From proof of concept to production?
Taking AsscherAi from proof of concept to production requires careful consideration of the costs and commitments involved, including the cost of supporting the system over time and integrating it with other systems, such as the purchase order table and the maintenance log.
Can we really take this from proof of concept to production, or are we just getting a feel for how it works in a demo? This question gets asked in meetings because the difference between a proof of concept and a production system is not just a matter of size, it is a difference in the kind of work that needs to be done, and the kind of commitment that needs to be made.
What each option genuinely commits you to
A proof of concept commits you to exploring an idea, and to finding out whether it is feasible. This means that you are committing to a process of investigation, and to a process of testing. You are not committing to a particular outcome, or to a particular implementation. A production system, on the other hand, commits you to delivering a working system, and to supporting it over time. This means that you are committing to a particular implementation, and to a process of maintenance and upkeep.
The distinction between these two commitments is important, because it affects the way that you approach the work. If you are building a proof of concept, you can focus on the core idea, and on testing its feasibility. If you are building a production system, you need to focus on the details of the implementation, and on ensuring that the system is reliable and maintainable.
The case where the other one is right
There are cases where a proof of concept is the right choice, even if you think you want a production system. For example, if you are not sure whether a particular technology is suitable for your needs, a proof of concept can be a good way to test it out. Similarly, if you are not sure whether a particular idea is feasible, a proof of concept can be a good way to explore it. On the other hand, there are also cases where a production system is the right choice, even if you think you only need a proof of concept. For example, if you have a clear idea of what you want to achieve, and you have the resources to support it, a production system can be a good way to deliver a working system quickly.
In general, the choice between a proof of concept and a production system depends on your goals, and on the level of uncertainty that you are facing. If you are unsure about the feasibility of an idea, or about the suitability of a technology, a proof of concept can be a good way to reduce that uncertainty. If you are clear about what you want to achieve, and you have the resources to support it, a production system can be a good way to deliver a working system.
The cost that only shows up later
One of the costs of taking a system from proof of concept to production is the cost of supporting it over time. This can include the cost of maintaining the system, the cost of updating it, and the cost of fixing any problems that arise. These costs can be significant, and they can add up quickly. For example, if you have a system that is used by many people, you may need to have a team of support staff available to help them with any issues that they encounter.
Another cost that can show up later is the cost of integrating the system with other systems. This can be a complex and time-consuming process, and it can require significant resources. For example, if you have a system that needs to integrate with a database, you may need to have a team of developers available to work on the integration.
A way to decide without a six month evaluation
One way to decide whether to take a system from proof of concept to production is to use a decision-making framework. This can help you to evaluate the pros and cons of each option, and to make a decision based on your goals and resources. For example, you can use a framework that considers the feasibility of the idea, the suitability of the technology, and the level of resources required to support it.
You can also use a framework that considers the potential benefits of each option, and the potential risks. For example, you can consider the potential benefits of taking a system to production, such as the ability to deliver a working system quickly, and the potential risks, such as the cost of supporting it over time. If you need help with this, you can contact us to discuss your options.
What this does not do
Taking a system from proof of concept to production does not guarantee success. There are many factors that can affect the success of a system, including the quality of the implementation, the level of support, and the level of user adoption. Additionally, taking a system to production does not mean that you will never need to make changes or updates. In fact, it is likely that you will need to make changes and updates over time, in order to keep the system running smoothly and to ensure that it continues to meet the needs of its users.
In general, taking a system from proof of concept to production is just one part of the overall process of delivering a working system. It is an important part, but it is not the only part. You will also need to consider the ongoing maintenance and support of the system, as well as the potential need for changes and updates over time.
Frequently asked questions
What is the difference between a proof of concept and a production system for AsscherAi?
A proof of concept commits to exploring an idea, while a production system commits to delivering a working system and supporting it over time.
How do I decide whether to take AsscherAi from proof of concept to production?
Use a decision-making framework to evaluate the pros and cons of each option, considering factors such as feasibility, suitability, and resources required.
What are the potential costs of taking AsscherAi from proof of concept to production?
The costs include supporting the system over time, integrating it with other systems, and maintaining and updating it, which can add up quickly.
Does taking AsscherAi from proof of concept to production guarantee success?
No, success depends on various factors, including the quality of the implementation, level of support, and user adoption, and changes and updates may still be needed over time.