Quality versus Completeness - how to assure quality with the least effort

With the overload of information coming our way these days, the hardest part is bridging the gap between gathering the most complete set of information and assuring you get the right quality of knowledge to work with. An AI assistant can help you with this, but it’s of course not the complete answer.

Let’s try and find the answer to the question "What's the right balance between quality and completeness?". And why is it so hard…

Quality is about being correct and exact about a topic. Completeness is about having all the relevant data for the topic.

If you're a commercial person working on a proposal or a consultant writing that final report, it's an easy way out to be lazy and not make sure that the result is as good as possible. All this hard work! However, you’re not like that. For the sake of the company, the customer and your career, you need to shine.

So you take on the challenge of being super-detailed with every aspect of what makes up what you’re creating and make it a success. 2 basic rules to guide in this process are:

• Be as complete as possible so all bases are covered in an efficient manner. You can’t leave gaps or holes which could lead others down paths where they won't get the complete information
• Be as detailed  & correct as possible. As worse as giving not enough information, is giving the wrong information.

So how to make sure I get the best results? Let’s ask the help of an AI or automated assistant. It will fix all your problems right?

Ai assistants can help you find exactly the right information and summarize it. However it may miss the exact qualitative point you're trying to make.

It's not always easy to manually find exactly the right information in an efficient way. However, there is another way to get to the core; the use of an automated extraction. A solution that helps you with the process of taking the huge amounts of knowledge you have to work with and turn it into a structured set to be analyzed by a machine and consequently give you what you’re looking for in a speedy way.

This makes the process of finding and re-using the correct information scalable and less of a stress on time and resources. It also takes away the complexity of sifting through tons of content from sometimes millions of company sources.

There are still some drawbacks in using an AI assistant of course. It is able to provide us with all the facts necessary for our business decisions but it can’t take the decisions itself instead of a human. It’s still an assistant.

So we go back to human hands to find the ultimate answer then?  

Human knowledge engagement gets you the qualitative content you need, summarized with the exact parameters.

Instinctively, we feel humans still have a greater capacity for critical thinking and problem-solving than an AI. It should allow them to better understand the context and nuances of a given situation, especially with complex or unfamiliar information.

Also, we have our intuition and experience to make judgments and decisions that may not be possible with AI or automated systems. Also the communication and collaboration with other people, is another plus for the quality of the final product. We share information and insights, and work together to come up with creative solutions and give it a personal touch.

Damn, this is hard. What do you want? Man versus machine? Nope. It’s a marriage of qualities we propose.

Finding the right equilibrium between both manual and automation means always getting the right summarized and qualitative information but don't lose the oversight or possibility to scale.

So we found the automated systems can be useful complements to human knowledge and expertise. No big man versus machine war coming our way yet. Finding the right equilibrium between both means always getting the right summarized and qualitative information but don't lose the oversight or possibility to scale. We use the machine to handle the large tasks and process big amounts of data. We use them where they are strong, helping people find exactly the right information to work with.

There are many ways to handle the completeness versus quality tradeoff. It all depends on your needs and goals. However, the ideal way is to come to the perfect collaboration between man and machine. Just be aware of the pitfalls associated with relying too heavily on AI assistants (or on the human brain for that matter 🙂)  

Do you want to make sure you cover both completeness and quality? Then it looks like you’re looking for the uman AI assistant, which has the equilibrium exactly where it should be.

Read about how uman’s AI platform makes you keep control on quality and completeness.

‍