FAQs

#What does data-driven mean?

Decisions are made every day. Sometimes they seem obvious, sometimes they are uncertain, and sometimes they are made in a hurry.

When we talk about data driven, the objective is that these decisions are made based on the reality on the ground, and not on intuitions and feelings that can easily be biased and incorrect. For a company, access to the field is done through the collection and exploitation of data that allows us to reconstruct the information that interests us in order to answer a given question.

#I upload my data in the cloud, then what?

The Big Data, that magical and wonderful object in which you just have to put all the data to create value... does not exist!

The Big Data is a technological ecosystem. It has developed at dizzying speed and is now rich enough that there are one or more tools capable of responding to all the problems of data manipulation, transfer, persistence, etc...

The challenge now is to identify opportunities for value creation and to implement the appropriate tools.

#What does it mean to create value?

Data in an information system does not fall from the sky, and is not due to chance.

They are full of information that is characteristic of the way a company operates. Particular patterns, operating regimes, know-how (through the history of machine settings, in reports, etc.).

Creating value means above all identifying the precise needs within the business lines that would benefit from this information, generally saving time and/or money.

#I'm used to running computer projects. What's the difference with a data project?

A data project is like a box of chocolates: you never know what you're going to run into. There is a lot of uncertainty upstream because, despite all the good intentions, it is the quantity and above all the quality of the available data that dictates what we can do and how far we can go.

If you operate with specifications that act as an immutable perimeter, then your data project risks disappointing you. It is strongly recommended that you leave enough room for a project to evolve with this data quality, but at the same time have practices to master and control the risk by adopting iterative and incremental project management methods, and always having a response with a ROI as the final target.

#So, I have to do a Proof of Concept?

No: in our view, the term "PoC" (Proof of Concept) has a connotation of an attempt with no future. We much prefer the "MVP" (Minimum Viable Product) approach: a short project that has to go into production, in real life, even though everyone knows it will be expanded and improved iteratively.

#How do I involve industry professionals in discussing data and innovation?

What not to do: "techno-push", meaning selling the trades an incredible new technology that will revolutionize their work, but hoping that the value will appear of its own accord when it is used. Our experience shows that a good approach is to start from a real business problem and to remain open to solutions that can respond to it.