Demand for Data Scientists and the Datification of Business

You cannot improve and manage what you cannot measure.

.
Datification means we have more and more data to measure things and organizations are increasingly dependent on data - both internal and external - to optimally operate to compete and win. It is also about taking a process or activity that was previously invisible and turning it into data. That data can then be measured, tracked and monitored to optimize processes, make better decisions and innovate.

The amount of business data is starting to explode as the world’s information is doubling every two years. IDC estimates the volume of digital data will grow 40% to 50% per year. By 2020, IDC predicts the number will have reached 40,000 EB, or 40 Zettabytes (ZB). By 2020 the world will generate 50 times the amount of information and 75 times the number of information containers.

IDC also estimates that less than 1% of world data is analyzed and thus demand for data scientists will significantly increase. McKinsey estimates the United States alone needs about 190,000 data scientists in addition to another 1.5 million data-savvy managers to handle the data and make game-changing decisions.

The trick is to generate value by extracting the right information from data and turning information into actionable intelligence. Data scientists can help an organization transform from descriptive analytics to a predictive and prescriptive analytics strategy.

.
It is prudent for organizations to capture, store and analyze any and all information, even if they're not sure what insights the data will provide. Later the organization can decide what to look for to make better decisions on the operational level, innovate new products and services on the tactical level, and make game changing shifts on the strategic level.

Collecting and storing data from multiple sources and forming data science teams to combine, slice and dice this data to create valuable, actionable insights from the data - is the key to developing durable competitive advantage.

See: http://bit.ly/10TgVHG

Tags: Analytics, Business, Data, Datification, Descriptive, Predictive, Prescriptive, Scientists

5 members like this

Comment

You need to be a member of Data Science Central to add comments!

Join Data Science Central

Comment by SUNIL NAGRA on October 19, 2015 at 10:03pm: Informative...

Comment by Chris on July 27, 2013 at 11:33am: Michael, you tackle the right itch of the current hiring situation in the U.S. Companies hopelessly look for the right person to the right job, the career track is new, countless underemployed and unemployed (not to mention the security clearance bottleneck).

Anyway, the career track is different than the traditional database ten years ago. You also hear the issues of "office culture, team spirit, fit the culture"...The problem is, corporations and HR are too lazy to look beyond their demands and find a solution to the core issue: a green career field and the need of training vs. culture fit issue; Meaning either you hire based on character standards, or you lower the culture fit issue and invest in training instead. Even the government is also lazy too in their core issue the need of filling jobs and the reluctancy to trust beyond "inner circles".