Data has become a key driver in our Society in a context where it is even listed as the new Oil of the century, we carefully need to not rush into it but be prepared to face new challenges either from Business or Technology to form a new Equilibrium. For this here are the essential questions that we must ask ourselves :

How to drive Data Initiative in the right way

• Build your portfolio and road-map about Data & Analytics Project
• Set KPIs and Maturity Matrix to follow the evolution of that initiative
• This needs to cover not only the delivery of the IT project but a follow up of the usage by the Business
• Include sustainability as a tactical requirement to define if you need to put that effort on that topic
• Gartner remarks that company are doing the right set of things but not the right amount of effort

How do you educate and make your company a fast learner around Data

• Start Data Literacy Program
• Get your Organization moving
• Pre-requisite: you need a way to build your Databook referring to all your Data Champions actual and future data speaker
• Look around D&I program and Continuous learning with your HR
• Know the skills you need and the sufficient experience for someone to acquire it

How do you steer your Metadata Program

• Master the definition all the data of your company in one place
• Serve the purpose of Data & Analytics use case and Operating/Tooling your Data Governance initiative

How do you quantify the value of your data: Infonomics

• How to measure and set value around data
  • Pre-requisite: linked to the portfolio and the data catalog because if you do not list your information how can you quantify the value of it
• How to measure the outcome of new data created :
  • i.e how to measure outcomes of your data science initiative
  • Each project use case must have a driver to define its level of completeness and success

How do you Operate: Organization, build your Operating Model

• Governance is key to leverage the equilibrium you need between tech and Business
• Choose the right level between centralized and local team

How do you Innovate and Prepare the future: Create a Lab or an Innovation Center

• The same way you created or willing to create a central data science lab you need this cell to explore emerging technology with great change focus or  adaptability  to provide new tool or ideas

How do you provide the right data to the right person at the right time?

• Building at the speed of light is not an easy thing to do if you do not have a solid foundation
• The Data Architecture is here to design, promote the Data factory platform of your company
• It is also the place to define the different howto you need and the tools and technologies you want to provide