detailed product design and develop prototypes.
- Develop the product and test it.
- Launch the product and collect user feedback.
- Analyze user feedback and make necessary improvements.
- Regularly monitor progress and adjust the development plan as necessary.
- Utilize Agile methodologies for flexibility.
- Communicate regularly with team members and stakeholders.
All in all, digital product development management is a critical process that requires careful planning and execution. By following best practices and utilizing our proposed checklist, businesses can ensure that their products are developed and launched successfully. By involving all stakeholders in the process, conducting market research, and incorporating user feedback throughout the development process, businesses can create products that meet the needs and preferences of their target audience.
Effective communication and collaboration among team members, as well as utilizing Agile methodologies, can also contribute to the successful development of digital products. By regularly monitoring progress and making necessary adjustments, businesses can ensure that their digital products are delivered on time and within budget.
by Tomás Freyer | May 6, 2023 | Process & Management
The Lean Project Charter is a document where we detail the main aspects and considerations of a project, based on its life cycle. This project management tool is a one-pager elaborated to formally authorize a project or a particular phase framed within one.
From an operational perspective, this document is a tool that gathers the work guidelines and functions as a framework that also delimits the software project or of any other nature. It documents the initial requirements that meet the needs and expectations of stakeholders. In this sense, it is useful to keep track of the project at all times and to be well organized during planning, implementation, and control.
Example by Techno-PM
Why carry out a Lean Project Charter?
Everything that is specified in this document we are going to plan and then we are going to execute. The purpose of this “cover letter” is to standardize and correctly plan the steps involved in the development of a project, in order to be able to carry it out safely from start to finish.
This project management tool links the decision-making managerial level with the project management level. Every project must have a project team led by the project manager. In this charter, it should be very specifically detailed what is the level of authority that this director has to make decisions within the project, whether they are decisions that affect it positively or negatively.
This document is prepared before the development of the project and all strategic stakeholders of the project must participate in its creation to align expectations, agree courses of action and establish preferences regarding the framework and reference of the project.
What is the structure of a Lean Project Charter?
There are various work templates and methodologies to organize a Project Charter, however, the Project Management Institute (PMI) has not defined a specific framework for its implementation. This realizes that each project and each organization shall adapt this project management tool to their particular needs. As general content, it can include the following sections that represent points that must be adapted to each project in particular:
- Project data. Here you should specify the enterprise, the project’s name, the date of preparation of the Project Charter, the clients, and the project manager.
- Purpose and justification, which allows demonstrating the reasons why the product or service in question needs to be developed. You should specify the context of the organization, the needs to satisfy, and all the legal requirements.
- Deliverables. This section is about the minimum viable products, documents, partial processes, and others, that are elaborated to complete and measure a project. It is important to clarify that the deliverables must be measurable and verifiable.
- Project life cycle. This phase represents the set of phases into which the project is divided. Many times we structure is based on some work methodology such as Design Thinking.
- Objectives of the project, which represent the goals that we set ourselves with the purpose of understanding, in the charter project, why we are carrying out this project.
- Budget, understood as the preliminary estimate of the resources needed to complete the project activities.
- Schedule of main milestones. These are activities that can be measured in duration, which mark important and key moments within the project. Some examples can be the official presentation of the project to the client, a meeting with the general manager to approve the project, periodic progress meetings to tell how the project is developing, and others. It is useful to structure the schedule using work methodologies such as the Kanban board or the Gantt chart.
- Stakeholders or interested parties. They are all those people and organizations, internal or external, who are involved in the project and who can positively or negatively influence its development. Once all the project stakeholders have been identified, the next step is to identify the expectations or interests that each of them has in carrying out the project. These will represent the fundamental requirements that must be considered in the realization of the project objectives.
We invite you to review this example of the development of a Lean Project Charter that can also serve as a template to develop yours.
For this document to be useful, it must be presented very briefly. At Huenei we like to understand it similarly to the Canvas model in business planning: The Project Charter must contain all the necessary and relevant information but must have the ability to be compressed into a single page. In this sense, like the Canvas model, the Lean Project Charter will allow us to have at a glance access to all the processes and flows involved in a project from a macro, global perspective.
We have covered the general aspects that a Project Charter should include, which allows administrators the possibility of seeing the most important factors of the project to be able to start it. It is finally necessary to remember that the charter project must be agreed upon and signed by the management positions, partners, and sponsors of the project.
As a corollary, we would like to emphasize that by using this tool we seek to avoid misunderstandings in the planning and execution of projects. In other words, we will always do what is registered in the Lean Project Charter and we will never do what this tool does not tell us.