Beyond Artificial Intelligence: Providing Insights to Your Customers

Providing your client with insights, briefly defined as short texts of analytically processed information, is a valuable addition to the services provided by virtually any company. Unfortunately, as engineers, or technicians in general, our training does not address in detail the techniques for writing insights. This short text seeks to serve as a basic guide for future analysts. I introduce the concept of insight and provide advice for the creation of concise and short intelligence pieces.

As a senior data analyst, I must do precisely what Ray Dalio, finance magnate, mentions in his December 2019 conversation with Lex Fridman in his podcast “Artificial Intelligence” when asked what role machine learning will play in making decisions and in the analysis:

“AI is particularly good at processing data, but the notion of what you want to do is most of the time better determined by the human mind. What are the principles? ” (Approximate quote) - Ray Dalio in an interview with Lex Fridman

TSC.ai (where I work as a Senior Data Analyst) is a technology company
that uses artificial intelligence to provide, precisely, intelligence to our
customers. In part, this intelligence is provided through insights.

Be careful, an insight is not the same as a report or a thorough investigation. An insight is a short text, less than 2,000 words, that provide intelligence to a client who does not expect to read a 10,000 paper or read five news to arrive to a conclusion on a topic. Examples of what are perhaps the most famous insights are in the Bloomberg QuickTake series.

The insights provided to the client require information processing for their creation. For the information processing the analyst can use tools such as articial intelligence, for example Atium of TSC.ai, however, this is not enough. The AI has serves as an invaluable tool for the creation of intelligence, it is formidable in the work of processing data for the prediction or identication of patterns. However, we are at a point where AI is not yet excellent in decision making that involves considering a large number of variables that evolve over time (playing Go or Poker does not apply): As Dalio says in the same interview, you will not allow an AI to dene how you are going to educate your children.

Once data is processed by the AI, the analyst has the decision of how to use the information, if he uses it, to make it useful for the client. Think, for example, of an NLP algorithm that identies names of persons in news and creates a summary of the story; in this case, when carrying out the analysis, it must be decided whether, given the fundamentals of what is important for our client, the news is of sufcient relevance or not, and whether the individuals identied are relevant to the story we want to provide to our client

Ajay Agrawal, Joshua Gans and Avi Goldfarbo, make it clear in “Prediction Machines: The Simple Economics of Artificial Intelligence”: although prediction (provided through AI) is a key component of intelligence, it is not one in the same.

To provide intelligence, artificial intelligence is not enough. Insights are precisily that and can only be made by humans.

Next, I will present some relevant points that my team and I have found for performing quality insights. But, first of all, remember the main rule:

Put crudely, the objective is to develop quality insights that will be sent to very, very busy people (customers) who want to see the note in two minutes.

The work of the analysts will be based on three fundamental pillars which I adressed here: 1) search for information, 2) writing, and 3) content structuring.

1) Search for information

• For this, a reliable and reliable search engine must be used. To my experience, Google is enough.
• At the time of the search it is advisable to use keywords on the subject under investigation. Example: If the insight must address the process and current state of the regulation of financial technology companies (FinTech) in Argentina, it is advisable to enter keywords in the Google search bar as follows: regulation+fintech+Argentina.
• Select recent information, as recent as possible. The idea is to offer the reader the latest events on the requested topic.
• Consider the information contained in reliable websites. On the internet there is a lot of information and most is not good or serious.
• As an additional, you can read: 10 Advanced Web Search Techniques You Probably Never Knew About; although, according to my experience, this is enough most of the time.

2) About the writing

The quality of an insight is not in its extension but in its content: clear ideas, short and successful writing.

• As I mentioned, most customers want to read your insight in two
  minutes. For this, the extension of the insight will range between
  one and two pages. Visualizations are great! At TSC.ai we provide
  maps of relationships between stakeholders that make insights more
  digestible. For example, look at this map, in Spanish, about the
  exponents of a new 2020 tax in Argentina:

• If you have not previously read about the subject under investigation, it is impossible to start developing the insight. Therefore, it is necessary to start by making a good reading of the information found. Then, write a very concise title that reflects the objetive of your text. The title could be something like "New Mexican Tax Focus on Digital Services" or "The Influence of Cristina Fernandez on the Argentinean Government in 2020".
• Whenever possible, look at the title of your insight to remember what it is about. The only objective mentioned in the title must be met.
• If you are still your first insights, I recommend that at the end of your insight you reread it and make a commitment to reduce at least one third of the words used. This will force you to keep it concrete and short. This concept and more are in the excellent book "On Writing Well" by William Zinsser.
• Do not write superfluous words for padding!

3) Content structuring

Since the content of the insight depends on the addressed topic, there is no recipe for the structure of the insight. Therefore, the creativity of the analyst and his own initiative is appreciated at the time of bashing the ideas in a coherent and orderly speech.

Here is the general structure I recomend. For the beginning of the insight:

• Title: it must be concise, easy to understand (consider that it will not be aimed at academics) and directly related to the main objective of the insight.
• Date and place: indicate the day on which the report has been prepared/updated and the place from where it has been prepared.
• Introduction: in a paragraph, the topic to be addressed should be briefly introduced; In other words, give an opening on the purpose of the insight (what will it be about?).

For the main body:

Avoid writing a lot and saying little. That is, go to the point.

Finally, remember...

Artificial intelligence is an excellent tool to provide intelligence to your customers. However, most of the time it will not be enough; It will take the human component that processes the information. In this short text, the concept of insight is introduced as a piece of short text that provides concise information that, ideally, can be read in two minutes.