APRIL 2019CIOAPPLICATIONSEUROPE.COM8IN MYOPINIONAre You Ready For Data Science?HERVÉ SCHNEGG, PRINCIPAL DATA SCIENTIST, THE TELEGRAPHor the last 10 years [1][2], companies have been complaining on how hard it is to hire data scientists. In the meantime, most data scientists keep changing jobs on a regular basis and invoke a lack of challenges as a reason for leaving. What is happening? My opinion is that companies are not hiring the right profiles at the right time and that they should start addressing a few issues before calling their favourite recruiters. Here are the main stages leading to a level of data maturity justifying the need for data scientists. At each stage, I describe the kind of professionals required to move to the next level.Stage 1 - Business PreparationFirst of all, companies need to assess how ready they are to start the journey that will transform them into data-driven businesses. Building a vision of what success looks like should be the starting point. Understanding the strengths, weaknesses, opportunities, and threats [3] of the environment in which they operate is still a valid approach. This initial analysis is what will feed into the definition of key performance indicators [4]. At that stage, working with experienced business consultants and business analysts is probably the best decision.Further, another important assessment also has to be performed at the business level. The critical point here is to decide whether the organisation is ready to base its decisions on data analysis or even recommendations of data models [5]. For traditional businesses, used to rely on the sole experience of domain experts, this might be the hardest challenge. Many experienced managers will struggle to go against their instinct and trust decisions coming from teams of new data experts lacking a deep experience of their industry. Much careful communication is required to explain that change is required and that using data can help finding new paths leading to success. Such an exercise should definitely start before the first data scientists are hired.Stage 2 - Technical PreparationTechnical questions needs to be addressed in parallel with those business considerations. Is the organisation capturing the data required to start performing data analysis? Some legacy systems might have been designed to help running some aspects of the business (eg. sales, logistics...), but do they expose data? Having access to the data related to any business process is critical to the success of the data science effort. Once again, hiring data scientists too early might prove extremely unproductive and frustrating. At that stage, working with internal system developers - or vendors - is required.The next question covers the processing and storage of the data. Once companies start capturing data, questions on how to make the data available for reporting and analysis have to be addressed. Traditionally, companies have built F
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