Frederik Van Holle, Partner at Deloitte remembers one of his first projects, 20 years ago, where only 2 weeks before the go live, the CFO requested a report before giving approval to proceed. In addition, the data model was not built to easily extract such kind of reports.

Having the data right at the beginning of a project is extremely important. A company with a Data First mindset, allows their business leaders to take better informed decisions.

However, it is important to make a distinction between ‘hindsight’ and ‘foresight’.

• Hindsight means looking into the mirror to see what happened in the past and what is the state of the business (historical data).
• Foresight is an extra layer on top of the hindsight. By applying techniques such as AI (artificial intelligence) and machine learning, companies can predict some aspects of the business in the future. Introducing the foresight will never replace all the decision makers but will enrich the decisions they are making.

Frederik shares an example of how this data can be extremely useful:

Some companies just ignore any transformation or are simply not ready for one. Even though, they should always think ‘Data and Analytics First’.

Julien reveals a concrete example. ‘Due to geopolitical circumstances, the board of a client decided to postpone a project for one year. Thanks to the ‘Data First’ sessions Deloitte had with the business stakeholders, they identified preparation activities around data archiving and governance for the client to work on during that year. The outcome returned into a lower TCO (total cost of ownership) with reduced system capacity requirements, a higher level of confidence with increased data quality and faster decision making with proper data ownership.’

Frederik explains why it is important to define the right reporting:

Correlations between data elements will only be discovered after ‘playing’ with the data. It might be a good idea to install a kind of ‘sandbox for data scientists’. Even though this environment may not be connected with the production systems, it should still contain real data. Creativity of employees often provides surprising insights.

A good example is a client in medtech wanting to have a better sales forecasts and predictability for a certain device in order to optimise stocks. By analysing data, they discovered a remarkably interesting correlation between their data and the public data that was published around diseases by governments. Consequently, they could use that data to better predict future sales.

If a company decides not to move to the Data and Analytics First method, it will lose its competitive advantage.

Organisations who implement this methodology can make better informed decisions in addition to the following advantages:

• Better knowledge of customer and market
• Better prediction and steering of sales volumes
• Better stock management
• More efficient supply chain
• Better operations in general

• Data First is a mindset
• Not only focus on Hindsight but also on Foresight
• Start early and small, scale up when needed
• Involve the right stakeholders
• Install a Sandbox for data scientists to reveal surprising insights